[Clinical Infectious Diseases, 1 February 2023]

Background: The rapid development of safe and effective vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a singular scientific achievement. Confounding due to health-seeking behaviors, circulating variants, and differential testing by vaccination status may bias analyses toward an apparent increase in infection severity following vaccination.

Methods: We used data from the Ontario, Canada, Case and Contact Management Database and a provincial vaccination dataset (COVaxON) to create a time-matched cohort of individuals who were hospitalized with SARS-CoV-2 infection. Vaccinated individuals were matched to up to 5 unvaccinated individuals based on test date. Risk of intensive care unit (ICU) admission and death were evaluated using conditional logistic regression.

Results: In 20 064 individuals (3353 vaccinated and 16 711 unvaccinated) hospitalized with infection due to SARS-CoV-2 between 1 January 2021 and 5 January 2022, vaccination with 1, 2, or 3 doses significantly reduced the risk of ICU admission and death. An inverse dose–response relationship was observed between vaccine doses received and both outcomes (adjusted odds ratio [aOR] per additional dose for ICU admission, 0.66; 95% confidence interval [CI], .62 to .71; aOR for death, 0.78; 95% CI, .72 to .84).

Conclusions: We identified decreased virulence of SARS-CoV-2 infections in vaccinated individuals, even when vaccines failed to prevent infection sufficiently severe to cause hospitalization. Even with diminished efficacy of vaccines against infection with novel variants of concern, vaccines remain an important tool for reduction of ICU admission and mortality.

[Clinical Infectious Diseases, 1 February 2023]

Background: Pregnancy represents a physiological state associated with increased vulnerability to severe outcomes from infectious diseases, both for the pregnant person and developing infant. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic may have important health consequences for pregnant individuals, who may also be more reluctant than nonpregnant people to accept vaccination.

Methods: We sought to estimate the degree to which increased severity of SARS-CoV-2 outcomes can be attributed to pregnancy using a population-based SARS-CoV-2 case file from Ontario, Canada. Because of varying propensity to receive vaccination, and changes in dominant circulating viral strains over time, a time-matched cohort study was performed to evaluate the relative risk of severe illness in pregnant women with SARS-CoV-2 compared to other SARS-CoV-2 infected women of childbearing age (10–49 years old). Risk of severe SARS-CoV-2 outcomes was evaluated in pregnant women and time-matched nonpregnant controls using multivariable conditional logistic regression.

Results: Compared with the rest of the population, nonpregnant women of childbearing age had an elevated risk of infection (standardized morbidity ratio, 1.28), whereas risk of infection was reduced among pregnant women (standardized morbidity ratio, 0.43). After adjustment for confounding, pregnant women had a markedly elevated risk of hospitalization (adjusted odds ratio, 4.96; 95% confidence interval, 3.86–6.37) and intensive care unit admission (adjusted odds ratio, 6.58; 95% confidence interval, 3.29–13.18). The relative increase in hospitalization risk associated with pregnancy was greater in women without comorbidities than in those with comorbidities (P for heterogeneity, .004).

Conclusions: Given the safety of SARS-CoV-2 vaccines in pregnancy, risk-benefit calculus strongly favors SARS-CoV-2 vaccination in pregnant women.

[Clinical Infectious Diseases, 1 February 2023]

Background: In late 2021, the Omicron severe acute respiratory syndrome coronavirus 2 variant emerged and rapidly replaced Delta as the dominant variant. The increased transmissibility of Omicron led to surges in case rates and hospitalizations; however, the true severity of the variant remained unclear. We aimed to provide robust estimates of Omicron severity relative to Delta.

Methods: This retrospective cohort study was conducted with data from the British Columbia COVID-19 Cohort, a large provincial surveillance platform with linkage to administrative datasets. To capture the time of cocirculation with Omicron and Delta, December 2021 was chosen as the study period. Whole-genome sequencing was used to determine Omicron and Delta variants. To assess the severity (hospitalization, intensive care unit [ICU] admission, length of stay), we conducted adjusted Cox proportional hazard models, weighted by inverse probability of treatment weights (IPTW).

Results: The cohort was composed of 13 128 individuals (7729 Omicron and 5399 Delta). There were 419 coronavirus disease 2019 hospitalizations, with 118 (22%) among people diagnosed with Omicron (crude rate = 1.5% Omicron, 5.6% Delta). In multivariable IPTW analysis, Omicron was associated with a 50% lower risk of hospitalization compared with Delta (adjusted hazard ratio [aHR] = 0.50, 95% confidence interval [CI] = 0.43 to 0.59), a 73% lower risk of ICU admission (aHR = 0.27, 95% CI = 0.19 to 0.38), and a 5-day shorter hospital stay (aß = −5.03, 95% CI = −8.01 to −2.05).

Conclusions: Our analysis supports findings from other studies that have demonstrated lower risk of severe outcomes in Omicron-infected individuals relative to Delta.

[BMJ Open Respiratory Research, 2 February 2023]

Introduction: We compared the population rate of COVID-19 and influenza hospitalisations by age, COVID-19 vaccine status and pandemic phase, which was lacking in other studies.

Method: We conducted a population-based study using hospital data from the province of British Columbia (population 5.3 million) in Canada with universal healthcare coverage. We created two cohorts of COVID-19 hospitalisations based on date of admission: annual cohort (March 2020 to February 2021) and peak cohort (Omicron era; first 10 weeks of 2022). For comparison, we created influenza annual and peak cohorts using three historical periods years to capture varying severity and circulating strains: 2009/2010, 2015/2016 and 2016/2017. We estimated hospitalisation rates per 100 000 population.

Results: COVID-19 and influenza hospitalisation rates by age group were ‘J’ shaped. The population rate of COVID-19 hospital admissions in the annual cohort (mostly unvaccinated; public health restrictions in place) was significantly higher than influenza among individuals aged 30–69 years, and comparable to the severe influenza year (2016/2017) among 70+. In the peak COVID-19 cohort (mostly vaccinated; few restrictions in place), the hospitalisation rate was comparable with influenza 2016/2017 in all age groups, although rates among the unvaccinated population were still higher than influenza among 18+. Among people aged 5–17 years, COVID-19 hospitalisation rates were lower than/comparable to influenza years in both cohorts. The COVID-19 hospitalisation rate among 0–4 years old, during Omicron, was higher than influenza 2015/2016 and 2016/2017 and lower than 2009/2010 pandemic.

Conclusions: During first Omicron wave, COVID-19 hospitalisation rates were significantly higher than historical influenza hospitalisation rates for unvaccinated adults but were comparable to influenza for vaccinated adults. For children, in the context of high infection levels, hospitalisation rates for COVID-19 were lower than 2009/2010 H1N1 influenza and comparable (higher for 0–4) to non-pandemic years, regardless of the vaccine status.

[BIOMATH, 27 January 2023]

We investigate a model of the early stage of the COVID-19 epidemic comprising undetected infected individuals as well as behavioural change towards the use of self-protection measures. The model is fitted to China data reported between 22 January and 29 June 2020. Using fitting results, we then consider model responses to varying screening intensities.

[JMIR Public Health and Surveillance, 11 January 2023]

Background: Face mask use has been associated with declines in COVID-19 incidence rates worldwide. A handful of studies have examined the factors associated with face mask use in North America during the COVID-19 pandemic; however, much less is known about the patterns of face mask use and the impact of mask mandates during this time. This information could have important policy implications, now and in the event of future pandemics.

Objective: To address existing knowledge gaps, we assessed face mask usage patterns among British Columbia COVID-19 Population Mixing Patterns (BC-Mix) survey respondents and evaluated the impact of the provincial mask mandate on these usage patterns.

Methods: Between September 2020 and July 2022, adult British Columbia residents completed the web-based BC-Mix survey, answering questions on the circumstances surrounding face mask use or lack thereof, movement patterns, and COVID-19–related beliefs. Trends in face mask use over time were assessed, and associated factors were evaluated using multivariable logistic regression. A stratified analysis was done to examine effect modification by the provincial mask mandate.

Results: Of the 44,301 respondents, 81.9% reported wearing face masks during the 23-month period. In-store and public transit mask mandates supported monthly face mask usage rates of approximately 80%, which was further bolstered up to 92% with the introduction of the provincial mask mandate. Face mask users mostly visited retail locations (51.8%) and travelled alone by car (49.6%), whereas nonusers mostly traveled by car with others (35.2%) to their destinations—most commonly parks (45.7%). Nonusers of face masks were much more likely to be male than female, especially in retail locations and restaurants, bars, and cafés. In a multivariable logistic regression model adjusted for possible confounders, factors associated with face mask use included age, ethnicity, health region, mode of travel, destination, and time period. The odds of face mask use were 3.68 times greater when the provincial mask mandate was in effect than when it was not (adjusted odds ratio [aOR] 3.68, 95% CI 3.33-4.05). The impact of the mask mandate was greatest in restaurants, bars, or cafés (mandate: aOR 7.35, 95% CI 4.23-12.78 vs no mandate: aOR 2.81, 95% CI 1.50-5.26) and in retail locations (mandate: aOR 19.94, 95% CI 14.86-26.77 vs no mandate: aOR 7.71, 95% CI 5.68-10.46).

Conclusions: Study findings provide added insight into the dynamics of face mask use during the COVID-19 pandemic. Mask mandates supported increased and sustained high face mask usage rates during the first 2 years of the pandemic, having the greatest impact in indoor public locations with limited opportunity for physical distancing targeted by these mandates. These findings highlight the utility of mask mandates in supporting high face mask usage rates during the COVID-19 pandemic.

[Int. J. Environ. Res. Public Health, 10 January 2023]

Throughout the COVID-19 pandemic, numerous non-human species were shown to be susceptible to natural infection by SARS-CoV-2, including farmed American mink. Once infected, American mink can transfer the virus from mink to human and mink to mink, resulting in a high rate of viral mutation. Therefore, outbreak surveillance on American mink farms is imperative for both mink and human health. Historically, disease surveillance on mink farms has consisted of a combination of mortality and live animal sampling; however, these methodologies have significant limitations. This study compared PCR testing of both deceased and live animal samples to environmental samples on an active outbreak premise, to determine the utility of environmental sampling. Environmental sampling mirrored trends in both deceased and live animal sampling in terms of percent positivity and appeared more sensitive in some low-prevalence instances. PCR CT values of environmental samples were significantly different from live animal samples’ CT values and were consistently high (mean CT = 36.2), likely indicating a low amount of viral RNA in the samples. There is compelling evidence in favour of environmental sampling for the purpose of disease surveillance, specifically as an early warning tool for SARS-CoV-2; however, further work is needed to ultimately determine whether environmental samples are viable sources for molecular epidemiology investigations.

[Epidemics, 25 January 2023]

Asymptomatic and symptomatic SARS-CoV-2 infections can have different characteristic time scales of transmission. These time-scale differences can shape outbreak dynamics as well as bias population-level estimates of epidemic strength, speed, and controllability. For example, prior work focusing on the initial exponential growth phase of an outbreak found that larger time scales for asymptomatic vs. symptomatic transmission can lead to under-estimates of the basic reproduction number as inferred from epidemic case data. Building upon this work, we use a series of nonlinear epidemic models to explore how differences in asymptomatic and symptomatic transmission time scales can lead to changes in the realized proportion of asymptomatic transmission throughout an epidemic. First, we find that when asymptomatic transmission time scales are longer than symptomatic transmission time scales, then the effective proportion of asymptomatic transmission increases as total incidence decreases. Moreover, these time-scale-driven impacts on epidemic dynamics are enhanced when infection status is correlated between infector and infectee pairs (e.g., due to dose-dependent impacts on symptoms). Next we apply these findings to understand the impact of time-scale differences on populations with age-dependent assortative mixing and in which the probability of having a symptomatic infection increases with age. We show that if asymptomatic generation intervals are longer than corresponding symptomatic generation intervals, then correlations between age and symptoms lead to a decrease in the age of infection during periods of epidemic decline (whether due to susceptible depletion or intervention). Altogether, these results demonstrate the need to explore the role of time-scale differences in transmission dynamics alongside behavioral changes to explain outbreak features both at early stages (e.g., in estimating the basic reproduction number) and throughout an epidemic (e.g., in connecting shifts in the age of infection to periods of changing incidence).

[Health Care Management Science, 24 January 2023]

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes and relaxation of mitigation measures leave many US communities at risk for surges of COVID-19 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop a framework to generate simple classification rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. This framework uses a simulation model of SARS-CoV-2 transmission and COVID-19 hospitalizations in the US to train classification decision trees that are robust to changes in the data-generating process and future uncertainties. These generated classification rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We show that these classification rules present reasonable accuracy, sensitivity, and specificity (all ≥ 80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19. Our proposed classification rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.

[Clinical Microbiology, 10 January 2023]

We compared the seroprevalence of SARS-CoV-2 anti-nucleocapsid antibodies in blood donors across Canadian regions in 2021. The seroprevalence was the highest in Alberta and the Prairies, and it was so low in Atlantic Canada that few correlates were observed. Being male and of young age were predictive of seropositivity. Racialization was associated with higher seroprevalence in British Columbia and Ontario but not in Alberta and the Prairies. Living in a materially deprived neighborhood predicted higher seroprevalence, but it was more linear across quintiles in Alberta and the Prairies, whereas in British Columbia and Ontario, the most affluent 60% were similarly low and the most deprived 40% similarly elevated. Living in a more socially deprived neighborhood (more single individuals and one parent families) was associated with lower seroprevalence in British Columbia and Ontario but not in Alberta and the Prairies. These data show striking variability in SARS-CoV-2 seroprevalence across regions by social determinants of health.

[JAMA Network Open, 29 December 2022]

Importance: Lockdown measures and the stress of the COVID-19 pandemic are factors associated with increased risk of violence, yet there is limited information on trends in emergency department (ED) encounters for sexual assault.

Objective: To compare changes in ED encounters for sexual assault during the COVID-19 pandemic vs prepandemic estimates.

Design, Setting, and Participants: This retrospective, population-based cohort study used linked health administrative data from 197 EDs across Ontario, Canada, representing more than 15 million residents. Participants included all patients who presented to an ED in Ontario from January 11, 2019, to September 10, 2021. Male and female individuals of all ages were included. Data analysis was performed from March to October 2022.

Exposures: Sexual assault, defined through 27 International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, procedure and diagnoses codes.

Main Outcomes and Measures: Ten bimonthly time periods were used to compare differences in the frequency and rates of ED encounters for sexual assault between 2020 to 2021 (during the pandemic) compared with baseline prepandemic rates in 2019. Rate differences (RDs) and age adjusted rate ratios (aRRs) and Wald 95% CIs were calculated using Poisson regression.

Results: From January 11, 2019, to September 10, 2021, there were 14 476 656 ED encounters, including 10 523 for sexual assault (9304 [88.4%] among female individuals). The median (IQR) age was 23 (17-33) years for female individuals and 15 (4-29) years for male individuals. Two months before the pandemic, ED encounters increased for sexual assault among female individuals (8.4 vs 6.9 cases per 100 000; RD, 1.51 [95% CI, 1.06 to 1.96]; aRR, 1.22 [95% CI, 1.09 to 1.38]) and male individuals (1.2 vs 1.0 cases per 100 000; RD, 0.19 [95% CI, 0.05 to 0.36]; aRR, 1.19 [95% CI, 0.87 to 1.64]). During the first 2 months of the pandemic, the rates decreased for female individuals (4.2 vs 8.3 cases per 100 000; RD, −4.07 [95% CI, −4.48 to −3.67]; aRR, 0.51 [95% CI, 0.44 to 0.58]) and male individuals (0.5 vs 1.2 cases per 100 000; RD, −0.72 [95% CI, −0.86 to −0.57]; aRR, 0.39 [95% CI, 0.26 to 0.58]). For the remainder of the study period, the rates of sexual assault oscillated, returning to prepandemic levels during the summer months and between COVID-19 waves.

Conclusions and Relevance: These findings suggest that lockdown protocols should evaluate the impact of limited care for sexual assault. Survivors should still present to EDs, especially when clinical care or legal interventions are needed.

[JAMA Network Open, 28 December 2022]

Consensus exists among US transplant authorities to encourage COVID-19 vaccination in candidate organ recipients to minimize risk of posttransplant infection and increase odds of organ acceptance amid scarce organ resources.1 However, only 36% of US transplant centers require COVID-19 vaccination.2 While lifestyle and vaccination requirements are not new organ transplant conditions, the misinformation and public controversy surrounding COVID-19 policies may have led to misinformed or unbalanced portrayals of COVID-19 vaccines in the popular press.3 In this qualitative study, we examined newspaper coverage of the COVID-19 vaccination requirement for organ transplant to understand reporting portrayals.

[Journal of Medical Virology, 22 December 2022]

The SARS-CoV-2 variant Omicron emerged in late 2021. In British Columbia (BC), Canada, and globally, three genetically distinct subvariants of Omicron, BA.1, BA.2, and BA.5, emerged and became dominant successively within an 8-month period. SARS-CoV-2 subvariants continue to circulate in the population, acquiring new mutations that have the potential to alter infectivity, immunity, and disease severity. Here, we report a propensity-matched severity analysis from residents of BC over the course of the Omicron wave, including 39,237 individuals infected with BA.1, BA.2, or BA.5 based on paired high-quality sequence data and linked to comprehensive clinical outcomes data between December 23, 2021 and August 31, 2022. Relative to BA.1, BA.2 cases were associated with a 15% and 28% lower risk of hospitalization and intensive care unit (ICU) admission (aHRhospital = 1.17; 95% confidence interval [CI] = 1.096–1.252; aHRICU = 1.368; 95% CI = 1.152–1.624), whereas BA.5 infections were associated with an 18% higher risk of hospitalization (aHRhospital = 1.18; 95% CI = 1.133–1.224) after accounting for age, sex, comorbidities, vaccination status, geography, and social determinants of health. Phylogenetic analysis revealed no specific subclades associated with more severe clinical outcomes for any Omicron subvariant. In summary, BA.1, BA.2, and BA.5 subvariants were associated with differences in clinical severity, emphasizing how variant-specific monitoring programs remain critical components of patient and population-level public health responses as the pandemic continues.

[The Lancet Global Health, January 2023]

Background: The WHO Strategic Advisory Group of Experts recommended that an extended interval of 3–5 years between the two doses of the human papillomavirus (HPV) vaccine could be considered to alleviate vaccine supply shortages. However, three concerns have limited the introduction of extended schedules: girls could be infected between the two doses, the vaccination coverage for the second dose could be lower at ages 13–14 years than at ages 9–10 years, and identifying girls vaccinated with a first dose to give them the second dose could be difficult. Using mathematical modelling, we examined the potential effect of these concerns on the population-level impact and efficiency of extended dose HPV vaccination schedules.

Methods: We used HPV-ADVISE, an individual-based, transmission-dynamic model of multitype HPV infection and disease, calibrated to country-specific data for four low-income and middle-income countries (India, Viet Nam, Uganda, and Nigeria). For the extended dose scenarios, we varied the vaccination coverage of the second dose among girls previously vaccinated, the one-dose vaccine efficacy, and the one-dose vaccine duration of protection. We also examined a strategy in which girls aged 14 years were vaccinated irrespective of their previous vaccination status. We used a scenario of girls-only two-dose vaccination at age 9 years (vaccine=9 valent, vaccine-type efficacy=100%, duration of protection=lifetime, and coverage=80%) as our comparator. We estimated two outcomes: the relative reduction in the age-standardised cervical cancer incidence (population-level impact) and the number of cervical cancers averted per 100 000 doses (efficiency).

Findings: Our model projected substantial reductions in cervical cancer incidence over 100 years with the two-dose schedule (79–86% depending on the country), compared with no vaccination. Projections for the 5-year extended schedule, in which the second dose is given only to girls previously vaccinated at age 9 years, were similar to the current two-dose schedule, unless vaccination coverage of the second dose is very low (reductions in cervical cancer incidence of 71–78% assuming 30% coverage at age 14 years among girls vaccinated at age 9 years). However, when the dose at age 14 years is given to girls irrespective of vaccination status and assuming high vaccination coverage, the model projected a substantially greater reduction in cervical cancer incidence compared with the current two-dose schedule (reductions in cervical cancer incidence of 86–93% assuming 70% coverage at age 14 years, irrespective of vaccination status). Efficiency of the extended schedule was greater than the two-dose schedule, even with a drop in vaccination coverage.

Interpretation: The three concerns are unlikely to have a substantial effect on the population-level impact of extended dose schedules. Hence, extended dose schedules will likely provide similar cervical cancer reductions as two-dose schedules, while reducing the number of doses required in the short-term, providing a more efficient use of scarce resources, and offering a 5-year time window to reassess the necessity of the second dose.

Funding: WHO, Canadian Institute of Health Research Foundation, Fonds de recherche du Québec–Santé, Digital Research Alliance of Canada, and Bill & Melinda Gates Foundation.

[International Journal of Infectious Diseases, February 2023]

Objectives: With the uptake of COVID-19 vaccines, there is a need for population-based studies to assess risk factors for COVID-19-related hospitalization after vaccination and how they differ from unvaccinated individuals.

Methods: We used data from the British Columbia COVID-19 Cohort, a population-based cohort that includes all individuals (aged ≥18 years) who tested positive for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction from January 1, 2021 (after the start of vaccination program) to December 31, 2021. We used multivariable logistic regression models to assess COVID-19-related hospitalization risk by vaccination status and age group among confirmed COVID-19 cases.

Results: Of the 162,509 COVID-19 cases included in the analysis, 8,546 (5.3%) required hospitalization. Among vaccinated individuals, an increased odds of hospitalization with increasing age was observed for older age groups, namely those aged 50-59 years (odds ratio [OR] = 2.95, 95% confidence interval [CI]: 2.01-4.33), 60-69 years (OR = 4.82, 95% CI: 3.29, 7.07), 70-79 years (OR = 11.92, 95% CI: 8.02, 17.71), and ≥80 years (OR = 24.25, 95% CI: 16.02, 36.71). However, among unvaccinated individuals, there was a graded increase in odds of hospitalization with increasing age, starting at age group 30-39 years (OR = 2.14, 95% CI: 1.90, 2.41) to ≥80 years (OR = 41.95, 95% CI: 35.43, 49.67). Also, comparing all the age groups to the youngest, the observed magnitude of association was much higher among unvaccinated individuals than vaccinated ones.

Conclusion: Alongside a number of comorbidities, our findings showed a strong association between age and COVID-19-related hospitalization, regardless of vaccination status. However, age-related hospitalization risk was reduced two-fold by vaccination, highlighting the need for vaccination in reducing the risk of severe disease and subsequent COVID-19-related hospitalization across all population groups.

[CMAJ, 21 November 2022]

Background: Postmarketing evaluations have linked myocarditis to SARS-CoV-2 mRNA vaccines. We sought to estimate the incidence of myocarditis after mRNA vaccination against SARS-CoV-2, and to compare the incidence with expected rates based on historical background rates in British Columbia.

Methods: We conducted an observational study using population health administrative data from the BC COVID-19 Cohort from Dec. 15, 2020, to Mar. 10, 2022. The primary exposure was any dose of an mRNA vaccine against SARS-CoV-2. The primary outcome was incidence of hospital admission or emergency department visit for myocarditis or myopericarditis within 7 and 21 days postvaccination, calculated as myocarditis rates per 100 000 mRNA vaccine doses, expected rates of myocarditis cases and observedto-expected ratios. We stratified analyses by age, sex, vaccine type and dose number.

Results: We observed 99 incident cases of myocarditis within 7 days (0.97 cases per 100 000 vaccine doses; observed v. expected ratio 14.81, 95% confidence interval [CI] 10.83–16.55) and 141 cases within 21 days (1.37 cases per 100 000 vaccine doses; observed v. expected ratio 7.03, 95% CI 5.92–8.29) postvaccination. Cases of myocarditis per 100 000 vaccine doses were higher for people aged 12–17 years (2.64, 95% CI 1.54–4.22) and 18–29 years (2.63, 95% CI 1.94–3.50) than for older age groups, for males compared with females (1.64, 95% CI 1.30–2.04 v. 0.35, 95% CI 0.21–0.55), for those receiving a second dose compared with a third dose (1.90, 95% CI 1.50–2.39 v. 0.76, 95% CI 0.45–1.30) and for those who received the mRNA-1273 (Moderna) vaccine compared with the BNT162b2 (Pfizer-BioNTech) vaccine (1.44, 95% CI 1.06–1.91 v. 0.74, 95% CI 0.56–0.98). The highest observed-to-expected ratio was seen after the second dose among males aged 18–29 years who received the mRNA-1273 vaccine (148.32, 95% CI 95.03–220.69).

Interpretation: Although absolute rates of myocarditis were low, vaccine type, age and sex are important factors to consider when strategizing vaccine administration to reduce the risk of postvaccination myocarditis. Our findings support the preferential use of the BNT162b2 vaccine over the mRNA-1273 vaccine for people aged 18–29 years.

As of September 2022, more than 32 million people in Canada, including around 4.5 million in British Columbia, have received a vaccine to prevent SARS-CoV-2 infection.1 With any novel vaccine, safety and effectiveness are important to public health and may determine the success of achieving the targeted immunization coverage. According to a recent systematic review, the overall rate of SARS-CoV-2 vaccination acceptance ranges from 53.6% to 84.4% in the United States.2 One of the key reasons for vaccine hesitancy is the fear of adverse effects.3,4

As large populations are vaccinated, certain uncommon events may be observed that were not detected during the premarketing clinical trials, whether or not these events are related to the vaccine. The same is the case with SARS-CoV-2 vaccination. The prelicensure study data did not suggest any risk of postvaccination myocarditis. However, postmarketing studies have suggested an association between mRNA SARS-CoV-2 vaccines (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]) and myocarditis, among other adverse events after immunization, which has raised concern regarding the safety of mRNA vaccines, specifically among younger populations.5–7 Most evidence comes from case reports and case series. Earlier data have suggested higher rates of myocarditis among young adults after the mRNA-1273 compared with the BNT162b2 vaccine. Limited data are available on the rate of myocarditis after the third dose, which is relevant as further boosters are planned. Given the important economic and health consequences of COVID-19, it is vital to further evaluate the likelihood of this signal.

One of the pharmacoepidemiologic methods that refine a previously detected signal is an observed-to-expected analysis, which compares the number of cases observed or reported to a calculated number of cases expected under the null hypothesis of no association between the intervention and the disease.8 Thus, the primary objective of this study was to determine the incidence of patients who visited the emergency department or were admitted to the hospital with myocarditis after mRNA SARS-CoV-2 vaccination, and to compare these observed results to expected numbers based on historical rates before the rollout of SARS-CoV-2 vaccination.

[CMAJ OPEN, 6 December 2022]

Background: SARS-CoV-2 transmission has an impact on education. In this study, we assessed the performance of rapid antigen detection tests (RADTs) versus polymerase chain reaction (PCR) for the diagnosis of SARS-CoV-2 infection in school settings, and RADT use for monitoring exposed contacts.

Methods: In this real-world, prospective observational cohort study, high-school students and staff were recruited from 2 high schools in Montréal, Canada, and followed from Jan. 25 to June 10, 2021. Twenty-five percent of asymptomatic participants were tested weekly by RADT (nasal) and PCR (gargle). Class contacts of cases were tested. Symptomatic participants were tested by RADT (nasal) and PCR (nasal and gargle). The number of cases and outbreaks were compared with those of other high schools in the same area.

Results: Overall, 2099 students and 286 school staff members consented to participate. The overall specificity of RADTs varied from 99.8% to 100%, with a lower sensitivity, varying from 28.6% in asymptomatic to 83.3% in symptomatic participants. Secondary cases were identified in 10 of 35 classes. Returning students to school after a 7-day quarantine, with a negative PCR result on days 6–7 after exposure, did not lead to subsequent outbreaks. Of cases for whom the source was known, 37 of 51 (72.5%) were secondary to household transmission, 13 (25.5%) to intraschool transmission, and 1 to community contacts between students in the same school.

Interpretation: Rapid antigen detection tests did not perform well compared with PCR in asymptomatic individuals. Reinforcing policies for symptom screening when entering schools and testing symptomatic individuals with RADTs on the spot may avoid subsequent substantial exposures in class. Preprint: medRxiv — doi.org/10.1101/2021.10.13.21264960

Timely diagnosis of infection enables outbreak control through rapid isolation of index cases and subsequent contact tracing.1,2 Diagnosis of SARS-CoV-2 infection is predominantly based on polymerase chain reaction (PCR), which has a turnaround time of 24–48 hours. Rapid antigen detection tests (RADTs) are inexpensive and can be used at the point of care. They usually have high specificity and moderate sensitivity compared with PCR.3–6 Given their rapid turnaround time, RADTs allow for efficient triage and management of exposed individuals.7 The potential use of RADTs is especially relevant in schools, where outbreaks of SARS-CoV-2 infection can interrupt in-person teaching and negatively affect learning.8–11

Rapid antigen detection tests perform best in the early stages of infection, when viral load is generally high.12–15 Reported RADT sensitivity ranges from 28.9% to 98.3%, with improved sensitivity in samples with high viral loads and in symptomatic individuals.16,17 The usual limits of detection for PCR is 600–1000 viral RNA copies/mL, whereas RADTs usually have limits of detection 2–3 logs higher (105 to 106).18 Many studies have indicated the importance of high viral load dynamics with infectiousness. 19,20 For each unit increase in cycle threshold (Ct) value, the odds of recovering infectious virus decreased by 0.67, being under 10% when Ct values were greater than 35. Cycle threshold values of 17 to 32 corresponded to 105 and 101 SARS-CoV-2 RNA copies/μL, respectively.21

We aimed to determine the performance characteristics of RADTs for SARS-CoV-2 compared with PCR in high-school students and staff, and to determine whether serial testing of COVID-19 contacts would allow for safe faster return to school.

[International Journal of Infectious Diseases, February 2023]

Objectives: We estimated the effectiveness of COVID-19 vaccines against laboratory-confirmed SARS-CoV-2 infection among people living with HIV (PLWH) and compared the estimates with a matched HIV-negative cohort.

Methods: We used the British Columbia COVID-19 Cohort, a population-based data platform, which integrates COVID-19 data on SARS-CoV-2 tests, laboratory-confirmed cases, and immunizations with provincial health services data. The vaccine effectiveness (VE) was estimated with a test-negative design using the multivariable logistic regression.

Results: The adjusted VE against SARS-CoV-2 infection was 71.1% (39.7, 86.1%) 7-59 days after two doses, rising to 89.3% (72.2, 95.9%) between 60 and 89 days. VE was preserved 4-6 months after the receipt of two doses, after which noticeable waning was observed (51.3% [4.8, 75.0%]). In the matched HIV-negative cohort (n = 375,043), VE peaked at 91.4% (90.9, 91.8%) 7-59 days after two doses and was sustained for up to 4 months, after which evidence of waning was observed, dropping to 84.2% (83.4, 85.0%) between 4 and 6 months.

Conclusion: The receipt of two COVID-19 vaccine doses was effective against SARS-CoV-2 infection among PLWH pre-Omicron. VE estimates appeared to peak later in PLWH than in the matched HIV-negative cohort and the degree of waning was relatively quicker in PLWH; however, peak estimates were comparable in both populations.

[Clinical Infectious Diseases, December 2022]

Background: The Canadian coronavirus disease 2019 (COVID-19) immunization strategy deferred second doses and allowed mixed schedules. We compared 2-dose vaccine effectiveness (VE) by vaccine type (mRNA and/or ChAdOx1), interval between doses, and time since second dose in 2 of Canada’s larger provinces.

Methods: Two-dose VE against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or hospitalization among adults ≥18 years, including due to Alpha, Gamma, and Delta variants of concern (VOCs), was assessed ≥14 days postvaccination by test-negative design studies separately conducted in British Columbia and Quebec, Canada, between 30 May and 27 November (epi-weeks 22–47) 2021.

Results: In both provinces, all homologous or heterologous mRNA and/or ChAdOx1 2-dose schedules were associated with ≥90% reduction in SARS-CoV-2 hospitalization risk for ≥7 months. With slight decline from a peak of >90%, VE against infection was ≥80% for ≥6 months following homologous mRNA vaccination, lower by ∼10% when both doses were ChAdOx1 but comparably high following heterologous ChAdOx1 + mRNA receipt. Findings were similar by age group, sex, and VOC. VE was significantly higher with longer 7–8-week versus manufacturer-specified 3–4-week intervals between mRNA doses.

Conclusions: Two doses of any mRNA and/or ChAdOx1 combination gave substantial and sustained protection against SARS-CoV-2 hospitalization, spanning Delta-dominant circulation. ChAdOx1 VE against infection was improved by heterologous mRNA series completion. A 7–8-week interval between first and second doses improved mRNA VE and may be the optimal schedule outside periods of intense epidemic surge. Findings support interchangeability and extended intervals between SARS-CoV-2 vaccine doses, with potential global implications for low-coverage areas and, going forward, for children.

[Annals of Internal Medicine, December 2022]

Background: It is uncertain if medical masks offer similar protection against COVID-19 compared with N95 respirators.

Objective: To determine whether medical masks are noninferior to N95 respirators to prevent COVID-19 in health care workers providing routine care.

Design: Multicenter, randomized, noninferiority trial. (ClinicalTrials.gov: NCT04296643).

Setting: 29 health care facilities in Canada, Israel, Pakistan, and Egypt from 4 May 2020 to 29 March 2022.

Participants: 1009 health care workers who provided direct care to patients with suspected or confirmed COVID-19.

Intervention: Use of medical masks versus fit-tested N95 respirators for 10 weeks, plus universal masking, which was the policy implemented at each site.

Measurements: The primary outcome was confirmed COVID-19 on reverse transcriptase polymerase chain reaction (RT-PCR) test.

Results: In the intention-to-treat analysis, RT-PCR–confirmed COVID-19 occurred in 52 of 497 (10.46%) participants in the medical mask group versus 47 of 507 (9.27%) in the N95 respirator group (hazard ratio [HR], 1.14 [95% CI, 0.77 to 1.69]). An unplanned subgroup analysis by country found that in the medical mask group versus the N95 respirator group RT-PCR–confirmed COVID-19 occurred in 8 of 131 (6.11%) versus 3 of 135 (2.22%) in Canada (HR, 2.83 [CI, 0.75 to 10.72]), 6 of 17 (35.29%) versus 4 of 17 (23.53%) in Israel (HR, 1.54 [CI, 0.43 to 5.49]), 3 of 92 (3.26%) versus 2 of 94 (2.13%) in Pakistan (HR, 1.50 [CI, 0.25 to 8.98]), and 35 of 257 (13.62%) versus 38 of 261 (14.56%) in Egypt (HR, 0.95 [CI, 0.60 to 1.50]). There were 47 (10.8%) adverse events related to the intervention reported in the medical mask group and 59 (13.6%) in the N95 respirator group.

Limitation: Potential acquisition of SARS-CoV-2 through household and community exposure, heterogeneity between countries, uncertainty in the estimates of effect, differences in self-reported adherence, differences in baseline antibodies, and between-country differences in circulating variants and vaccination.

Conclusion: Among health care workers who provided routine care to patients with COVID-19, the overall estimates rule out a doubling in hazard of RT-PCR–confirmed COVID-19 for medical masks when compared with HRs of RT-PCR–confirmed COVID-19 for N95 respirators. The subgroup results varied by country, and the overall estimates may not be applicable to individual countries because of treatment effect heterogeneity.

[International Journal of Infectious Diseases, 28 November 2022]

Objectives: We examined the incremental protection and durability of infection-acquired immunity against Omicron infection in individuals with hybrid immunity in Ontario, Canada.

Methods: We followed up 6 million individuals with at least one multiplex reverse transcriptase–polymerase chain reaction test before November 21, 2021, until an Omicron infection. Protection via infection-acquired immunity was assessed by comparing Omicron infection risk between previously infected individuals and those without documented infection under different vaccination scenarios and stratified by time since the last infection or vaccination.

Results: A previous infection was associated with 68% (95% CI 61-73) and 43% (95% CI 27-56) increased protection against Omicron infection in individuals with two and three doses, respectively. Among individuals with two-dose vaccination, the incremental protection of infection-induced immunity decreased from 79% (95% CI 75-81) within 3 months after vaccination or infection to 27% (95% CI 14-37) at 9-11 months. In individuals with three-dose vaccination, it decreased from 57% (95% CI 50-63) within 3 months to 37% (95% CI 19-51) at 3-5 months after vaccination or infection.

Conclusion: Previous SARS-CovV-2 infections provide added cross-variant immunity to vaccination. Given the limited durability of infection-acquired protection in individuals with hybrid immunity, its influence on shield-effects at the population level and reinfection risks at the individual level may be limited.

[Experimental Biology and Medicine, 25 November 2022]

This editorial article aims to highlight advances in artificial intelligence (AI) technologies in five areas: Collaborative AI, Multimodal AI, Human-Centered AI, Equitable AI, and Ethical and Value-based AI in order to cope with future complex socioeconomic and public health issues.

[Journal of Theoretical Biology, 20 December 2022]

COVID-19 remains a major public health concern, with large resurgences even where there has been widespread uptake of vaccines. Waning immunity and the emergence of new variants will shape the long-term burden and dynamics of COVID-19. We explore the transition to the endemic state, and the endemic incidence in British Columbia (BC), Canada and South Africa (SA), to compare low and high vaccination coverage settings with differing public health policies, using a combination of modelling approaches. We compare reopening (relaxation of public health measures) gradually and rapidly as well as at different vaccination levels. We examine how the eventual endemic state depends on the duration of immunity, the rate of importations, the efficacy of vaccines and the transmissibility. These depend on the evolution of the virus, which continues to undergo selection. Slower reopening leads to a lower peak level of incidence and fewer overall infections in the wave following reopening: as much as a 60% lower peak and a 10% lower total in some illustrative simulations; under realistic parameters, reopening when 70% of the population is vaccinated leads to a large resurgence in cases. The long-term endemic behaviour may stabilize as late as January 2023, with further waves of high incidence occurring depending on the transmissibility of the prevalent variant, duration of immunity, and antigenic drift. We find that long term endemic levels are not necessarily lower than current pandemic levels: in a population of 100,000 with representative parameter settings (Reproduction number 5, 1-year duration of immunity, vaccine efficacy at 80% and importations at 3 cases per 100K per day) there are over 100 daily incident cases in the model. Predicted prevalence at endemicity has increased more than twofold after the emergence and spread of Omicron. The consequent burden on health care systems depends on the severity of infection in immunized or previously infected individuals.

[The Journal of Immunology, 15 November 2022]

Chronic infection with human CMV may contribute to poor vaccine efficacy in older adults. We assessed the effects of CMV serostatus on Ab quantity and quality, as well as cellular memory recall responses, after two and three SARS-CoV-2 mRNA vaccine doses, in older adults in assisted living facilities. CMV serostatus did not affect anti-Spike and anti–receptor-binding domain IgG Ab levels, nor neutralization capacity against wild-type or β variants of SARS-CoV-2 several months after vaccination. CMV seropositivity altered T cell expression of senescence-associated markers and increased effector memory re-expressing CD45RA T cell numbers, as has been previously reported; however, this did not impact Spike-specific CD4+ T cell memory recall responses. CMV-seropositive individuals did not have a higher incidence of COVID-19, although prior infection influenced humoral immunity. Therefore, CMV seropositivity may alter T cell composition but does not impede the durability of humoral protection or cellular memory responses after SARS-CoV-2 mRNA vaccination in older adults.

[PLoS Medicine, 10 November 2022]

Background: Our understanding of the global scale of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remains incomplete: Routine surveillance data underestimate infection and cannot infer on population immunity; there is a predominance of asymptomatic infections, and uneven access to diagnostics. We meta-analyzed SARS-CoV-2 seroprevalence studies, standardized to those described in the World Health Organization’s Unity protocol (WHO Unity) for general population seroepidemiological studies, to estimate the extent of population infection and seropositivity to the virus 2 years into the pandemic.

Methods and findings: We conducted a systematic review and meta-analysis, searching MEDLINE, Embase, Web of Science, preprints, and grey literature for SARS-CoV-2 seroprevalence published between January 1, 2020 and May 20, 2022. The review protocol is registered with PROSPERO (CRD42020183634). We included general population cross-sectional and cohort studies meeting an assay quality threshold (90% sensitivity, 97% specificity; exceptions for humanitarian settings). We excluded studies with an unclear or closed population sample frame. Eligible studies—those aligned with the WHO Unity protocol—were extracted and critically appraised in duplicate, with risk of bias evaluated using a modified Joanna Briggs Institute checklist. We meta-analyzed seroprevalence by country and month, pooling to estimate regional and global seroprevalence over time; compared seroprevalence from infection to confirmed cases to estimate underascertainment; meta-analyzed differences in seroprevalence between demographic subgroups such as age and sex; and identified national factors associated with seroprevalence using meta-regression. We identified 513 full texts reporting 965 distinct seroprevalence studies (41% low- and middle-income countries [LMICs]) sampling 5,346,069 participants between January 2020 and April 2022, including 459 low/moderate risk of bias studies with national/subnational scope in further analysis. By September 2021, global SARS-CoV-2 seroprevalence from infection or vaccination was 59.2%, 95% CI [56.1% to 62.2%]. Overall seroprevalence rose steeply in 2021 due to infection in some regions (e.g., 26.6% [24.6 to 28.8] to 86.7% [84.6% to 88.5%] in Africa in December 2021) and vaccination and infection in others (e.g., 9.6% [8.3% to 11.0%] in June 2020 to 95.9% [92.6% to 97.8%] in December 2021, in European high-income countries [HICs]). After the emergence of Omicron in March 2022, infection-induced seroprevalence rose to 47.9% [41.0% to 54.9%] in Europe HIC and 33.7% [31.6% to 36.0%] in Americas HIC. In 2021 Quarter Three (July to September), median seroprevalence to cumulative incidence ratios ranged from around 2:1 in the Americas and Europe HICs to over 100:1 in Africa (LMICs). Children 0 to 9 years and adults 60+ were at lower risk of seropositivity than adults 20 to 29 (p < 0.001 and p = 0.005, respectively). In a multivariable model using prevaccination data, stringent public health and social measures were associated with lower seroprevalence (p = 0.02). The main limitations of our methodology include that some estimates were driven by certain countries or populations being overrepresented.

Conclusions: In this study, we observed that global seroprevalence has risen considerably over time and with regional variation; however, over one-third of the global population are seronegative to the SARS-CoV-2 virus. Our estimates of infections based on seroprevalence far exceed reported Coronavirus Disease 2019 (COVID-19) cases. Quality and standardized seroprevalence studies are essential to inform COVID-19 response, particularly in resource-limited regions.

[Frontiers in Public Health, 9 November 2022]

Background: Correctional workers are at increased risk of SARS-CoV-2 infection. We examined the seroprevalence of SARS-CoV-2, determined the effects of carceral and occupational exposures on seropositivity, and explored predictors of COVID-19 vaccine uptake among correctional workers in Quebec, Canada.

Methods: We conducted a cross-sectional seroprevalence study in three provincial prisons. The primary and secondary outcomes were SARS-CoV-2 antibody seropositivity (Roche Elecsys® serology test) and self-reported COVID-19 vaccination status (“fully vaccinated” defined as two doses or prior infection plus one dose), respectively. Poisson regression models with robust standard error were used to examine the effect of occupational variables with SARS-CoV-2 seropositivity and predictors of COVID-19 vaccine uptake. Estimates are presented as crude and adjusted prevalence ratios (aPR) with 95% confidence intervals (95% CI).

Results: From 14 July to 15 November 2021, 105/600 (18%) correctional workers tested positive across three prisons (range 11–21%); 76% were fully vaccinated. Seropositivity was affected by prison occupation (aPR 1.59, 95% CI 1.11–2.27 for correctional officers vs. all other occupations) and low perceived concern of SARS-CoV-2 acquisition (aPR 1.62, 95% CI 1.11–2.38 for not/hardly worried vs. somewhat/extremely worried). Predictors of being fully vaccinated included race/ethnicity (aPR 0.86, 95% CI 0.76–0.99 for visible minority vs. White), presence of comorbidities (aPR 1.14, 95% CI 1.02–1.28 for > 2 vs. none), and prison occupation (aPR 0.82, 95% CI 0.73–0.92 for correctional officers vs. all other occupations).

Conclusions: Correctional officers were most likely to have acquired SARS-CoV-2, but least likely to be vaccinated, underscoring the importance of addressing both occupational risks and COVID-19 vaccine hesitancy to mitigate future outbreaks.

[eLife, 8 November 2022]

Public health emergencies like SARS, MERS, and COVID-19 have prioritized surveillance of zoonotic coronaviruses, resulting in extensive genomic characterization of coronavirus diversity in bats. Sequencing viral genomes directly from animal specimens remains a laboratory challenge, however, and most bat coronaviruses have been characterized solely by PCR amplification of small regions from the best-conserved gene. This has resulted in limited phylogenetic resolution and left viral genetic factors relevant to threat assessment undescribed. In this study, we evaluated whether a technique called hybridization probe capture can achieve more extensive genome recovery from surveillance specimens. Using a custom panel of 20,000 probes, we captured and sequenced coronavirus genomic material in 21 swab specimens collected from bats in the Democratic Republic of the Congo. For 15 of these specimens, probe capture recovered more genome sequence than had been previously generated with standard amplicon sequencing protocols, providing a median 6.1-fold improvement (ranging up to 69.1-fold). Probe capture data also identified five novel alpha- and betacoronaviruses in these specimens, and their full genomes were recovered with additional deep sequencing. Based on these experiences, we discuss how probe capture could be effectively operationalized alongside other sequencing technologies for high-throughput, genomics-based discovery and surveillance of bat coronaviruses.

[Journal of the American College of Cardiology, 7 November 2022]

Background: Postmarketing evaluations have linked myocarditis to COVID-19 mRNA vaccines. However, few population-based analyses have directly compared the safety of the 2 mRNA COVID-19 vaccines.

Objectives: This study aimed to compare the risk of myocarditis, pericarditis, and myopericarditis between BNT162b2 and mRNA-1273.

Methods: We used data from the British Columbia COVID-19 Cohort (BCC19C), a population-based cohort study. The exposure was the second dose of an mRNA vaccine. The outcome was diagnosis of myocarditis, pericarditis, or myopericarditis during a hospitalization or an emergency department visit within 21 days of the second vaccination dose. We performed multivariable logistic regression to assess the association between vaccine product and the outcomes of interest.

Results: The rates of myocarditis and pericarditis per million second doses were higher for mRNA-1273 (n = 31, rate 35.6; 95% CI: 24.1-50.5; and n = 20, rate 22.9; 95% CI: 14.0-35.4, respectively) than BNT162b2 (n = 28, rate 12.6; 95% CI: 8.4-18.2 and n = 21, rate 9.4; 95% CI: 5.8-14.4, respectively). mRNA-1273 vs BNT162b2 had significantly higher odds of myocarditis (adjusted OR [aOR]: 2.78; 95% CI: 1.67-4.62), pericarditis (aOR: 2.42; 95% CI: 1.31-4.46) and myopericarditis (aOR: 2.63; 95% CI: 1.76-3.93). The association between mRNA-1273 and myocarditis was stronger for men (aOR: 3.21; 95% CI: 1.77-5.83) and younger age group (18-39 years; aOR: 5.09; 95% CI: 2.68-9.66).

Conclusions: Myocarditis/pericarditis following mRNA COVID-19 vaccines is rare, but we observed a 2- to 3-fold higher odds among individuals who received mRNA-1273 vs BNT162b2. The rate of myocarditis following mRNA-1273 receipt is highest among younger men (age 18-39 years) and does not seem to be present at older ages. Our findings may have policy implications regarding the choice of vaccine offered.

[Viruses, 31 October 2022]

Background: Investigating antibody titers in individuals who have been both naturally infected with SARS-CoV-2 and vaccinated can provide insight into antibody dynamics and correlates of protection over time.

Methods: Human coronavirus (HCoV) IgG antibodies were measured longitudinally in a prospective cohort of qPCR-confirmed, COVID-19 recovered individuals (k = 57) in British Columbia pre- and post-vaccination. SARS-CoV-2 and endemic HCoV antibodies were measured in serum collected between Nov. 2020 and Sept. 2021 (n = 341). Primary analysis used a linear mixed-effects model to understand the effect of single dose vaccination on antibody concentrations adjusting for biological sex, age, time from infection and vaccination. Secondary analysis investigated the cumulative incidence of high SARS-CoV-2 anti-spike IgG seroreactivity equal to or greater than 5.5 log10 AU/mL up to 105 days post-vaccination. No re-infections were detected in vaccinated participants, post-vaccination by qPCR performed on self-collected nasopharyngeal specimens.

Results: Bivariate analysis (complete data for 42 participants, 270 samples over 472 days) found SARS-CoV-2 spike and RBD antibodies increased 14–56 days post-vaccination (p < 0.001) and vaccination prevented waning (regression coefficient, B = 1.66 [95%CI: 1.45–3.46]); while decline of nucleocapsid antibodies over time was observed (regression coefficient, B = −0.24 [95%CI: −1.2-(−0.12)]). A positive association was found between COVID-19 vaccination and endemic human β-coronavirus IgG titer 14–56 days post vaccination (OC43, p = 0.02 & HKU1, p = 0.02). On average, SARS-CoV-2 anti-spike IgG concentration increased in participants who received one vaccine dose by 2.06 log10 AU/mL (95%CI: 1.45–3.46) adjusting for age, biological sex, and time since infection. Cumulative incidence of high SARS-CoV-2 spike antibodies (>5.5 log10 AU/mL) was 83% greater in vaccinated compared to unvaccinated individuals.

Conclusions: Our study confirms that vaccination post-SARS-CoV-2 infection provides multiple benefits, such as increasing anti-spike IgG titers and preventing decay up to 85 days post-vaccination.

[Oikos, 25 October 2022]

Despite considerable study of population cycles, the striking variability of cycle periods in many cyclic populations has received relatively little attention. Mathematical models of cyclic population dynamics have historically exhibited much greater regularity in cycle periods than many real populations, even when accounting for environmental stochasticity. We contend, however, that the recent focus on understanding the impact of long, transient but recurrent epochs within population oscillations points the way to a previously unrecognized means by which environmental stochasticity can create cycle period variation. Specifically, consumer–resource cycles that bring the populations near a saddle point (a combination of population sizes toward which the populations tend, before eventually transitioning to substantially different levels) may be subject to a slow passage effect that has been dubbed a ‘saddle crawlby'. In this study, we illustrate how stochasticity that generates variability in how close predator and prey populations come to saddles can result in substantial variability in the durations of crawlbys and, as a result, in the periods of population cycles. Our work suggests a new mechanistic hypothesis to explain an important factor in the irregular timing of population cycles and provides a basis for understanding when environmental stochasticity is, and is not, expected to generate cyclic dynamics with variability across periods.

[eLife, 30 November 2022]

The role of schools in the spread of SARS-CoV-2 is controversial, with some claiming they are an important driver of the pandemic and others arguing that transmission in schools is negligible. School cluster reports that have been collected in various jurisdictions are a source of data about transmission in schools. These reports consist of the name of a school, a date, and the number of students known to be infected. We provide a simple model for the frequency and size of clusters in this data, based on random arrivals of index cases at schools who then infect their classmates with a highly variable rate, fitting the overdispersion evident in the data. We fit our model to reports from four Canadian provinces, providing estimates of mean and dispersion for cluster size, as well as the distribution of the instantaneous transmission parameter β, whilst factoring in imperfect ascertainment. According to our model with parameters estimated from the data, in all four provinces (i) more than 65% of non-index cases occur in the 20% largest clusters, and (ii) reducing instantaneous transmission rate and the number of contacts a student has at any given time are effective in reducing the total number of cases, whereas strict bubbling (keeping contacts consistent over time) does not contribute much to reduce cluster sizes. We predict strict bubbling to be more valuable in scenarios with substantially higher transmission rates.

[Epidemics, 26 October 2022]

Seroprevalence studies have been used throughout the COVID-19 pandemic to monitor infection and immunity. These studies are often reported in peer-reviewed journals, but the academic writing and publishing process can delay reporting and thereby public health action. Seroprevalence estimates have been reported faster in preprints and media, but with concerns about data quality. We aimed to (i) describe the timeliness of SARS-CoV-2 serosurveillance reporting by publication venue and study characteristics and (ii) identify relationships between timeliness, data validity, and representativeness to guide recommendations for serosurveillance efforts. We included seroprevalence studies published between January 1, 2020 and December 31, 2021 from the ongoing SeroTracker living systematic review. For each study, we calculated timeliness as the time elapsed between the end of sampling and the first public report. We evaluated data validity based on serological test performance and correction for sampling error, and representativeness based on the use of a representative sample frame and adequate sample coverage. We examined how timeliness varied with study characteristics, representativeness, and data validity using univariate and multivariate Cox regression. We analyzed 1844 studies. Median time to publication was 154 days (IQR 64–255), varying by publication venue (journal articles: 212 days, preprints: 101 days, institutional reports: 18 days, and media: 12 days). Multivariate analysis confirmed the relationship between timeliness and publication venue and showed that general population studies were published faster than special population or health care worker studies; there was no relationship between timeliness and study geographic scope, geographic region, representativeness, or serological test performance. Seroprevalence studies in peer-reviewed articles and preprints are published slowly, highlighting the limitations of using the academic literature to report seroprevalence during a health crisis. More timely reporting of seroprevalence estimates can improve their usefulness for surveillance, enabling more effective responses during health emergencies.

[JAMA Network Open, 13 March 2023]

Importance: People experiencing homelessness are at high risk of SARS-CoV-2 infection. Incident infection rates have yet to be established in these communities and are needed to inform infection prevention guidance and related interventions.

Objective: To quantify the SARS-CoV-2 incident infection rate among people experiencing homelessness in Toronto, Canada, in 2021 and 2022 and to assess factors associated with incident infection.

Design, Setting, and Participants: This prospective cohort study was conducted among individuals aged 16 years and older who were randomly selected between June and September 2021 from 61 homeless shelters, temporary distancing hotels, and encampments in Toronto, Canada.

Exposures: Self-reported housing characteristics, such as number sharing living space.

Main Outcomes and Measures: Prevalence of prior SARS-CoV-2 infection in summer 2021, defined as self-reported or polymerase chain reaction (PCR)– or serology-confirmed evidence of infection at or before the baseline interview, and SARS-CoV-2 incident infection, defined as self-reported or PCR- or serology-confirmed infection among participants without history of infection at baseline. Factors associated with infection were assessed using modified Poisson regression with generalized estimating equations.

Results: The 736 participants (415 of whom did not have SARS-CoV-2 infection at baseline and were included in the primary analysis) had a mean (SD) age of 46.1 (14.6) years; 486 (66.0%) self-identified as male. Of these, 224 (30.4% [95% CI, 27.4%-34.0%]) had a history of SARS-CoV-2 infection by summer 2021. Of the remaining 415 participants with follow-up, 124 experienced infection within 6 months, representing an incident infection rate of 29.9% (95% CI, 25.7%-34.4%), or 5.8% (95% CI, 4.8%-6.8%) per person-month. Report after onset of the SARS-CoV-2 Omicron variant was associated with incident infection, with an adjusted rate ratio (aRR) of 6.28 (95% CI, 3.94-9.99). Other factors associated with incident infection included recent immigration to Canada (aRR, 2.74 [95% CI, 1.64-4.58]) and alcohol consumption over the past interval (aRR, 1.67 [95% CI, 1.12-2.48]). Self-reported housing characteristics were not significantly associated with incident infection.

Conclusions and Relevance: In this longitudinal study of people experiencing homelessness in Toronto, SARS-CoV-2 incident infection rates were high in 2021 and 2022, particularly once the Omicron variant became dominant in the region. Increased focus on homelessness prevention is needed to more effectively and equitably protect these communities.

[BMC Genomics, 19 October 2022]

Background: The COVID-19 pandemic remains a global public health concern. Advances in sequencing technologies has allowed for high numbers of SARS-CoV-2 whole genome sequence (WGS) data and rapid sharing of sequences through global repositories to enable almost real-time genomic analysis of the pathogen. WGS data has been used previously to group genetically similar viral pathogens to reveal evidence of transmission, including methods that identify distinct clusters on a phylogenetic tree. Identifying clusters of linked cases can aid in the regional surveillance and management of the disease. In this study, we present a novel method for producing stable genomic clusters of SARS-CoV-2 cases, cov2clusters, and compare the accuracy and stability of our approach to previous methods used for phylogenetic clustering using real-world SARS-CoV-2 sequence data obtained from British Columbia, Canada.

Results: We found that cov2clusters produced more stable clusters than previously used phylogenetic clustering methods when adding sequence data through time, mimicking an increase in sequence data through the pandemic. Our method also showed high accuracy when predicting epidemiologically informed clusters from sequence data.

Conclusions: Our new approach allows for the identification of stable clusters of SARS-CoV-2 from WGS data. Producing high-resolution SARS-CoV-2 clusters from sequence data alone can a challenge and, where possible, both genomic and epidemiological data should be used in combination.

[AIDS, 1 December 2022]

Objective: People with HIV were underrepresented in coronavirus disease 2019 (COVID-19) vaccine clinical trials. We estimated vaccine effectiveness (VE) against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection for the BNT162b2, mRNA-1273, and ChAdOx1 vaccines among a population-based cohort of people with HIV in Ontario, Canada.

Design: Test-negative design

Methods: We identified people with HIV aged ≥19 years who were tested for SARS-CoV-2 by RT-PCR between December 14, 2020 (first availability of COVID-19 vaccines) and November 21, 2021 (pre-Omicron circulation). Outcomes included any infection, symptomatic infection, and COVID-19-related hospitalization/death. We compared the odds of vaccination between test-positive cases and test-negative controls using multivariable logistic regression with adjustment for age, sex, region, calendar time, SARS-CoV-2 test histories, influenza vaccination, comorbidities, and neighborhood-level socio-economic status. VE was derived as (1 – adjusted odds ratio) × 100%.

Results: Among 21 023 adults living with HIV, there were 801 (8.3%) test-positive cases and 8,879 (91.7%) test-negative controls. 20.1% cases and 47.8% of controls received ≥1 COVID-19 vaccine dose; among two-dose recipients, 93.4% received ≥1 mRNA dose. Two-dose VE ≥7 days before specimen collection was 82% (95% confidence interval [CI] = 74–87%) against any infection, 94% (95% CI = 82–98%) against symptomatic infection, and 97% (95% CI = 85–100%) against hospitalization/death. Against any infection, VE declined from 86% (95% CI = 77–92%) within 7–59 days after the second dose to 66% (95% CI = −15–90%) after ≥180 days; we did not observe evidence of waning protection for other outcomes.

Conclusion: Two doses of COVID-19 vaccine offered substantial protection against symptomatic illness and hospitalization/death in people with HIV prior to the emergence of the Omicron variant. Our findings do not support a broad conclusion that COVID-19 VE is lower among people with HIV in populations that, for the most part, are attending HIV care, taking antiretroviral medication, and are virally suppressed.

[JAMA Network Open, 14 October 2022]

Importance: The Omicron variant is phylogenetically and antigenically distinct from earlier SARS-CoV-2 variants and the original vaccine strain. Protection conferred by prior SARS-CoV-2 infection against Omicron reinfection, with and without vaccination, requires quantification.

Objective: To estimate the protection against Omicron reinfection and hospitalization conferred by prior heterologous non-Omicron SARS-CoV-2 infection and/or up to 3 doses of an ancestral, Wuhan-like messenger RNA (mRNA) vaccine.

Design, Setting, and Participants: This test-negative, population-based case-control study was conducted between December 26, 2021, and March 12, 2022, and included community-dwelling individuals aged 12 years or older who were tested for SARS-CoV-2 infection in the province of Quebec, Canada.

Exposures: Prior laboratory-confirmed SARS-CoV-2 infection with or without mRNA vaccination.

Main Outcomes and Measures: The main outcome was laboratory-confirmed SARS-CoV-2 reinfection and associated hospitalization, presumed to be associated with the Omicron variant according to genomic surveillance. The odds of prior infection with or without vaccination were compared for case participants with Omicron infection and associated hospitalizations vs test-negative control participants. Estimated protection was derived as 1 − the odds ratio, adjusted for age, sex, testing indication, and epidemiologic week. Analyses were stratified by severity and time since last non-Omicron infection or vaccine dose.

Results: This study included 696 439 individuals (224 007 case participants and 472 432 control participants); 62.2% and 63.9% were female and 87.4% and 75.5% were aged 18 to 69 years, respectively. Prior non-Omicron SARS-CoV-2 infection was detected for 9505 case participants (4.2%) and 29 712 control participants (6.3%). Among nonvaccinated individuals, prior non-Omicron infection was associated with a 44% reduction (95% CI, 38%-48%) in Omicron reinfection risk, which decreased from 66% (95% CI, 57%-73%) at 3 to 5 months to 35% (95% CI, 21%-47%) at 9 to 11 months postinfection and was below 30% thereafter. The more severe the prior infection, the greater the risk reduction. Estimated protection (95% CI) against Omicron infection was consistently significantly higher among vaccinated individuals with prior infection compared with vaccinated infection-naive individuals, with 65% (63%-67%) vs 20% (16%-24%) for 1 dose, 68% (67%-70%) vs 42% (41%-44%) for 2 doses, and 83% (81%-84%) vs 73% (72%-73%) for 3 doses. For individuals with prior infection, estimated protection (95% CI) against Omicron-associated hospitalization was 81% (66%-89%) and increased to 86% (77%-99%) with 1, 94% (91%-96%) with 2, and 97% (94%-99%) with 3 mRNA vaccine doses, without signs of waning.

Conclusions and Relevance: The findings of this study suggest that vaccination with 2 or 3 mRNA vaccine doses among individuals with prior heterologous SARS-CoV-2 infection provided the greatest protection against Omicron-associated hospitalization. In the context of program goals to prevent severe outcomes and preserve health care system capacity, a third mRNA vaccine dose may add limited protection in twice-vaccinated individuals with prior SARS-CoV-2 infection.

[The Lancet Respiratory Medicine, December 2022]

Background: The large number of patients worldwide infected with the SARS-CoV-2 virus has overwhelmed health-care systems globally. The Anti-Coronavirus Therapies (ACT) outpatient trial aimed to evaluate anti-inflammatory therapy with colchicine and antithrombotic therapy with aspirin for prevention of disease progression in community patients with COVID-19.

Methods: The ACT outpatient, open-label, 2 × 2 factorial, randomised, controlled trial, was done at 48 clinical sites in 11 countries. Patients in the community aged 30 years and older with symptomatic, laboratory confirmed COVID-19 who were within 7 days of diagnosis and at high risk of disease progression were randomly assigned (1:1) to receive colchicine 0·6 mg twice daily for 3 days and then 0·6 mg once daily for 25 days versus usual care, and in a second (1:1) randomisation to receive aspirin 100 mg once daily for 28 days versus usual care. Investigators and patients were not masked to treatment allocation. The primary outcome was assessed at 45 days in the intention-to-treat population; for the colchicine randomisation it was hospitalisation or death, and for the aspirin randomisation it was major thrombosis, hospitalisation, or death. The ACT outpatient trial is registered at ClinicalTrials.gov, NCT04324463 and is ongoing.

Findings: Between Aug 27, 2020, and Feb 10, 2022, 3917 patients were randomly assigned to colchicine or control and to aspirin or control; after excluding 36 patients due to administrative reasons 3881 individuals were included in the analysis (n=1939 colchicine vs n=1942 control; n=1945 aspirin vs 1936 control). Follow-up was more than 99% complete. Overall event rates were 5 (0·1%) of 3881 for major thrombosis, 123 (3·2%) of 3881 for hospitalisation, and 23 (0·6%) of 3881 for death; 66 (3·4%) of 1939 patients allocated to colchicine and 65 (3·3%) of 1942 patients allocated to control experienced hospitalisation or death (hazard ratio [HR] 1·02, 95% CI 0·72–1·43, p=0·93); and 59 (3·0%) of 1945 of patients allocated to aspirin and 73 (3·8%) of 1936 patients allocated to control experienced major thrombosis, hospitalisation, or death (HR 0·80, 95% CI 0·57–1·13, p=0·21). Results for the primary outcome were consistent in all prespecified subgroups, including according to baseline vaccination status, timing of randomisation in relation to onset of symptoms (post-hoc analysis), and timing of enrolment according to the phase of the pandemic (post-hoc analysis). There were more serious adverse events with colchicine than with control (34 patients [1·8%] of 1939 vs 27 [1·4%] of 1942) but none in either group that led to discontinuation of study interventions. There was no increase in serious adverse events with aspirin versus control (31 [1·6%] vs 31 [1·6%]) and none that led to discontinuation of study interventions.

Interpretation: The results provide no support for the use of colchicine or aspirin to prevent disease progression or death in outpatients with COVID-19.

[The Lancet Respiratory Medicine, December 2022]

Background: COVID-19 disease is accompanied by a dysregulated immune response and hypercoagulability. The Anti-Coronavirus Therapies (ACT) inpatient trial aimed to evaluate anti-inflammatory therapy with colchicine and antithrombotic therapy with the combination of rivaroxaban and aspirin for prevention of disease progression in patients hospitalised with COVID-19.

Methods: The ACT inpatient, open-label, 2 × 2 factorial, randomised, controlled trial was done at 62 clinical centres in 11 countries. Patients aged at least 18 years with symptomatic, laboratory confirmed COVID-19 who were within 72 h of hospitalisation or worsening clinically if already hospitalised were randomly assigned (1:1) to receive colchicine 1·2 mg followed by 0·6 mg 2 h later and then 0·6 mg twice daily for 28 days versus usual care; and in a second (1:1) randomisation, to the combination of rivaroxaban 2·5 mg twice daily plus aspirin 100 mg once daily for 28 days versus usual care. Investigators and patients were not masked to treatment allocation. The primary outcome, assessed at 45 days in the intention-to-treat population, for the colchicine randomisation was the composite of the need for high-flow oxygen, mechanical ventilation, or death; and for the rivaroxaban plus aspirin randomisation was the composite of major thrombosis (myocardial infarction, stroke, acute limb ischaemia, or pulmonary embolism), the need for high-flow oxygen, mechanical ventilation, or death. The trial is registered at www.clinicaltrials.gov, NCT04324463 and is ongoing.

Findings: Between Oct 2, 2020, and Feb 10, 2022, at 62 sites in 11 countries, 2749 patients were randomly assigned to colchicine or control and the combination of rivaroxaban and aspirin or to the control. 2611 patients were included in the analysis of colchicine (n=1304) versus control (n=1307); 2119 patients were included in the analysis of rivaroxaban and aspirin (n=1063) versus control (n=1056). Follow-up was more than 98% complete. Overall, 368 (28·2%) of 1304 patients allocated to colchicine and 356 (27·2%) of 1307 allocated to control had a primary outcome (hazard ratio [HR] 1·04, 95% CI 0·90–1·21, p=0·58); and 281 (26·4%) of 1063 patients allocated to the combination of rivaroxaban and aspirin and 300 (28·4%) of 1056 allocated to control had a primary outcome (HR 0·92, 95% CI 0·78–1·09, p=0·32). Results were consistent in subgroups defined by vaccination status, disease severity at baseline, and timing of randomisation in relation to onset of symptoms. There was no increase in the number of patients who had at least one serious adverse event for colchicine versus control groups (87 [6·7%] of 1304 vs 90 [6·9%] of 1307) or with rivaroxaban and aspirin versus control groups (85 [8·0%] vs 91 [8·6%]). Among patients assigned to colchicine, 8 (0·61%) had adverse events that led to discontinuation of study drug, mostly gastrointestinal in nature. 17 (1·6%) patients assigned to the combination of rivaroxaban and aspirin had bleeding compared with seven (0·66%) of those allocated to control (p=0·042); the number of serious bleeding events was two (0·19%) versus six (0·57%), respectively (p=0·18). No patients assigned to rivaroxaban and aspirin had serious adverse events that led to discontinuation of study drug.

Interpretation: Among patients hospitalised with COVID-19, neither colchicine nor the combination of rivaroxaban and aspirin prevent disease progression or death.

[JMIR Public Health and Surveillance, 4 October 2022]

Background: Disproportionate risks of COVID-19 in congregate care facilities including long-term care homes, retirement homes, and shelters both affect and are affected by SARS-CoV-2 infections among facility staff. In cities across Canada, there has been a consistent trend of geographic clustering of COVID-19 cases. However, there is limited information on how COVID-19 among facility staff reflects urban neighborhood disparities, particularly when stratified by the social and structural determinants of community-level transmission.

Objective: This study aimed to compare the concentration of cumulative cases by geography and social and structural determinants across 3 mutually exclusive subgroups in the Greater Toronto Area (population: 7.1 million): community, facility staff, and health care workers (HCWs) in other settings.

Methods: We conducted a retrospective, observational study using surveillance data on laboratory-confirmed COVID-19 cases (January 23 to December 13, 2020; prior to vaccination rollout). We derived neighborhood-level social and structural determinants from census data and generated Lorenz curves, Gini coefficients, and the Hoover index to visualize and quantify inequalities in cases.

Results: The hardest-hit neighborhoods (comprising 20% of the population) accounted for 53.87% (44,937/83,419) of community cases, 48.59% (2356/4849) of facility staff cases, and 42.34% (1669/3942) of other HCW cases. Compared with other HCWs, cases among facility staff reflected the distribution of community cases more closely. Cases among facility staff reflected greater social and structural inequalities (larger Gini coefficients) than those of other HCWs across all determinants. Facility staff cases were also more likely than community cases to be concentrated in lower-income neighborhoods (Gini 0.24, 95% CI 0.15-0.38 vs 0.14, 95% CI 0.08-0.21) with a higher household density (Gini 0.23, 95% CI 0.17-0.29 vs 0.17, 95% CI 0.12-0.22) and with a greater proportion working in other essential services (Gini 0.29, 95% CI 0.21-0.40 vs 0.22, 95% CI 0.17-0.28).

Conclusions: COVID-19 cases among facility staff largely reflect neighborhood-level heterogeneity and disparities, even more so than cases among other HCWs. The findings signal the importance of interventions prioritized and tailored to the home geographies of facility staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighborhood level) and at work.

[The Journal of Infectious Diseases, 15 September 2022]

Background: Third coronavirus disease 2019 (COVID-19) vaccine doses are broadly recommended, but immunogenicity data remain limited, particularly in older adults.

Methods: We measured circulating antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor-binding domain, ACE2 displacement, and virus neutralization against ancestral and omicron (BA.1) strains from prevaccine up to 1 month following the third dose, in 151 adults aged 24–98 years who received COVID-19 mRNA vaccines.

Results: Following 2 vaccine doses, humoral immunity was weaker, less functional, and less durable in older adults, where a higher number of chronic health conditions was a key correlate of weaker responses and poorer durability. One month after the third dose, antibody concentrations and function exceeded post–second-dose levels, and responses in older adults were comparable in magnitude to those in younger adults at this time. Humoral responses against omicron were universally weaker than against the ancestral strain after both the second and third doses. Nevertheless, after 3 doses, anti-omicron responses in older adults reached equivalence to those in younger adults. One month after 3 vaccine doses, the number of chronic health conditions, but not age, was the strongest consistent correlate of weaker humoral responses.

Conclusions: Results underscore the immune benefits of third COVID-19 vaccine doses, particularly in older adults.

[The Lancet Infectious Diseases, 21 September 2022]

Background: There is a paucity of data on vaccine-induced or infection-induced (hybrid or natural) immunity against omicron (B.1.1.529) subvariant BA.2, particularly in comparing the effects of previous SARS-CoV-2 infection with the same or different genetic lineage. We aimed to estimate the protection against omicron BA.2 associated with previous primary infection with omicron BA.1 or pre-omicron SARS-CoV-2, among health-care workers with and without mRNA vaccination.

Methods: We conducted a test-negative case-control study among health-care workers aged 18 years or older who were tested for SARS-CoV-2 in Quebec, Canada, between March 27 and June 4, 2022, when BA.2 was the predominant variant and was presumptively diagnosed with a positive test result. We identified cases (positive test during study period) and controls (negative test during study period) using the provincial laboratory database that records all nucleic acid amplification testing for SARS-CoV-2 in Quebec, and used the provincial immunisation registry to determine vaccination status. Logistic regression models compared the likelihood of BA.2 infection or reinfection (second positive test ≥30 days after primary infection) among health-care workers who had previous primary infection and none to three mRNA vaccine doses versus unvaccinated health-care workers with no primary infection.

Findings: 258 007 SARS-CoV-2 tests were done during the study period. Among those with a valid result and that met the inclusion criteria, there were 37 732 presumed BA.2 cases (2521 [6·7%] reinfections following pre-omicron primary infection and 659 [1·7%] reinfections following BA.1 primary infection) and 73 507 controls (7360 [10·0%] had pre-omicron primary infection and 12 315 [16·8%] had BA.1 primary infection). Pre-omicron primary infection was associated with a 38% (95% CI 19–53) reduction in BA.2 infection risk, with higher BA.2 protection among those who had also received one (56%, 95% CI 47–63), two (69%, 64–73), or three (70%, 66–74) mRNA vaccine doses. Omicron BA.1 primary infection was associated with greater protection against BA.2 infection (risk reduction of 72%, 95% CI 65–78), and protection was increased further among those who had received two doses of mRNA vaccine (96%, 95–96), but was not improved with a third dose (96%, 95–97).

Interpretation: Health-care workers who had received two doses of mRNA vaccine and had previous BA.1 infection were subsequently well protected for a prolonged period against BA.2 reinfection, with a third vaccine dose conferring no improvement to that hybrid protection. If this protection also pertains to future variants, there might be limited benefit from additional vaccine doses for people with hybrid immunity, depending on timing and variant.

[Clinical Microbiology, 20 September 2022]

There is evidence that COVID-19 convalescent plasma may improve outcomes of patients with impaired immune systems; however, more clinical trials are required. Although we have previously used a 50% plaque reduction/neutralization titer (PRNT50) assay to qualify convalescent plasma for clinical trials and virus-like particle (VLP) assays to validate PRNT50 methodologies, these approaches are time-consuming and expensive. Here, we characterized the ability of the Abbott severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgG II Quant assay to identify high- and low-titer plasma for wild-type and variant (Alpha, Beta, Gamma, and Delta) SARS-CoV-2 characterized by both VLP assays and PRNT50. Plasma specimens previously tested in wild-type, Alpha, Beta, Gamma, and Delta VLP neutralization assays were selected based on availability. Selected specimens were evaluated by the Abbott SARS-CoV-2 IgG II Quant assay [Abbott anti-Spike (S); Abbott, Chicago, IL], and values in units per milliliter were converted to binding antibody units (BAU) per milliliter. Sixty-three specimens were available for analysis. Abbott SARS-CoV-2 IgG II Quant assay values in BAU per milliliter were significantly different between high- and low-titer specimens for wild-type (Mann-Whitney U = 42, P < 0.0001), Alpha (Mann-Whitney U = 38, P < 0.0001), Beta (Mann-Whitney U = 29, P < 0.0001), Gamma (Mann-Whitney U = 0, P < 0.0001), and Delta (Mann-Whitney U = 42, P < 0.0001). A conservative approach using the highest 95% confidence interval (CI) values from wild-type and variant of concern (VOC) SARS-CoV-2 experiments would identify a potential Abbott SARS-CoV-2 IgG II Quant assay cutoff of ≥7.1 × 103 BAU/mL.

IMPORTANCE: The United States Food and Drug Administration (FDA) issued an Emergency Use Authorization (EUA) for the use of COVID-19 convalescent plasma (CCP) to treat hospitalized patients with COVID-19 in August 2020. However, by 4 February 2021, the FDA had revised the convalescent plasma EUA. This revision limited the authorization for high-titer COVID-19 convalescent plasma and restricted patient groups to hospitalized patients with COVID-19 early in their disease course or hospitalized patients with impaired humoral immunity. Traditionally our group utilized 50% plaque reduction/neutralization titer (PRNT50) assays to qualify CCP in Canada. Since that time, the Abbott SARS-CoV-2 IgG II Quant assay (Abbott, Chicago IL) was developed for the qualitative and quantitative determination of IgG against the SARS-CoV-2. Here, we characterized the ability of the Abbott SARS-CoV-2 IgG II Quant assay to identify high- and low-titer plasma for wild-type and variant (Alpha, Beta, Gamma, and Delta) SARS-CoV-2.

[Preventive Medicine Reports, December 2022]

The long-term dynamics of COVID-19 disease incidence and public health measures may impact individuals’ precautionary behaviours as well as support for measures. The objectives of this study were to assess longitudinal changes in precautionary behaviours and support for public health measures. Survey data were collected online from 1030 Canadians in each of 5 cycles in 2020: June 15-July 13; July 22-Aug 8; Sept 7–15; Oct 14–21; and Nov 12–17. Precautionary behaviour increased over the study period in the context of increasing disease incidence. When controlling for the stringency of public health measures and disease incidence, mixed effects logistic regression models showed these behaviours did not significantly change over time. Odds ratios for avoiding contact with family and friends ranged from 0.84 (95% CI 0.59–1.20) in September to 1.25 (95% CI 0.66–2.37) in November compared with July 2020. Odds ratios for attending an indoor gathering ranged from 0.86 (95% CI 0.62–1.20) in August to 1.71 (95% CI 0.95–3.09) in October compared with July 2020. Support for non-essential business closures increased over time with 2.33 (95% CI 1.14–4.75) times higher odds of support in November compared to July 2020. Support for school closures declined over time with lower odds of support in September (OR 0.66 [95% CI 0.45–0.96]), October (OR 0.48 [95% CI 0.26–0.87]), and November (OR 0.39 [95% CI 0.19–0.81]) compared with July 2020. In summary, respondents’ behaviour mirrored government guidance between July and November 2020 and supported individual precautionary behaviour and limitations on non-essential businesses over school closures.

[PLoS ONE, 9 September 2022]

Importance: The measurement of laboratory biomarkers plays a critical role in managing patients with COVID-19. However, to date most systematic reviews examining the association between laboratory biomarkers and mortality in hospitalized patients early in the pandemic focused on small sets of biomarkers, did not account for multiple studies including patients within the same institutions during overlapping timeframes, and did not include a significant number of studies conducted in countries other than China.

Objective: To provide a comprehensive summary and an evidence map examining the relationship between a wide range of laboratory biomarkers and mortality among patients hospitalized with COVID-19 during the early phase of the pandemic in multiple countries.

Evidence review: MEDLINE, EMBASE, and Web of Science were searched from Dec 2019 to March 9, 2021. A total of 14,049 studies were identified and screened independently by two raters; data was extracted by a single rater and verified by a second. Quality was assessed using the Joanna Briggs Institute (JBI) Case Series Critical Appraisal tool. To allow comparison across biomarkers, standardized mean differences (SMD) were used to quantify the relationship between laboratory biomarkers and hospital mortality. Meta-regression was conducted to account for clustering within institutions and countries.

Results: Our systematic review included 94 case-series studies from 30 countries. Across all biomarkers, the largest and most precise SMDs were observed for cardiac (troponin (1.03 (95% CI 0.86 to 1.21)), and BNP/NT-proBNP (0.93 (0.52 to 1.34)), inflammatory (IL-6 (0.97 (0.67 to 1.28) and Neutrophil-to-lymphocyte ratio (0.94 (0.59 to 1.29)), and renal biomarkers (blood urea nitrogen (1.01 (0.79 to 1.23)) and estimated glomerular filtration rate (-0.96 (-1.42 to -0.50)). There was heterogeneity for most biomarkers across countries with studies conducted in China generally having larger effect sizes.

Conclusions and relevance: The results of this study provide an early pandemic summary of the relationship between biomarkers and mortality in hospitalized patients. We found our estimated ESs were generally attenuated compared to previous systematic reviews which predominantly included studies conducted in China. Despite using sophisticated methodology to examine studies across countries, heterogeneity in reporting of case-series studies early in the pandemic limits clinical interpretability.

[Frontiers in Immunology, 6 September 2022]

SARS-CoV-2 Omicron infections are common among individuals who are vaccinated or have recovered from prior variant infection, but few reports have immunologically assessed serial Omicron infections. We characterized SARS-CoV-2 humoral responses in an individual who acquired laboratory-confirmed Omicron BA.1.15 ten weeks after a third dose of BNT162b2, and BA.2 thirteen weeks later. Responses were compared to 124 COVID-19-naive vaccinees. One month post-second and -third vaccine doses, the participant’s wild-type and BA.1-specific IgG, ACE2-displacement and virus neutralization activities were average for a COVID-19-naive triple-vaccinated individual. BA.1 infection boosted the participant’s responses to the cohort ≥95th percentile, but even this strong “hybrid” immunity failed to protect against BA.2. Reinfection increased BA.1 and BA.2-specific responses only modestly. Though vaccines clearly protect against severe disease, results highlight the continued importance of maintaining additional protective measures to counteract the immune-evasive Omicron variant, particularly as vaccine-induced immune responses naturally decline over time.

[PLoS ONE, 29 August 2022]

Background: COVID-19 has rapidly emerged as a global public health threat with infections recorded in nearly every country. Responses to COVID-19 have varied in intensity and breadth, but generally have included domestic and international travel limitations, closure of non-essential businesses, and repurposing of health services. While these interventions have focused on testing, treatment, and mitigation of COVID-19, there have been reports of interruptions to diagnostic, prevention, and treatment services for other public health threats.

Objectives: We conducted a scoping review to characterize the early impact of COVID-19 on HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.

Methods: A scoping literature review was completed using searches of PubMed and preprint servers (medRxiv/bioRxiv) from November 1st, 2019 to October 31st, 2020, using Medical Subject Headings (MeSH) terms related to SARS-CoV-2 or COVID-19 and HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition. Empiric studies reporting original data collection or mathematical models were included, and available data synthesized by region. Studies were excluded if they were not written in English.

Results: A total of 1604 published papers and 205 preprints were retrieved in the search. Overall, 8.0% (129/1604) of published studies and 10.2% (21/205) of preprints met the inclusion criteria and were included in this review: 7.3% (68/931) on HIV, 7.1% (24/339) on tuberculosis, 11.6% (26/224) on malaria, 7.8% (19/183) on sexual and reproductive health, and 9.8% (13/132) on malnutrition. Thematic results were similar across competing health risks, with substantial indirect effects of the COVID-19 pandemic and response on diagnostic, prevention, and treatment services for HIV, tuberculosis, malaria, sexual and reproductive health, and malnutrition.

Discussion: COVID-19 emerged in the context of existing public health threats that result in millions of deaths every year. Thus, effectively responding to COVID-19 while minimizing the negative impacts of COVID-19 necessitates innovation and integration of existing programs that are often siloed across health systems. Inequities have been a consistent driver of existing health threats; COVID-19 has worsened disparities, reinforcing the need for programs that address structural risks. The data reviewed here suggest that effective strengthening of health systems should include investment and planning focused on ensuring the continuity of care for both rapidly emergent and existing public health threats.

[The Journal of Infectious Diseases, 27 January 2022]

Background: In British Columbia, Canada, most adults 50–69 years old became eligible for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine in April 2021, with chimpanzee adenoviral vectored vaccine (ChAdOx1) restricted to ≥55-year-olds and second doses deferred ≥6 weeks to optimize single-dose coverage.

Methods: Among adults 50–69 years old, single-dose messenger RNA (mRNA) and ChAdOx1 vaccine effectiveness (VE) against SARS-CoV-2 infection and hospitalization, including variant-specific, was assessed by test-negative design between 4 April and 2 October 2021.

Results: Single-dose VE included 11 861 cases and 99 544 controls. Median of postvaccination follow-up was 32 days (interquartile range, 15–52 days). Alpha, Gamma, and Delta variants comprised 23%, 18%, and 56%, respectively, of genetically characterized viruses. At 21–55 days postvaccination, single-dose mRNA and ChAdOx1 VE (95% confidence interval [CI]) was 74% (71%–76%) and 59% (53%–65%) against any infection and 86% (80%–90%) and 94% (85%–97%) against hospitalization, respectively. VE (95% CI) was similar against Alpha and Gamma infections for mRNA (80% [76%–84%] and 80% [75%–84%], respectively) and ChAdOx1 (69% [60%–76%] and 66% [56%–73%], respectively). mRNA VE was lower at 63% (95% CI, 56%–69%) against Delta but 85% (95% CI, 71%–92%) against Delta-associated hospitalization (nonestimable for ChAdOx1).

Conclusions: A single mRNA or ChAdOx1 vaccine dose gave important protection against SARS-CoV-2, including early variants of concern. ChAdOx1 VE was lower against infection, but 1 dose of either vaccine reduced the hospitalization risk by >85% to at least 8 weeks postvaccination. Findings inform program options, including longer dosing intervals.

[Clinical Infectious Diseases, 1 July 2022]

Background: In Canada, first and second doses of messenger RNA (mRNA) vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were uniquely spaced 16 weeks apart. We estimated 1- and 2-dose mRNA vaccine effectiveness (VE) among healthcare workers (HCWs) in Québec, Canada, including protection against varying outcome severity, variants of concern (VOCs), and the stability of single-dose protection up to 16 weeks postvaccination.

Methods: A test-negative design compared vaccination among SARS-CoV-2 test–positive and weekly matched (10:1), randomly sampled, test-negative HCWs using linked surveillance and immunization databases. Vaccine status was defined by 1 dose ≥14 days or 2 doses ≥7 days before illness onset or specimen collection. Adjusted VE was estimated by conditional logistic regression.

Results: Primary analysis included 5316 cases and 53 160 controls. Single-dose VE was 70% (95% confidence interval [CI], 68%–73%) against SARS-CoV-2 infection; 73% (95% CI, 71%–75%) against illness; and 97% (95% CI, 92%–99%) against hospitalization. Two-dose VE was 86% (95% CI, 81%–90%) and 93% (95% CI, 89%–95%), respectively, with no hospitalizations. VE was higher for non-VOCs than VOCs (73% Alpha) among single-dose recipients but not 2-dose recipients. Across 16 weeks, no decline in single-dose VE was observed, with appropriate stratification based upon prioritized vaccination determined by higher vs lower likelihood of direct patient contact.

Conclusions: One mRNA vaccine dose provided substantial and sustained protection to HCWs extending at least 4 months postvaccination. In circumstances of vaccine shortage, delaying the second dose may be a pertinent public health strategy.

[Clinical Infectious Diseases, 1 July 2022]

Background: Novel variants of concern (VOCs) have been associated with both increased infectivity and virulence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The virulence of SARS-CoV-2 is closely linked to age. Whether relative increases in virulence of novel VOCs are similar across the age spectrum or are limited to some age groups is unknown.

Methods: We created a retrospective cohort of people in Ontario, Canada, who tested positive for SARS-CoV-2 and were screened for VOCs (n = 259 984) between 7 February 2021 and 31 October 2021. Cases were classified as N501Y-positive VOC, probable Delta VOC, or VOC undetected. We constructed age-specific logistic regression models to evaluate associations between N501Y-postive or Delta VOC infections and infection severity using hospitalization, intensive care unit (ICU) admission, and death as outcome variables. Models were adjusted for sex, comorbidity, vaccination status, and temporal trends.

Results: Infection with either N501Y-positive or Delta VOCs was associated with significant elevations in risk of hospitalization, ICU admission, and death across age groups compared with infections where a VOC was not detected. The Delta VOC increased hospitalization risk in children aged <10 years by a factor of 2.5 (adjusted odds ratio; 95% confidence interval, 1.3 to 5.0) compared with non-VOCs. There was a significant inverse relationship between age and relative increase in risk of death with the Delta VOC, with younger age groups showing a greater relative increase in risk of death than older individuals.

Conclusions: SARS-CoV-2 VOCs appear to be associated with increased relative virulence of infection in all age groups, though low absolute numbers of outcomes in younger individuals make estimates in these groups imprecise.

[Clinical Infectious Diseases, 1 July 2022]

Background: People in prison are at increased risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We examined the seroprevalence of SARS-CoV-2 and associated carceral risk factors among incarcerated adult men in Quebec, Canada.

Methods: We conducted a cross-sectional seroprevalence study in 2021 across 3 provincial prisons, representing 45% of Quebec’s incarcerated male provincial population. The primary outcome was SARS-CoV-2 antibody seropositivity (Roche Elecsys serology test). Participants completed self-administered questionnaires on sociodemographic, clinical, and carceral characteristics. The association of carceral variables with SARS-CoV-2 seropositivity was examined using Poisson regression models with robust standard errors. Crude and adjusted prevalence ratios (aPR) with 95% confidence intervals (95% CIs) were calculated.

Results: Between 19 January 2021 and 15 September 2021, 246 of 1100 (22%) recruited individuals tested positive across 3 prisons (range, 15%–27%). Seropositivity increased with time spent in prison since March 2020 (aPR, 2.17; 95% CI, 1.53–3.07 for “all” vs “little time”), employment during incarceration (aPR, 1.64; 95% CI, 1.28–2.11 vs not), shared meal consumption during incarceration (“with cellmates”: aPR, 1.46; 95% CI, 1.08–1.97 vs “alone”; “with sector”: aPR, 1.34; 95% CI, 1.03–1.74 vs “alone”), and incarceration post-prison outbreak (aPR, 2.32; 95% CI, 1.69–3.18 vs “pre-outbreak”).

Conclusions: The seroprevalence of SARS-CoV-2 among incarcerated individuals was high and varied among prisons. Several carceral factors were associated with seropositivity, underscoring the importance of decarceration and occupational safety measures, individual meal consumption, and enhanced infection prevention and control measures including vaccination during incarceration.

[PLoS ONE, 31 March 2023]

Background: Vaccines against SARS-CoV-2 have been shown to reduce risk of infection as well as severe disease among those with breakthrough infection in adults. The latter effect is particularly important as immune evasion by Omicron variants appears to have made vaccines less effective at preventing infection. Therefore, we aimed to quantify the protection conferred by mRNA vaccination against hospitalization due to SARS-CoV-2 in adolescent and pediatric populations.

Methods: We retrospectively created a cohort of reported SARS-CoV-2 case records from Ontario’s Public Health Case and Contact Management Solution among those aged 4 to 17 linked to vaccination records from the COVaxON database on January 19, 2022. We used multivariable logistic regression to estimate the association between vaccination and hospitalization among SARS-CoV-2 cases prior to and during the emergence of Omicron.

Results: We included 62 hospitalized and 27,674 non-hospitalized SARS-CoV-2 cases, with disease onset from May 28, 2021 to December 4, 2021 (Pre-Omicron) and from December 23, 2021 to January 9, 2022 (Omicron). Among adolescents, two mRNA vaccine doses were associated with an 85% (aOR = 0.15; 95% CI: [0.04, 0.53]; p<0.01) lower likelihood of hospitalization among SARS-CoV-2 cases caused by Omicron. Among children, one mRNA vaccine dose was associated with a 79% (aOR = 0.21; 95% CI: [0.03, 0.77]; p<0.05) lower likelihood of hospitalization among SARS-CoV-2 cases caused by Omicron. The calculation of E-values, which quantifies how strong an unmeasured confounder would need to be to nullify our findings, suggest that these effects are unlikely to be explained by unmeasured confounding.

Conclusions: Despite immune evasion by SARS-CoV-2 variants, vaccination continues to be associated with a lower likelihood of hospitalization among adolescent and pediatric Omicron (B.1.1.529) SARS-CoV-2 cases, even when the vaccines do not prevent infection. Continued efforts are needed to increase vaccine uptake among adolescent and pediatric populations.

[Canada Communicable Disease Report, 31 May 2023]

Background: National responses to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic have been highly variable. We sought to explore the effectiveness of the Canadian pandemic response up to May 2022 relative to responses in four peer countries with similar political, economic and health systems, and with close historical and cultural ties to Canada.

Methods: We used reported age-specific mortality data to generate estimates of pandemic mortality standardized to the Canadian population. Age-specific case fatality, hospitalization, and intensive care admission probabilities for the Canadian province of Ontario were applied to estimated deaths, to calculate hospitalizations and intensive care admissions averted by the Canadian response. Health impacts were valued in both monetary terms, and in terms of lost quality-adjusted life years.

Results: We estimated that the Canadian pandemic response averted 94,492, 64,306 and 13,641 deaths relative to the responses of the United States, United Kingdom and France, respectively, and more than 480,000 hospitalizations relative to the United States. The United States pandemic response, if applied to Canada, would have resulted in more than $40 billion in economic losses due to healthcare expenditures and lost quality-adjusted life years. In contrast, an Australian pandemic response applied to Canada would have averted over 28,000 additional deaths and averted nearly $9 billion in costs.

Conclusion: Canada outperformed several peer countries that aimed for mitigation rather than elimination of SARS-CoV-2 in the first two years of the pandemic, with substantial numbers of lives saved and economic costs averted. However, a comparison with Australia demonstrated that an elimination focus would have saved Canada tens of thousands of lives as well as substantial economic costs.

[Emerging Infectious Diseases, October 2023]

In British Columbia, Canada, initial growth of the SARS-CoV-2 Delta variant was slower than that reported in other jurisdictions. Delta became the dominant variant (>50% prevalence) within ≈7–13 weeks of first detection in regions within the United Kingdom and United States. In British Columbia, it remained at <10% of weekly incident COVID-19 cases for 13 weeks after first detection on March 21, 2021, eventually reaching dominance after 17 weeks. We describe the growth of Delta variant cases in British Columbia during March 1–June 30, 2021, and apply retrospective counterfactual modeling to examine factors for the initially low COVID-19 case rate after Delta introduction, such as vaccination coverage and nonpharmaceutical interventions. Growth of COVID-19 cases in the first 3 months after Delta emergence was likely limited in British Columbia because additional nonpharmaceutical interventions were implemented to reduce levels of contact at the end of March 2021, soon after variant emergence.

[Vaccine, 16 September 2023]

Background: It is evident that COVID-19 will remain a public health concern in the coming years, largely driven by variants of concern (VOC). It is critical to continuously monitor vaccine effectiveness as new variants emerge and new vaccines and/or boosters are developed. Systematic surveillance of the scientific evidence base is necessary to inform public health action and identify key uncertainties. Evidence syntheses may also be used to populate models to fill in research gaps and help to prepare for future public health crises. This protocol outlines the rationale and methods for a living evidence synthesis of the effectiveness of COVID-19 vaccines in reducing the morbidity and mortality associated with, and transmission of, VOC of SARS-CoV-2.

Methods: Living evidence syntheses of vaccine effectiveness will be carried out over one year for (1) a range of potential outcomes in the index individual associated with VOC (pathogenesis); and (2) transmission of VOC. The literature search will be conducted up to May 2023. Observational and database-linkage primary studies will be included, as well as RCTs. Information sources include electronic databases (MEDLINE; Embase; Cochrane, L*OVE; the CNKI and Wangfang platforms), pre-print servers (medRxiv, BiorXiv), and online repositories of grey literature. Title and abstract and full-text screening will be performed by two reviewers using a liberal accelerated method. Data extraction and risk of bias assessment will be completed by one reviewer with verification of the assessment by a second reviewer. Results from included studies will be pooled via random effects meta-analysis when appropriate, or otherwise summarized narratively.

Discussion: Evidence generated from our living evidence synthesis will be used to inform policy making, modelling, and prioritization of future research on the effectiveness of COVID-19 vaccines against VOC.

[Healthcare Policy, August 2023]

Background: This paper aims to assess the extent to which the COVID-19 vaccine's speed to market affected Canadian residents' decision to remain unvaccinated.

Method: A cross-sectional survey conducted in late 2021 asked participants whether they had received the vaccine and their reasons for abstaining.

Results: Of the 2,712 participants who completed the survey, 8.9% remained unvaccinated. Unvaccinated respondents who selected “They made the vaccine too fast” (59.8%), were significantly more likely to identify as white, believe that the COVID-19 pandemic was not serious and have an unvaccinated social circle.

Conclusion: Should the COVID-19 vaccine rapid regulatory process be expanded, more patients may refuse treatment than if traditional timelines are followed.

[Vaccine, 5 September 2023]

Background: The Global COVID Vaccine Safety (GCoVS) project was established in 2021 under the multinational Global Vaccine Data Network (GVDN) consortium to facilitate the rapid assessment of the safety of newly introduced vaccines. This study analyzed data from GVDN member sites on the background incidence rates of conditions designated as adverse events of special interest (AESI) for COVID-19 vaccine safety monitoring.

Methods: Eleven GVDN global sites obtained data from national or regional healthcare databases using standardized methods. Incident events of 13 pre-defined AESI were included for a pre-pandemic period (2015–19) and the first pandemic year (2020). Background incidence rates (IR) and 95% confidence intervals (CI) were calculated for inpatient and emergency department encounters, stratified by age and sex, and compared between pre-pandemic and pandemic periods using incidence rate ratios.

Results: An estimated 197 million people contributed 1,189,652,926 person-years of follow-up time. Among inpatients in the pre-pandemic period (2015–19), generalized seizures were the most common neurological AESI (IR ranged from 22.15 [95% CI 19.01–25.65] to 278.82 [278.20–279.44] per 100,000 person-years); acute disseminated encephalomyelitis was the least common (<0.5 per 100,000 person-years at most sites). Pulmonary embolism was the most common thrombotic event (IR 45.34 [95% CI 44.85–45.84] to 93.77 [95% CI 93.46–94.08] per 100,000 person-years). The IR of myocarditis ranged from 1.60 [(95% CI 1.45–1.76) to 7.76 (95% CI 7.46–8.08) per 100,000 person-years. The IR of several AESI varied by site, healthcare setting, age and sex. The IR of some AESI were notably different in 2020 compared to 2015–19.

Conclusion: Background incidence of AESIs exhibited some variability across study sites and between pre-pandemic and pandemic periods. These findings will contribute to global vaccine safety surveillance and research.

[Journal of the Royal Society of Interface, 30 August 2023]

As the SARS-CoV-2 trajectory continues, the longer-term immuno-epidemiology of COVID-19, the dynamics of Long COVID, and the impact of escape variants are important outstanding questions. We examine these remaining uncertainties with a simple modelling framework that accounts for multiple (antigenic) exposures via infection or vaccination. If immunity (to infection or Long COVID) accumulates rapidly with the valency of exposure, we find that infection levels and the burden of Long COVID are markedly reduced in the medium term. More pessimistic assumptions on host adaptive immune responses illustrate that the longer-term burden of COVID-19 may be elevated for years to come. However, we also find that these outcomes could be mitigated by the eventual introduction of a vaccine eliciting robust (i.e. durable, transmission-blocking and/or ‘evolution-proof’) immunity. Overall, our work stresses the wide range of future scenarios that still remain, the importance of collecting real-world epidemiological data to identify likely outcomes, and the crucial need for the development of a highly effective transmission-blocking, durable and broadly protective vaccine.

[PLoS ONE, 23 August 23, 2023]

Background: The effects of the COVID-19 pandemic have been more pronounced for socially disadvantaged populations. We sought to determine how access to SARS-CoV-2 testing and the likelihood of testing positive for COVID-19 were associated with demographic factors, socioeconomic status (SES) and social determinants of health (SDH) in three Canadian provinces.

Methods: An observational population-based cross-sectional study was conducted for the provinces of Ontario, Manitoba and New Brunswick between March 1, 2020 and April 27, 2021, using provincial health administrative data. After excluding residents of long-term care homes, those without current provincial health insurance and those who were tested for COVID-19 out of province, records from provincial healthcare administrative databases were reviewed for 16,900,661 healthcare users. Data was modelled separately for each province in accordance to a prespecified protocol and follow-up consultations among provincial statisticians and collaborators. We employed univariate and multivariate regression models to examine determinants of testing and test results.

Results: After adjustment for other variables, female sex and urban residency were positively associated with testing, while female sex was negatively associated with test positivity. In New Brunswick and Ontario, individuals living in higher income areas were more likely to be tested, whereas in Manitoba higher income was negatively associated with both testing and positivity. High ethnocultural composition was associated with lower testing rates. Both high ethnocultural composition and high situational vulnerability increased the odds of testing positive for SARS-CoV-2.

Discussion: We observed that multiple demographic, income and SDH factors were associated with SARS-CoV-2 testing and test positivity. Barriers to healthcare access identified in this study specifically relate to COVID-19 testing but may reflect broader inequities for certain at-risk groups.

[CMAJ, 14 August 2023]

Background: During the first year of the COVID-19 pandemic, the proportion of reported cases of COVID-19 among Canadians was under 6%. Although high vaccine coverage was achieved in Canada by fall 2021, the Omicron variant caused unprecedented numbers of infections, overwhelming testing capacity and making it difficult to quantify the trajectory of population immunity.

Methods: Using a time-series approach and data from more than 900 000 samples collected by 7 research studies collaborating with the COVID-19 Immunity Task Force (CITF), we estimated trends in SARS-CoV-2 seroprevalence owing to infection and vaccination for the Canadian population over 3 intervals: prevaccination (March to November 2020), vaccine roll-out (December 2020 to November 2021), and the arrival of the Omicron variant (December 2021 to March 2023). We also estimated seroprevalence by geographical region and age.

Results: By November 2021, 9.0% (95% credible interval [CrI] 7.3%–11%) of people in Canada had humoral immunity to SARS-CoV-2 from an infection. Seroprevalence increased rapidly after the arrival of the Omicron variant — by Mar. 15, 2023, 76% (95% CrI 74%–79%) of the population had detectable antibodies from infections. The rapid rise in infection-induced antibodies occurred across Canada and was most pronounced in younger age groups and in the Western provinces: Manitoba, Saskatchewan, Alberta and British Columbia.

Interpretation: Data up to March 2023 indicate that most people in Canada had acquired antibodies against SARS-CoV-2 through natural infection and vaccination. However, given variations in population seropositivity by age and geography, the potential for waning antibody levels, and new variants that may escape immunity, public health policy and clinical decisions should be tailored to local patterns of population immunity.

The COVID-19 pandemic defied expectations about immunity arising from infection and vaccination. During the first months of the pandemic, despite the burden on Canadian society and health systems, rates of symptomatic infection remained low, with 580 000 confirmed cases by December 2020, representing 1.6% of the Canadian population.1 Vaccines were widely distributed in Canada beginning in early 2021, with a rapid rise in vaccine coverage to 79% by fall of 2021,2 whereas cumulative reported cases of COVID-19 remained low, at 4.7% of the population.3 The arrival of Omicron variants and subvariants, however, caused an unprecedented increase in the number of infections. In short, the high vaccine coverage, combined with population immunity from infections in earlier waves of the pandemic, were insufficient to slow the spread of the Omicron variant.

Although the overall progression of confirmed cases and vaccination is clear, the underlying dynamics of population seropositivity are less obvious, yet critically important for policy and clinical decisions about vaccination and other preventive measures. A count of confirmed cases of COVID-19 is of limited use for understanding the evolution of population immunity because case ascertainment is biased by multiple factors. Most notably, access to laboratory-based polymerase chain reaction (PCR) testing varied across the country and, in many locations, was overwhelmed by demand after December 2021. In this context, serological surveillance provides an informative adjunct to monitoring confirmed cases, as seroprevalence offers a more direct measure of population humoral immunity.

We sought to describe the trajectory of SARS-CoV-2 seroprevalence in the Canadian population, as measured by anti-nucleocapsid (anti-N) and anti-spike protein (anti-S) antibody levels over 3 intervals: prevaccination (March to November 2020), vaccine roll-out (December 2020 to November 2021), and the Omicron variant waves (December 2021 to March 2023). We draw on seroprevalence estimates from multiple studies collaborating with the COVID-19 Immunity Task Force (CITF).4 In addition to describing the temporal evolution of population seropositivity in Canada, we highlight trends in infection-acquired and vaccine-induced seroprevalence by Canadian region and age.

[Clinical Infectious Diseases, 1 August 2023]

Background: Antibiotics are frequently prescribed unnecessarily in outpatients with coronavirus disease 2019 (COVID-19). We sought to evaluate factors associated with antibiotic prescribing in outpatients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection.

Methods: We performed a population-wide cohort study of outpatients aged ≥66 years with polymerase chain reaction–confirmed SARS-CoV-2 from 1 January 2020 to 31 December 2021 in Ontario, Canada. We determined rates of antibiotic prescribing within 1 week before (prediagnosis) and 1 week after (postdiagnosis) reporting of the positive SARS-CoV-2 result, compared to a self-controlled period (baseline). We evaluated predictors of prescribing, including a primary-series COVID-19 vaccination, in univariate and multivariable analyses.

Results: We identified 13 529 eligible nursing home residents and 50 885 eligible community-dwelling adults with SARS-CoV-2 infection. Of the nursing home and community residents, 3020 (22%) and 6372 (13%), respectively, received at least 1 antibiotic prescription within 1 week of a SARS-CoV-2 positive result. Antibiotic prescribing in nursing home and community residents occurred, respectively, at 15.0 and 10.5 prescriptions per 1000 person-days prediagnosis and 20.9 and 9.8 per 1000 person-days postdiagnosis, higher than the baseline rates of 4.3 and 2.5 prescriptions per 1000 person-days. COVID-19 vaccination was associated with reduced prescribing in nursing home and community residents, with adjusted postdiagnosis incidence rate ratios (95% confidence interval) of 0.7 (0.4–1) and 0.3 (0.3–0.4), respectively.

Conclusions: Antibiotic prescribing was high and with little or no decline following SARS-CoV-2 diagnosis but was reduced in COVID-19–vaccinated individuals, highlighting the importance of vaccination and antibiotic stewardship in older adults with COVID-19.

[Nature Communications, 10 August 2023]

Serial intervals – the time between symptom onset in infector and infectee – are a fundamental quantity in infectious disease control. However, their estimation requires knowledge of individuals’ exposures, typically obtained through resource-intensive contact tracing efforts. We introduce an alternate framework using virus sequences to inform who infected whom and thereby estimate serial intervals. We apply our technique to SARS-CoV-2 sequences from case clusters in the first two COVID-19 waves in Victoria, Australia. We find that our approach offers high resolution, cluster-specific serial interval estimates that are comparable with those obtained from contact data, despite requiring no knowledge of who infected whom and relying on incompletely-sampled data. Compared to a published serial interval, cluster-specific serial intervals can vary estimates of the effective reproduction number by a factor of 2–3. We find that serial interval estimates in settings such as schools and meat processing/packing plants are shorter than those in healthcare facilities.

[Biometrics, 10 August 2023]

We develop a proportional incidence model that estimates vaccine effectiveness (VE) at the population level using conditional likelihood for aggregated data. Our model assumes that the population counts of clinical outcomes for an infectious disease arise from a superposition of Poisson processes with different vaccination statuses. The intensity function in the model is calculated as the product of per capita incidence rate and the at-risk population size, both of which are time-dependent. We formulate a log-linear regression model with respect to the relative risk, defined as the ratio between the per capita incidence rates of vaccinated and unvaccinated individuals. In the regression analysis, we treat the baseline incidence rate as a nuisance parameter, similar to the Cox proportional hazard model in survival analysis. We then apply the proposed models and methods to age-stratified weekly counts of COVID-19–related hospital and ICU admissions among adults in Ontario, Canada. The data spanned from 2021 to February 2022, encompassing the Omicron era and the rollout of booster vaccine doses. We also discuss the limitations and confounding effects while advocating for the necessity of more comprehensive and up-to-date individual-level data that document the clinical outcomes and measure potential confounders.

[Journal of Clinical Epidemiology, 8 August 2023]

Background and Objective: To identify COVID-19 actionable statements (e.g., recommendations) focused on specific disadvantaged populations in the living map of COVID-19 recommendations (eCOVIDRecMap) and describe how health equity was assessed in the development of the formal recommendations.

Methods: We employed the place of residence, race or ethnicity or culture, occupation, gender or sex, religion, education, socio-economic status, and social capital-Plus framework to identify statements focused on specific disadvantaged populations. We assessed health equity considerations in the evidence to decision frameworks (EtD) of formal recommendations for certainty of evidence and impact on health equity criteria according to the Grading of Recommendations, Assessment, Development, and Evaluations criteria.

Results: We identified 16% (124/758) formal recommendations and 24% (186/819) good practice statements (GPS) that were focused on specific disadvantaged populations. Formal recommendations (40%, 50/124) and GPS (25%, 47/186) most frequently focused on children. Seventy-six percent (94/124) of the recommendations were accompanied with EtDs. Over half (55%, 52/94) of those considered indirectness of the evidence for disadvantaged populations. Considerations in impact on health equity criterion most frequently involved implementation of the recommendation for disadvantaged populations (17%, 16/94).

Conclusion: Equity issues were rarely explicitly considered in the development COVID-19 formal recommendations focused on specific disadvantaged populations. Guidance is needed to support the consideration of health equity in guideline development during health emergencies.

[Water Research, 8 August 2023]

Wastewater-based surveillance (WBS) has been established as a powerful tool that can guide health policy at multiple levels of government. However, this approach has not been well assessed at more granular scales, including large work sites such as University campuses. Between August 2021 and April 2022, we explored the occurrence of SARS-CoV-2 RNA in wastewater using qPCR assays from multiple complimentary sewer catchments and residential buildings spanning the University of Calgary's campus and how this compared to levels from the municipal wastewater treatment plant servicing the campus. Real-time contact tracing data was used to evaluate an association between wastewater SARS-CoV-2 burden and clinically confirmed cases and to assess the potential of WBS as a tool for disease monitoring across worksites. Concentrations of wastewater SARS-CoV-2 N1 and N2 RNA varied significantly across six sampling sites – regardless of several normalization strategies – with certain catchments consistently demonstrating values 1–2 orders higher than the others. Relative to clinical cases identified in specific sewersheds, WBS provided one-week leading indicator. Additionally, our comprehensive monitoring strategy enabled an estimation of the total burden of SARS-CoV-2 for the campus per capita, which was significantly lower than the surrounding community (p≤0.001). Allele-specific qPCR assays confirmed that variants across campus were representative of the community at large, and at no time did emerging variants first debut on campus. This study demonstrates how WBS can be efficiently applied to locate hotspots of disease activity at a very granular scale, and predict disease burden across large, complex worksites.

[American Journal of Epidemiology, 9 March 2023]

Evidence from early observational studies suggested negative vaccine effectiveness (⁠VEff) for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. Since true VEff is unlikely to be negative, we explored how differences in contact among vaccinated persons (e.g., potentially from the implementation of vaccine mandates) could lead to observed negative VEff. Using a susceptible-exposed-infectious-recovered (SEIR) transmission model, we examined how vaccinated-contact heterogeneity, defined as an increase in the contact rate only between vaccinated individuals, interacted with 2 mechanisms of vaccine efficacy: vaccine efficacy against susceptibility (⁠VES) and vaccine efficacy against infectiousness (⁠VEI), to produce underestimated and in some cases, negative measurements of VEff. We found that vaccinated-contact heterogeneity led to negative estimates when VEI, and especially VES⁠, were low. Moreover, we determined that when contact heterogeneity was very high, VEff could still be underestimated given relatively high vaccine efficacies (0.7), although its effect on VEff was strongly reduced. We also found that this contact heterogeneity mechanism generated a signature temporal pattern: The largest underestimates and negative measurements of VEff occurred during epidemic growth. Overall, our research illustrates how vaccinated-contact heterogeneity could have feasibly produced negative measurements during the Omicron period and highlights its general ability to bias observational studies of VEff⁠.

[Infection, Genetics and Evolution, 2 August 2023]

Objectives: Clustering pathogen sequence data is a common practice in epidemiology to gain insights into the genetic diversity and evolutionary relationships among pathogens. We can find groups of cases with a shared transmission history and common origin, as well as identifying transmission hotspots. Motivated by the experience of clustering SARS-CoV-2 cases using whole genome sequence data during the COVID-19 pandemic to aid with public health investigation, we investigated how differences in epidemiology and sampling can influence the composition of clusters that are identified.

Methods: We performed genomic clustering on simulated SARS-CoV-2 outbreaks produced with different transmission rates and levels of genomic diversity, along with varying the proportion of cases sampled.

Results: In single outbreaks with a low transmission rate, decreasing the sampling fraction resulted in multiple, separate clusters being identified where intermediate cases in transmission chains are missed. Outbreaks simulated with a high transmission rate were more robust to changes in the sampling fraction and largely resulted in a single cluster that included all sampled outbreak cases. When considering multiple outbreaks in a sampled jurisdiction seeded by different introductions, low genomic diversity between introduced cases caused outbreaks to be merged into large clusters. If the transmission and sampling fraction, and diversity between introductions was low, a combination of the spurious break-up of outbreaks and the linking of closely related cases in different outbreaks resulted in clusters that may appear informative, but these did not reflect the true underlying population structure. Conversely, genomic clusters matched the true population structure when there was relatively high diversity between introductions and a high transmission rate.

Conclusion: Differences in epidemiology and sampling can impact our ability to identify genomic clusters that describe the underlying population structure. These findings can help to guide recommendations for the use of pathogen clustering in public health investigations.

[BMJ, 24 July 2023]

Canada’s public health system was reformed after its 2003 severe acute respiratory syndrome (SARS) outbreak, which was the worst outside of Asia with 438 cases and 44 deaths. Ensuing national and provincial inquiries led to the creation of the national Public Health Agency of Canada (PHAC) to coordinate Canada’s preparation for and response to public health threats. Subnational public health agencies were also created or strengthened to function as regional centres for disease control. These actions should have put Canada in a good position to respond to the covid-19 pandemic.

Despite these reforms, Canada experienced serious failures during the covid-19 pandemic. Memories faded rapidly after SARS, and if history is not to repeat itself, government and health system leaders must strengthen the country’s public health and healthcare systems in preparation for the next threat. Health authorities as well as all Canadians need to reflect on the crises of the past three years—what went well and why; what caused pandemic response failures, and what were their consequences? Here, in the first of a series of articles examining Canada’s response and setting out suggestions for a national inquiry, we examine the limitations of the country’s decentralised structure for public health decision making and missed lessons from the 2003 SARS-CoV-1 outbreak, particularly with regard to data infrastructure.5 Other articles in the series examine how research and data failed to inform public health responses tailored to community and population needs, the predictable failures in long term care, and Canada’s role in global vaccine inequity…

[BMJ, 24 July 2023]

Canada had one of the lowest rates of covid-19 cases and deaths per population than most in the G10 group of industrialised countries. But overall rates ignore underlying health inequalities—a consistent feature of the covid-19 pandemic across countries, within and outside the G10. Across every G10 country, for example, economic marginalisation was associated with twofold to fourfold higher rates of covid deaths.

Disproportionate risks of exposures and transmissions are shaped by physical and social networks: how, under what context, and with whom infectious disease contacts take place. The same context that governs these networks often defines what happens after infection occurs: access to and quality of care and treatment within a healthcare system that is built with the same tools as the social and economic system that failed to mitigate disproportionate risks. Yet early in the pandemic, Canada, like most countries, largely applied public health measures universally across its decentralised public health system with little focus on how measures and strategies would, or would not, reach and apply to those most at risk.

[Annals of Internal Medicine, 18 July 2023]

Regarding their trial, Loeb and colleagues (1) state, “the overall estimates rule out a doubling in hazard”; however, no such conclusion is possible. The trial used an extraordinary threshold (a hazard ratio of 2, or a 100% relative increase in risk) for noninferiority and was underpowered to find smaller but still important risks. (We estimate that a 4-fold increase in sample size would have been needed to identify a 50% increase in relative hazard.) Power aside, design flaws biased the study toward the null result that was obtained.

The intervention under study was incorrect use of N95 respirators—intermittently rather than continuously. SARS-CoV-2 is an airborne pathogen (2). Infection occurs via inhalation of shared air, and infective aerosols accumulate over time in closed indoor settings. As such, only continuous use of N95 respirators protects health care workers against respiratory infection; intermittent use of medical masks and respirators is equally ineffective (3). Unplanned crossover (those randomly assigned to medical masks could reassign themselves to the N95 group on the basis of unrecorded risk assessment) and contamination due to failure to use a cluster design further biased study results toward the null (4).

Notwithstanding lack of power and multiple biases—and although only 21 infections developed among 301 participants recruited in Canada and Israel through May 2021—analysis according to the registered protocol reveals a doubling of risk for infection for medical masks (relative risk, 2.05 [95% CI, 0.85 to 4.95]; P = 0.10) in these participants. The study had come close to showing inferiority after recruiting only a fraction of its prespecified sample size. Around this time, the authors recalculated their required sample size (in July 2021) as 1010 participants and began recruiting participants in Pakistan at a site not mentioned in the trial's registered protocol. Six months later, recruitment in Pakistan was discontinued and was begun in Egypt (also not registered in the protocol). Final results were heavily influenced by the inclusion of the sites in Egypt, with more than 70% of infections originating there. As Altman and associates note, “when authors substitute other outcomes after the trial has started there must be concern that such changes were done with knowledge of the data. That casts doubt on the reliability and integrity of the results” (5).

Lastly, the performance of this trial lacked equipoise in the face of clear engineering evidence of the superiority of respirators for airborne pathogens. The fact that this trial was done in a flawed manner that could not provide valid results means that participants were endangered for no reason.

[The Lancet Healthy Longevity, 14 July 2023]

Background: Older adults (aged ≥60 years) were prioritised for COVID-19 booster vaccination due to severe outcome risk, but the risk for this group is also affected by previous SARS-CoV-2 infection and vaccination. We estimated vaccine effectiveness against omicron-associated hospitalisation in older adults by previously documented infection, time since last immunological event, and age group.

Methods: This was a population-based test-negative case-control study done in Quebec, Canada, during BA.1 dominant (December, 2021, to March, 2022), BA.2 dominant (April to June, 2022), and BA.4/5 dominant (July to November, 2022) periods using provincial laboratory, immunisation, hospitalisation, and chronic disease surveillance databases. We included older adults (aged ≥60 years) with symptoms associated with COVID-19 who were tested for SARS-CoV-2 in acute-care hospitals. Cases were defined as patients who were hospitalised for COVID-19 within 14 days after testing positive; controls were patients who tested negative. Analyses spanned 3–14 months after last vaccine dose or previous infection. Logistic regression models compared COVID-19 hospitalisation risk by mRNA vaccine dose and previous infection versus unvaccinated and infection-naive participants.

Findings: Between Dec 26, 2021, and Nov 5, 2022, we included 174 819 specimens (82 870 [47·4%] from men and 91 949 [52·6%] from women; from 8455 cases and 166 364 controls), taken from 2951 cases and 48 724 controls in the BA.1 period; 1897 cases and 41 702 controls in the BA.2 period; and 3607 cases and 75 938 controls in the BA.4/5 period. In participants who were infection naive, vaccine effectiveness against hospitalisation improved with dose number, consistent with a shorter median time since last dose, but decreased with more recent omicron subvariants. Four-dose vaccine effectiveness was 96% (95% CI 93–98) during the BA.1 period, 84% (81–87) during the BA.2 period, and 68% (63–72) during the BA.4/5 period. Regardless of dose number (two to five doses) or timing since previous infection, hybrid protection was more than 90%, persisted for at least 6–8 months, and did not decline with age.

Interpretation: Older adults with both previous SARS-CoV-2 infection and two or more vaccine doses appear to be well protected for a prolonged period against hospitalisation due to omicron subvariants, including BA.4/5. Ensuring that older adults who are infection naive remain up to date with vaccination might reduce COVID-19 hospitalisations most efficiently.

[iScience, 13 July 2023]

Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.

[Thorax, 9 July 2023]

Introduction: Airway disease exacerbations are cyclical related to respiratory virus prevalence. The COVID-19 pandemic has been associated with reduced exacerbations possibly related to public health measures and their impact on non-COVID-19 respiratory viruses. We aimed to investigate the prevalence of non-COVID-19 respiratory viruses during the pandemic compared with prior in Ontario, Canada and healthcare utilisation related to asthma, chronic obstructive pulmonary disease (COPD) and respiratory tract infection.

Methods: This is a population-based retrospective analysis of respiratory virus tests, emergency department (ED) visits and hospitalisations between 2015 and 2021 in Ontario. Weekly virus testing data were used to estimate viral prevalence for all non-COVID-19 respiratory viruses. We plotted the %positivity and observed and expected counts of each virus to visualise the impact of the pandemic. We used Poisson and binomial logistic regression models to estimate the change in %positivity, count of positive viral cases and count of healthcare utilisation during the pandemic.

Results: The prevalence of all non-COVID-19 respiratory viruses decreased dramatically during the pandemic compared with prior. Comparing periods, the incidence rate ratio (IRR) for positive cases corresponded to a >90% reduction for non-COVID-19 respiratory viruses except adenovirus and rhino/enterovirus. Asthma-related ED visits and hospital admissions fell by 57% (IRR 0.43 (95% CI 0.37 to 0.48)) and 61% (IRR 0.39 (95% CI 0.33 to 0.46)). COPD-related ED visits and admissions fell by 63% (IRR 0.37 (95% CI 0.30 to 0.45)) and 45% (IRR 0.55 (95% CI 0.48 to 0.62)). Respiratory tract infection ED visits and admissions fell by 85% (IRR 0.15 (95% CI 0.10 to 0.22)), and 85% (IRR 0.15 (95% CI 0.09 to 0.24)). Rather than the usual peaks in disease condition, during the pandemic, healthcare utilisation peaked in October when rhino/enterovirus peaked.

Conclusions: The prevalence of nearly all non-COVID-19 respiratory viruses decreased during the pandemic and was associated with marked reductions in ED visits and hospitalisations. The re-emergence of rhino/enterovirus was associated with increased healthcare utilisation.

[International Journal of Infectious Diseases, 5 July 2023]

Objective: To examine the risk of hospitalization within 14 days of COVID-19 diagnosis among people living with HIV (PLWH) and HIV-negative individuals who had laboratory-confirmed SARS-CoV-2 infection.

Methods: We used Cox proportional hazard models to compare the relative risk of hospitalization in PLWH and HIV-negative individuals. Then, we used propensity score weighting to examine the influence of sociodemographic factors and comorbid conditions on risk of hospitalization. These models were further stratified by vaccination status and pandemic period (pre-Omicron: December 15, 2020, to November 21, 2021; Omicron: November 22, 2021, to October 31, 2022).

Results: The crude hazard ratio (HR) for risk of hospitalization in PLWH was 2.44 (95% confidence interval [CI]: 2.04-2.94). In propensity score-weighted models that included all covariates, the relative risk of hospitalization was substantially attenuated in the overall analyses (adjusted HR [aHR]: 1.03; 95% CI: 0.85-1.25), in vaccinated (aHR 1.00; 95% CI: 0.69-1.45), inadequately vaccinated (aHR: 1.04; 95% CI: 0.76-1.41) and unvaccinated individuals (aHR: 1.15; 95% CI: 0.84-1.56).

Conclusion: PLWH had about two times the risk of COVID-19 hospitalization than HIV-negative individuals in crude analyses which attenuated in propensity score-weighted models. This suggests that the risk differential can be explained by sociodemographic factors and history of comorbidity, underscoring the need to address social and comorbid vulnerabilities (e.g., injecting drugs) that were more prominent among PLWH.

[Frontiers in Digital Health, 28 June 2023]

Background: The use of social media data provides an opportunity to complement traditional influenza and COVID-19 surveillance methods for the detection and control of outbreaks and informing public health interventions.

Objective: The first aim of this study is to investigate the degree to which Twitter users disclose health experiences related to influenza and COVID-19 that could be indicative of recent plausible influenza cases or symptomatic COVID-19 infections. Second, we seek to use the Twitter datasets to train and evaluate the classification performance of Bidirectional Encoder Representations from Transformers (BERT) and variant language models in the context of influenza and COVID-19 infection detection.

Methods: We constructed two Twitter datasets using a keyword-based filtering approach on English-language tweets collected from December 2016 to December 2022 in Saskatchewan, Canada. The influenza-related dataset comprised tweets filtered with influenza-related keywords from December 13, 2016, to March 17, 2018, while the COVID-19 dataset comprised tweets filtered with COVID-19 symptom-related keywords from January 1, 2020, to June 22, 2021. The Twitter datasets were cleaned, and each tweet was annotated by at least two annotators as to whether it suggested recent plausible influenza cases or symptomatic COVID-19 cases. We then assessed the classification performance of pre-trained transformer-based language models, including BERT-base, BERT-large, RoBERTa-base, RoBERT-large, BERTweet-base, BERTweet-covid-base, BERTweet-large, and COVID-Twitter-BERT (CT-BERT) models, on each dataset. To address the notable class imbalance, we experimented with both oversampling and undersampling methods.

Results: The influenza dataset had 1129 out of 6444 (17.5%) tweets annotated as suggesting recent plausible influenza cases. The COVID-19 dataset had 924 out of 11939 (7.7%) tweets annotated as inferring recent plausible COVID-19 cases. When compared against other language models on the COVID-19 dataset, CT-BERT performed the best, supporting the highest scores for recall (94.8%), F1(94.4%), and accuracy (94.6%). For the influenza dataset, BERTweet models exhibited better performance. Our results also showed that applying data balancing techniques such as oversampling or undersampling method did not lead to improved model performance.

Conclusions: Utilizing domain-specific language models for monitoring users’ health experiences related to influenza and COVID-19 on social media shows improved classification performance and has the potential to supplement real-time disease surveillance.

[Journal of Veterinary Diagnostic Investigation, 27 June 2023]

Surveillance for SARS-CoV-2 in American mink (Neovison vison) is a global priority because outbreaks on mink farms have potential consequences for animal and public health. Surveillance programs often focus on screening natural mortalities; however, significant knowledge gaps remain regarding sampling and testing approaches. Using 76 mink from 3 naturally infected farms in British Columbia, Canada, we compared the performance of 2 reverse-transcription real-time PCR (RT-rtPCR) targets (the envelope [E] and RNA-dependent RNA polymerase [RdRp] genes) as well as serology. We also compared RT-rtPCR and sequencing results from nasopharyngeal, oropharyngeal, skin, and rectal swabs, as well as nasopharyngeal samples collected using swabs and interdental brushes. We found that infected mink were generally RT-rtPCR–positive on all samples; however, Ct values differed significantly among sample types (nasopharyngeal < oropharyngeal < skin < rectal). There was no difference in the results of nasopharyngeal samples collected using swabs or interdental brushes. For most mink (89.4%), qualitative (i.e., positive vs. negative) serology and RT-rtPCR results were concordant. However, mink were positive on RT-rtPCR and negative on serology and vice versa, and there was no significant correlation between Ct values on RT-rtPCR and percent inhibition on serology. Both the E and RdRp targets were detectable in all sample types, albeit with a small difference in Ct values. Although SARS-CoV-2 RNA can be detected in multiple sample types, passive surveillance programs in mink should focus on multiple target RT-rtPCR testing of nasopharyngeal samples in combination with serology.

[Science of The Total Environment, 26 June 2023]

Wastewater-based surveillance (WBS) of infectious diseases is a powerful tool for understanding community COVID-19 disease burden and informing public health policy. The potential of WBS for understanding COVID-19's impact in non-healthcare settings has not been explored to the same degree. Here we examined how SARS-CoV-2 measured from municipal wastewater treatment plants (WWTPs) correlates with workforce absenteeism. SARS-CoV-2 RNA N1 and N2 were quantified three times per week by RT-qPCR in samples collected at three WWTPs servicing Calgary and surrounding areas, Canada (1.4 million residents) between June 2020 and March 2022. Wastewater trends were compared to workforce absenteeism using data from the largest employer in the city (>15,000 staff). Absences were classified as being COVID-19-related, COVID-19-confirmed, and unrelated to COVID-19. Poisson regression was performed to generate a prediction model for COVID-19 absenteeism based on wastewater data. SARS-CoV-2 RNA was detected in 95.5 % (85/89) of weeks assessed. During this period 6592 COVID-19-related absences (1896 confirmed) and 4524 unrelated absences COVID-19 cases were recorded. A generalized linear regression using a Poisson distribution was performed to predict COVID-19-confirmed absences out of the total number of absent employees using wastewater data as a leading indicator (P < 0.0001). The Poisson regression with wastewater as a one-week leading signal has an Akaike information criterion (AIC) of 858, compared to a null model (excluding wastewater predictor) with an AIC of 1895. The likelihood-ratio test comparing the model with wastewater signal with the null model shows statistical significance (P < 0.0001). We also assessed the variation of predictions when the regression model was applied to new data, with the predicted values and corresponding confidence intervals closely tracking actual absenteeism data. Wastewater-based surveillance has the potential to be used by employers to anticipate workforce requirements and optimize human resource allocation in response to trackable respiratory illnesses like COVID-19.

[CMAJ, 17 April 2023]

The term “lockdown” has become a powerful and perverted word in the infodemic about democracies’ responses to the COVID-19 pandemic. Lockdown, as used in public discourse, has expanded to include any public health measure, even if it places little to no restriction on social mobility or interaction. For example, a working literature review and meta-analysis on the effects of lockdowns on COVID-19 mortality misleadingly defined lockdowns as “the imposition of at least 1 compulsory non-pharmaceutical intervention.” This working paper therefore conflated mandatory isolation for people with confirmed infections and masking policies with heavy-handed limitations on freedom of movement, and since it gained viral fame, it has helped fuel calls for “no more lockdowns.” This working paper has been highly critiqued and is less convincing than comparative assessments of health measures, like the Oxford Stringency Index.

Here, we discuss the spread of misinformation on lockdowns and other public health measures, which we refer to as “lock-down revisionism,” and how this phenomenon has damaged trust in public health initiatives designed to keep people safer…

[Clinical Microbiology and Infection, 14 June 2023]

Single-nucleotide polymorphism (SNP)-PCR has been proposed as a rapid, reliable and complementary method to whole-genome sequencing (WGS) for SARS-CoV-2 surveillance. The advantages of SNP-PCR include the ability of front-line clinical laboratories to easily implement the method without additional instrumentation or bioinformatics, flexibility to edit or update the SNP-PCR as new SARS-CoV-2 variants of concern (VOC) emerge, and rapid turnaround time when needed for clinical management (e.g. determining the effectiveness of monoclonal antibody therapy or investigating prolonged infection versus re-infection). From a laboratory workflow and utilization perspective, SNP-PCR also allows WGS resources to be best reserved for atypical or newly emerging strains, whereas the SNP-PCR rapidly identifies the most common and predominant VOC. Currently, public health experts are calling for prompt testing to identify new cases of the latest emerging variants: XBB, XBB.1.5 and B.Q.1/B.Q.1.1.

Our clinical virology laboratory has performed SNP-PCR for SARS-CoV-2 subtyping on positive clinical samples weekly since January 2021, using various combinations of the commercially available VirSNiP assays (TIB Molbiol, Germany) and end-point hydrolysis probe PCR, validated with WGS (Illumina MiSeq). For all samples undergoing SNP-PCR, 500 μL underwent nucleic acid extraction using MagNA Pure 96 (Roche Molecular Systems Inc., USA) into 50 μL of eluate, followed by PCR amplification according to the manufacturer's protocols using LightCycler 480 (Roche). Our SNP-PCR algorithm has evolved many times over the course of the pandemic to incorporate new mutations reflecting the latest VOC (Table 1). As readers may currently seek to implement testing protocols in their own laboratories, we describe our previous SNP-PCR algorithms for Omicron variants and the design of a new SNP-PCR to differentiate XBB, XBB.1.5 and B.Q.1/B.Q.1.1 in a single well, which has not been previously described…

[BMJ Open, 12 June 2023]

Objective: To determine the SARS-CoV-2 seroprevalence among school workers within the Greater Vancouver area, British Columbia, Canada, after the first Omicron wave.

Design: Cross-sectional study by online questionnaire, with blood serology testing.

Setting: Three main school districts (Vancouver, Richmond and Delta) in the Vancouver metropolitan area.

Participants: Active school staff enrolled from January to April 2022, with serology testing between 27 January and 8 April 2022. Seroprevalence estimates were compared with data obtained from Canadian blood donors weighted over the same sampling period, age, sex and postal code distribution.

Primary and secondary outcomes: SARS-CoV-2 nucleocapsid antibody testing results adjusted for test sensitivity and specificity, and regional variation across school districts using Bayesian models.

Results: Of 1850 school staff enrolled, 65.8% (1214/1845) reported close contact with a COVID-19 case outside the household. Of those close contacts, 51.5% (625/1214) were a student and 54.9% (666/1214) were a coworker. Cumulative incidence of COVID-19 positive testing by self-reported nucleic acid or rapid antigen testing since the beginning of the pandemic was 15.8% (291/1845). In a representative sample of 1620 school staff who completed serology testing (87.6%), the adjusted seroprevalence was 26.5% (95% CrI 23.9% to 29.3%), compared with 32.4% (95% CrI 30.6% to 34.5%) among 7164 blood donors.

Conclusion: Despite frequent COVID-19 exposures reported, SARS-CoV-2 seroprevalence among school staff in this setting remained no greater than the community reference group. Results are consistent with the premise that many infections were acquired outside the school setting, even with Omicron.

[Human Vaccines & Immunotherapeutics, 8 June 2023]

Vaccine certificates have been implemented worldwide, aiming to promote vaccination rates and to reduce the spread of COVID-19. However, their use during the COVID-19 pandemic was controversial and has been criticized for infringing upon medical autonomy and individual rights. We administered a national online survey exploring social and demographic factors predicting the degree of public approval of vaccine certificates in Canada. We conducted a multivariate linear regression which revealed which factors were predictive of vaccine certificate acceptance in Canada. Self-reported minority status (p < .001), rurality (p < .001), political ideology (p < .001), age (p < .001), having children under 18 in the household (p < .001), education (p = .014), and income status (p = .034) were significant predictors of attitudes toward COVID-19 vaccine certificates. We observed the lowest vaccine-certificate approval among participants who: self-identify as a visible minority; live in rural areas; are politically conservative; are 18–34 years of age; have children under age 18 living in the household; have completed an apprenticeship or trades education; and those with an annual income between $100,000–$159,999. The present findings are valuable for their ability to inform the implementation of vaccine certificates during future pandemic scenarios which may require targeted communication between public health agencies and under-vaccinated populations.

[Clinical Microbiology, 8 June 2023]

The 50% plaque reduction neutralization assay (PRNT50) has been previously used to assess the neutralization capacity of donor plasma against wild-type and variant of concern (VOC) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Emerging data suggest that plasma with an anti-SARS-CoV-2 level of ≥2 × 104 binding antibody units/mL (BAU/mL) protects against SARS-CoV-2 Omicron BA.1 infection. Specimens were collected using a cross-sectional random sampling approach. For PRNT50 studies, 63 previously analyzed specimens by PRNT50 versus SARS-CoV-2 wild-type, Alpha, Beta, Gamma, and Delta were analyzed by PRNT50 versus Omicron BA.1. The 63 specimens plus 4,390 specimens (randomly sampled regardless of serological evidence of infection) were also tested using the Abbott SARS-CoV-2 IgG II Quant assay (anti-spike [S]; Abbott, Chicago, IL, USA; Abbott Quant assay). In the vaccinated group, the percentages of specimens with any measurable PRNT50 versus wild-type or VOC were wild type (21/25 [84%]), Alpha (19/25 [76%]), Beta (18/25 [72%]), Gamma (13/25 [52%]), Delta (19/25 [76%]), and Omicron BA.1 (9/25 [36%]). In the unvaccinated group, the percentages of specimens with any measurable PRNT50 versus wild type or VOC were wild-type SARS-CoV-2 (16/39 [41%]), Alpha (16/39 [41%]), Beta (10/39 [26%]), Gamma (9/39 [23%]), Delta (16/39 [41%]), and Omicron BA.1 (0/39) (Fisher's exact tests, vaccinated versus unvaccinated for each variant, P < 0.05). None of the 4,453 specimens tested by the Abbott Quant assay had a binding capacity of ≥2 × 104 BAU/mL. Vaccinated donors were more likely than unvaccinated donors to neutralize Omicron when assessed by a PRNT50 assay.

[Infectious Disease Modelling, 7 June 2023]

Monitoring of viral signal in wastewater is considered a useful tool for monitoring the burden of COVID-19, especially during times of limited availability in testing. Studies have shown that COVID-19 hospitalizations are highly correlated with wastewater viral signals and the increases in wastewater viral signals can provide an early warning for increasing hospital admissions. The association is likely nonlinear and time-varying. This project employs a distributed lag nonlinear model (DLNM) (Gasparrini et al., 2010) to study the nonlinear exposure-response delayed association of the COVID-19 hospitalizations and SARS-CoV-2 wastewater viral signals using relevant data from Ottawa, Canada. We consider up to a 15-day time lag from the average of SARS-CoV N1 and N2 gene concentrations to COVID-19 hospitalizations. The expected reduction in hospitalization is adjusted for vaccination efforts. A correlation analysis of the data verifies that COVID-19 hospitalizations are highly correlated with wastewater viral signals with a time-varying relationship. Our DLNM based analysis yields a reasonable estimate of COVID-19 hospitalizations and enhances our understanding of the association of COVID-19 hospitalizations with wastewater viral signals.

[PLoS One, 2 June 2023]

Objectives: We sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function.

Methods: This was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]).

Results: There were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (p<0.001). The EQ5D VAS significantly improved between 3 and 6 months for Class 1 (median difference of 6.0 [95% CI, 4.0 to 8.0]) and Class 3 (median difference of 5.0 [95% CI, 0 to 8.5]). There were no differences in DLCO between the classes.

Conclusions: There were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

[Current Opinion in Infectious Diseases, August 2023]

Purpose of review: This review summarizes the epidemiological evidence for respiratory personal protective equipment for SARA-CoV-2, a topic of considerable controversy.

Recent findings : The main findings are that the observational studies and non-coronavirus disease 2019 (COVID-19) randomized trials do not provide clear evidence that the N95 respirators offer superior protection over surgical masks. A randomized controlled trial on COVID-19 provides evidence that the absolute risk to healthcare workers over time using surgical masks is similar to N95 respirators.

Summary : The implications of the findings are that surgical masks and N95 respirators can be considered for respiratory protection in healthcare workers.

[JoGH, 26 May 2023]

The coronavirus 2019 (COVID-19) pandemic has significantly impacted the global economy and society. One of the key challenges in combating it was predicting its spread to take appropriate measures, such as lockdowns and social distancing. These measures have now been lifted, and many countries are entering the final stages of the COVID-19 pandemic.

It is essential to continue studying the data collected during the COVID-19 pandemic, even as the focus shifts to recovery and rebuilding, to improve our ability to respond to future pandemics and protect public health. The COVID-19 pandemic has provided a wealth of data that can be used to enhance our understanding of the virus and how it spreads. We used data from 3112 counties in the USA obtained from multiple sources, including the daily infection rates from the COVID-19 Data Repository of the Center for Systems Science and Engineering (CSSE) at the John Hopkins University [1], interventions used to control the spread of the virus [2], and demographics from the US Census [3], to train monitoring systems that detect and track future outbreaks or pandemics, allowing us to better prepare or even mitigate them in advance.

Artificial intelligence (AI) models have been used to forecast the cumulative daily number of COVID-19 cases. These models can analyse large amounts of data and make predictions quickly, which is critical in fast-moving pandemics. We built a forecasting model based on the temporal convolutional network (TCN) [4] and implemented a web application [5] that displays 28-day forecasts for every county in the United States. In our evaluation study, we found that our TCN-based model outperformed its extension (an ensemble model) and other state-of-art forecasting models…

[PNAS, 22 May 2023]

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection—for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we reanalyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same dataset reported shorter mean observed incubation period (3.2 d vs. 4.4 d) and serial interval (3.5 d vs. 4.1 d) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8 to 4.5 d) for both variants but a shorter mean generation interval for the Omicron variant (3.0 d; 95% CI: 2.7 to 3.2 d) than for the Delta variant (3.8 d; 95% CI: 3.7 to 4.0 d). The differences in estimated generation intervals may be driven by the “network effect”—higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.

[Health Care Management Science, 22 May 2023]

We applied a queuing model to inform ventilator capacity planning during the first wave of the COVID-19 epidemic in the province of British Columbia (BC), Canada. The core of our framework is a multi-class Erlang loss model that represents ventilator use by both COVID-19 and non-COVID-19 patients. Input for the model includes COVID-19 case projections, and our analysis incorporates projections with different levels of transmission due to public health measures and social distancing. We incorporated data from the BC Intensive Care Unit Database to calibrate and validate the model. Using discrete event simulation, we projected ventilator access, including when capacity would be reached and how many patients would be unable to access a ventilator. Simulation results were compared with three numerical approximation methods, namely pointwise stationary approximation, modified offered load, and fixed point approximation. Using this comparison, we developed a hybrid optimization approach to efficiently identify required ventilator capacity to meet access targets. Model projections demonstrate that public health measures and social distancing potentially averted up to 50 deaths per day in BC, by ensuring that ventilator capacity was not reached during the first wave of COVID-19. Without these measures, an additional 173 ventilators would have been required to ensure that at least 95% of patients can access a ventilator immediately. Our model enables policy makers to estimate critical care utilization based on epidemic projections with different transmission levels, thereby providing a tool to quantify the interplay between public health measures, necessary critical care resources, and patient access indicators.

[Genome Research, 22 May 2023]

The reconstruction of phylogenetic networks is an important but challenging problem in phylogenetics and genome evolution, as the space of phylogenetic networks is vast and cannot be sampled well. One approach to the problem is to solve the minimum phylogenetic network problem, in which phylogenetic trees are first inferred, and then the smallest phylogenetic network that displays all the trees is computed. The approach takes advantage of the fact that the theory of phylogenetic trees is mature, and there are excellent tools available for inferring phylogenetic trees from a large number of biomolecular sequences. A tree–child network is a phylogenetic network satisfying the condition that every nonleaf node has at least one child that is of indegree one. Here, we develop a new method that infers the minimum tree–child network by aligning lineage taxon strings in the phylogenetic trees. This algorithmic innovation enables us to get around the limitations of the existing programs for phylogenetic network inference. Our new program, named ALTS, is fast enough to infer a tree–child network with a large number of reticulations for a set of up to 50 phylogenetic trees with 50 taxa that have only trivial common clusters in about a quarter of an hour on average.

[Journal of Public Health Research, 12 May 2023]

Background: Public health surveillance data do not always capture all cases, due in part to test availability and health care seeking behaviour. Our study aimed to estimate under-ascertainment multipliers for each step in the reporting chain for COVID-19 in Toronto, Canada.

Design and methods: We applied stochastic modeling to estimate these proportions for the period from March 2020 (the beginning of the pandemic) through to May 23, 2020, and for three distinct windows with different laboratory testing criteria within this period.

Results: For each laboratory-confirmed symptomatic case reported to Toronto Public Health during the entire period, the estimated number of COVID-19 infections in the community was 18 (5th and 95th percentile: 12, 29). The factor most associated with under-reporting was the proportion of those who sought care that received a test.

Conclusions: Public health officials should use improved estimates to better understand the burden of COVID-19 and other similar infections.

[PLoS Computational Biology, 12 May 2023]

The outbreak of the severe acute respiratory syndrome coronavirus 2 started in Wuhan, China, towards the end of 2019 and spread worldwide. The rapid spread of the disease can be attributed to many factors including its high infectiousness and the high rate of human mobility around the world. Although travel/movement restrictions and other non-pharmaceutical interventions aimed at controlling the disease spread were put in place during the early stages of the pandemic, these interventions did not stop COVID-19 spread. To better understand the impact of human mobility on the spread of COVID-19 between regions, we propose a hybrid gravity-metapopulation model of COVID-19. Our modeling framework has the flexibility of determining mobility between regions based on the distances between the regions or using data from mobile devices. In addition, our model explicitly incorporates time-dependent human mobility into the disease transmission rate, and has the potential to incorporate other factors that affect disease transmission such as facemasks, physical distancing, contact rates, etc. An important feature of this modeling framework is its ability to independently assess the contribution of each factor to disease transmission. Using a Bayesian hierarchical modeling framework, we calibrate our model to the weekly reported cases of COVID-19 in thirteen local health areas in Metro Vancouver, British Columbia (BC), Canada, from July 2020 to January 2021. We consider two main scenarios in our model calibration: using a fixed distance matrix and time-dependent weekly mobility matrices. We found that the distance matrix provides a better fit to the data, whilst the mobility matrices have the ability to explain the variance in transmission between regions. This result shows that the mobility data provides more information in terms of disease transmission than the distances between the regions.

[JAMA Network Open, 18 April 2023]

Importance: SARS-CoV-2 infection may lead to acute and chronic sequelae. Emerging evidence suggests a higher risk of diabetes after infection, but population-based evidence is still sparse.

Objective: To evaluate the association between COVID-19 infection, including severity of infection, and risk of diabetes.

Design, Setting, and Participants: This population-based cohort study was conducted in British Columbia, Canada, from January 1, 2020, to December 31, 2021, using the British Columbia COVID-19 Cohort, a surveillance platform that integrates COVID-19 data with population-based registries and administrative data sets. Individuals tested for SARS-CoV-2 by real-time reverse transcription-polymerase chain reaction (RT-PCR) were included. Those who tested positive for SARS-CoV-2 (ie, those who were exposed) were matched on sex, age, and collection date of RT-PCR test at a 1:4 ratio to those who tested negative (ie, those who were unexposed). Analysis was conducted January 14, 2022, to January 19, 2023.

Exposure: SARS-CoV-2 infection.

Main Outcomes and Measures: The primary outcome was incident diabetes (insulin dependent or not insulin dependent) identified more than 30 days after the specimen collection date for the SARS-CoV-2 test with a validated algorithm based on medical visits, hospitalization records, chronic disease registry, and prescription drugs for diabetes management. Multivariable Cox proportional hazard modeling was performed to evaluate the association between SARS-CoV-2 infection and diabetes risk. Stratified analyses were performed to assess the interaction of SARS-CoV-2 infection with diabetes risk by sex, age, and vaccination status.

Results: Among 629 935 individuals (median [IQR] age, 32 [25.0-42.0] years; 322 565 females [51.2%]) tested for SARS-CoV-2 in the analytic sample, 125 987 individuals were exposed and 503 948 individuals were unexposed. During the median (IQR) follow-up of 257 (102-356) days, events of incident diabetes were observed among 608 individuals who were exposed (0.5%) and 1864 individuals who were not exposed (0.4%). The incident diabetes rate per 100 000 person-years was significantly higher in the exposed vs nonexposed group (672.2 incidents; 95% CI, 618.7-725.6 incidents vs 508.7 incidents; 95% CI, 485.6-531.8 incidents; P < .001). The risk of incident diabetes was also higher in the exposed group (hazard ratio [HR], 1.17; 95% CI, 1.06-1.28) and among males (adjusted HR, 1.22; 95% CI, 1.06-1.40). The risk of diabetes was higher among people with severe disease vs those without COVID-19, including individuals admitted to the intensive care unit (HR, 3.29; 95% CI, 1.98-5.48) or hospital (HR, 2.42; 95% CI, 1.87-3.15). The fraction of incident diabetes cases attributable to SARS-CoV-2 infection was 3.41% (95% CI, 1.20%-5.61%) overall and 4.75% (95% CI, 1.30%-8.20%) among males.

Conclusions and Relevance: In this cohort study, SARS-CoV-2 infection was associated with a higher risk of diabetes and may have contributed to a 3% to 5% excess burden of diabetes at a population level.

[The Journal of Infectious Diseases, 7 June 2022]

Background: Longer-term humoral responses to 2-dose coronavirus disease 2019 (COVID-19) vaccines remain incompletely characterized in people living with human immunodeficiency virus (HIV) (PLWH), as do initial responses to a third dose.

Methods: We measured antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein receptor-binding domain, angiotensin-converting enzyme 2 (ACE2) displacement, and viral neutralization against wild-type and Omicron strains up to 6 months after 2-dose vaccination, and 1 month after the third dose, in 99 PLWH receiving suppressive antiretroviral therapy and 152 controls.

Results: Although humoral responses naturally decline after 2-dose vaccination, we found no evidence of lower antibody concentrations or faster rates of antibody decline in PLWH compared with controls after accounting for sociodemographic, health, and vaccine-related factors. We also found no evidence of poorer viral neutralization in PLWH after 2 doses, nor evidence that a low nadir CD4+ T-cell count compromised responses. Post–third-dose humoral responses substantially exceeded post–second-dose levels, though Omicron-specific responses were consistently weaker than responses against wild-type virus. Nevertheless, post–third-dose responses in PLWH were comparable to or higher than controls. An mRNA-1273 third dose was the strongest consistent correlate of higher post–third-dose responses.

Conclusion: PLWH receiving suppressive antiretroviral therapy mount strong antibody responses after 2- and 3-dose COVID-19 vaccination. Results underscore the immune benefits of third doses in light of Omicron

[International Journal of Drug Policy, 17 April 2023]

Background: In Montreal (Canada), high hepatitis C virus (HCV) seroincidence (21 per 100 person-years in 2017) persists among people who have injected drugs (PWID) despite relatively high testing rates and coverage of needle and syringe programs (NSP) and opioid agonist therapy (OAT). We assessed the potential of interventions to achieve HCV elimination (80% incidence reduction and 65% reduction in HCV-related mortality between 2015 and 2030) in the context of COVID-19 disruptions among all PWID and PWID living with HIV.

Methods: Using a dynamic model of HCV-HIV co-transmission, we simulated increases in NSP (from 82% to 95%) and OAT (from 33% to 40%) coverage, HCV testing (every 6 months), or treatment rate (100 per 100 person-years) starting in 2022 among all PWID and PWID living with HIV. We also modeled treatment scale-up among active PWID only (i.e., people who report injecting in the past six months). We reduced intervention levels in 2020–2021 due to COVID-19-related disruptions. Outcomes included HCV incidence, prevalence, and mortality, and proportions of averted chronic HCV infections and deaths.

Results: COVID-19-related disruptions could have caused temporary rebounds in HCV transmission. Further increasing NSP/OAT or HCV testing had little impact on incidence. Scaling-up treatment among all PWID achieved incidence and mortality targets among all PWID and PWID living with HIV. Focusing treatment on active PWID could achieve elimination, yet fewer projected deaths were averted (36% versus 48%).

Conclusions: HCV treatment scale-up among all PWID will be required to eliminate HCV in high-incidence and prevalence settings. Achieving elimination by 2030 will entail concerted efforts to restore and enhance pre-pandemic levels of HCV prevention and care.

[eLife, 4 April 2023]

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, approx ⅔ were plausibly introduced into these animal species from local human populations, while the remaining approx ⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.

[Pediatrics, 3 March 2023]

OBJECTIVES: This study aimed to provide real-world evidence on coronavirus disease 2019 vaccine effectiveness (VE) against symptomatic infection and severe outcomes caused by Omicron in children aged 5 to 11 years.

METHODS: We used the test-negative study design and linked provincial databases to estimate BNT162b2 vaccine effectiveness against symptomatic infection and severe outcomes caused by Omicron in children aged 5 to 11 years between January 2 and August 27, 2022 in Ontario. We used multivariable logistic regression to estimate VE by time since the latest dose, compared with unvaccinated children, and we evaluated VE by dosing interval.

RESULTS: We included 6284 test-positive cases and 8389 test-negative controls. VE against symptomatic infection declined from 24% (95% confidence interval [CI], 8% to 36%) 14 to 29 days after a first dose and 66% (95% CI, 60% to 71%) 7 to 29 days after 2 doses. VE was higher for children with dosing intervals of ≥56 days (57% [95% CI, 51% to 62%]) than 15 to 27 days (12% [95% CI, −11% to 30%]) and 28 to 41 days (38% [95% CI, 28% to 47%]), but appeared to wane over time for all dosing interval groups. VE against severe outcomes was 94% (95% CI, 57% to 99%) 7 to 29 days after 2 doses and declined to 57% (95%CI, −20% to 85%) after ≥120 days.

CONCLUSIONS: In children aged 5 to 11 years, 2 doses of BNT162b2 provide moderate protection against symptomatic Omicron infection within 4 months of vaccination and good protection against severe outcomes. Protection wanes more rapidly for infection than severe outcomes. Overall, longer dosing intervals confer higher protection against symptomatic infection, however protection decreases and becomes similar to shorter dosing interval starting 90 days after vaccination.

[International Journal of Infectious Diseases, 26 March 2023]

Since the emergence of the SARS-CoV-2 Omicron variant, multiple observational studies have reported negative vaccine effectiveness (VE) against infection, symptomatic infection, and even severity (hospitalization), potentially leading to an interpretation that vaccines were facilitating infection and disease. However, current observations of negative VE likely stem from the presence of various biases (e.g., exposure differences, testing differences). Although negative VE is more likely to arise when true biological efficacy is generally low and biases are large, positive VE measurements can also be subject to the same mechanisms of bias. In this perspective, we first outline the different mechanisms of bias that could lead to false-negative VE measurements and then discuss their ability to potentially influence other protection measurements. We conclude by discussing the use of suspected false-negative VE measurements as a signal to interrogate the estimates (quantitative bias analysis) and to discuss potential biases when communicating real-world immunity research.

[International Journal of Infectious Diseases, 24 March 2023]

Objectives: We aimed to estimate the rate of myocarditis after the messenger RNA (mRNA) COVID-19 booster vaccination by vaccine type, age, and sex.

Methods: We used data from the British Columbia COVID-19 Cohort, a population-based cohort surveillance platform. The exposure was a booster dose of an mRNA vaccine. The outcome was diagnosis of myocarditis during hospitalization or an emergency department visit within 7-21 days of booster vaccination.

Results: The overall rate of myocarditis was lower for the booster dose (6.41, 95% confidence interval [CI]: 3.50-10.75) than the second dose (17.97, 95% CI: 13.78-23.04); (Rate ratiobooster vs dose-2 = 0.34, 95% CI: 0.17-0.61). This difference was more apparent for the mRNA-1273 vaccine type. After the second dose, the myocarditis rate in males was significantly lower for BNT162b2 than mRNA-1273 overall and among those aged 18-39 years. In contrast, after the booster dose, no significant differences between myocarditis and vaccine type was observed overall or within the specific age groups among males or females.

Conclusion: Myocarditis after mRNA COVID-19 vaccines is a rare event. A lower absolute risk of myocarditis was observed after a booster dose of mRNA vaccine than the primary series second dose.

[Clinical Infectious Diseases, 28 October 2022]

Background: Social determinants of health (SDOH) have been associated with coronavirus disease 2019 (COVID-19) outcomes. We examined patterns in COVID-19–related mortality by SDOH and compared these patterns to those for non–COVID-19 mortality.

Methods: Residents of Ontario, Canada, aged ≥20 years were followed from 1 March 2020 to 2 March 2021. COVID-19–related death was defined as death within 30 days following or 7 days prior to a positive COVID-19 test. Area-level SDOH from the 2016 census included median household income; proportion with diploma or higher educational attainment; proportion essential workers, racially minoritized groups, recent immigrants, apartment buildings, and high-density housing; and average household size. We examined associations between SDOH and COVID-19–related mortality, and non-COVID-19 mortality using cause-specific hazard models.

Results: Of 11 810 255 individuals, we observed 3880 COVID-19–related deaths and 88 107 non–COVID-19 deaths. After accounting for demographics, baseline health, and other area-level SDOH, the following were associated with increased hazards of COVID-19–related death (hazard ratio [95% confidence interval]: lower income (1.30 [1.04–1.62]), lower educational attainment (1.27 [1.07–1.52]), higher proportions essential workers (1.28 [1.05–1.57]), racially minoritized groups (1.42 [1.08–1.87]), apartment buildings (1.25 [1.07–1.46]), and large vs medium household size (1.30 [1.12–1.50]). Areas with higher proportion racially minoritized groups were associated with a lower hazard of non–COVID-19 mortality (0.88 [0.84–0.92]).

Conclusions: Area-level SDOH are associated with COVID-19–related mortality after accounting for demographic and clinical factors. COVID-19 has reversed patterns of lower non–COVID-19 mortality among racially minoritized groups. Pandemic responses should include strategies to address disproportionate risks and inequitable coverage of preventive interventions associated with SDOH.

[Journal of Simulation, 20 March 2023]

In this study, we present a hybrid agent-based model (ABM) and discrete event simulation (DES) framework where ABM captures the spread dynamics of COVID-19 via asymptomatic passengers and DES captures the impacts of environmental variables, such as service process capacity, on the results of different containment measures in a typical high-speed train station in China. The containment and control measures simulated include as-is (nothing changed) passenger flow control, enforcing social distancing, adherence level in face mask-wearing, and adding capacity to current service stations. These measures are evaluated individually and then jointly under a different initial number of asymptomatic passengers. The results show how some measures can consolidate the outcomes for each other, while combinations of certain measures could compromise the outcomes for one or the other due to unbalanced service process configurations. The hybrid ABM and DES models offer a useful multi-function simulation tool to help inform decision/policy makers of intervention designs and implementations for addressing issues like public health emergencies and emergency evacuations. Challenges still exist for the hybrid model due to the limited availability of simulation platforms, extensive consumption of computing resources, and difficulties in validation and optimisation.

[Policy Insights from the Behavioral and Brain Sciences, 15 March 2023]

Psychosocial factors are related to immune, viral, and vaccination outcomes. Yet, this knowledge has been poorly represented in public health initiatives during the COVID-19 pandemic. This review provides an overview of biopsychosocial links relevant to COVID-19 outcomes by describing seminal evidence about these associations known prepandemic as well as contemporary research conducted during the pandemic. This focuses on the negative impact of the pandemic on psychosocial health and how this in turn has likely consequences for critically relevant viral and vaccination outcomes. We end by looking forward, highlighting the potential of psychosocial interventions that could be leveraged to support all people in navigating a postpandemic world and how a biopsychosocial approach to health could be incorporated into public health responses to future pandemics.

[Open Forum Infectious Diseases, 9 February 2023]

Background: Longer-term immune response data after 3 doses of coronavirus disease 2019 (COVID-19) mRNA vaccine remain limited, particularly among older adults and after Omicron breakthrough infection.

Methods: We quantified wild-type- and Omicron-specific serum immunoglobulin (Ig)G levels, angiotensin-converting enzyme 2 displacement activities, and live virus neutralization up to 6 months after third dose in 116 adults aged 24–98 years who remained COVID-19 naive or experienced their first severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection during this time.

Results: Among the 78 participants who remained COVID-19 naive throughout follow up, wild-type- and Omicron-BA.1-specific IgG concentrations were comparable between younger and older adults, although BA.1-specific responses were consistently significantly lower than wild-type-specific responses in both groups. Wild-type- and BA.1-specific IgG concentrations declined at similar rates in COVID-19-naive younger and older adults, with median half-lives ranging from 69 to 78 days. Antiviral antibody functions declined substantially over time in COVID-19-naive individuals, particularly in older adults: by 6 months, BA.1-specific neutralization was undetectable in 96% of older adults, versus 56% of younger adults. Severe acute respiratory syndrome coronavirus 2 infection, experienced by 38 participants, boosted IgG levels and neutralization above those induced by vaccination alone. Nevertheless, BA.1-specific neutralization remained significantly lower than wild-type, with BA.5-specific neutralization lower still. Higher Omicron BA.1-specific neutralization 1 month after third dose was an independent correlate of lower SARS-CoV-2 infection risk.

Conclusions: Results underscore the immune benefits of the third COVID-19 mRNA vaccine dose in adults of all ages and identify vaccine-induced Omicron-specific neutralization as a correlate of protective immunity. Systemic antibody responses and functions however, particularly Omicron-specific neutralization, decline rapidly in COVID-19-naive individuals, particularly in older adults, supporting the need for additional booster doses.

[Clinical Infectious Diseases, 17 August 2022]

Background: A major goal of coronavirus disease 2019 (COVID-19) vaccination is to prevent severe outcomes (hospitalizations and deaths). We estimated the effectiveness of messenger RNA (mRNA) and ChAdOx1 COVID-19 vaccines against severe outcomes in 4 Canadian provinces between December 2020 and September 2021.

Methods: We conducted this multiprovincial, retrospective, test-negative study among community-dwelling adults aged ≥18 years in Ontario, Quebec, British Columbia, and Manitoba using linked provincial databases and a common study protocol. Multivariable logistic regression was used to estimate province-specific vaccine effectiveness against COVID-19 hospitalization and/or death. Estimates were pooled using random-effects models.

Results: We included 2 508 296 tested participants, with 31 776 COVID-19 hospitalizations and 5842 deaths. Vaccine effectiveness was 83% after a first dose and 98% after a second dose against both hospitalization and death (separately). Against severe outcomes, effectiveness was 87% (95% confidence interval [CI], 71%–94%) ≥84 days after a first dose of mRNA vaccine, increasing to 98% (95% CI, 96%–99%) ≥112 days after a second dose. Vaccine effectiveness against severe outcomes for ChAdOx1 was 88% (95% CI, 75%–94%) ≥56 days after a first dose, increasing to 97% (95% CI, 91%–99%) ≥56 days after a second dose. Lower 1-dose effectiveness was observed for adults aged ≥80 years and those with comorbidities, but effectiveness became comparable after a second dose. Two doses of vaccines provided very high protection for both homologous and heterologous schedules and against Alpha, Gamma, and Delta variants.

Conclusions: Two doses of mRNA or ChAdOx1 vaccine provide excellent protection against severe outcomes.

[medRxiv, 10 June 2023]

Background: Vaccine homophily describes non-heterogeneous vaccine uptake within contact networks. This study was performed to determine observable patterns of vaccine homophily, associations between vaccine homophily, self-reported vaccination, COVID-19 prevention behaviours, contact network size, and self-reported COVID-19, as well as the impact of vaccine homophily on disease transmission within and between vaccination groups under conditions of high and low vaccine efficacy.

Methods: Residents of British Columbia, Canada, aged ≥16 years, were recruited via online advertisements between February and March 2022, and provided information about vaccination status, perceived vaccination status of household and non-household contacts, compliance with COVID-19 prevention guidelines, and history of COVID-19. A deterministic mathematical model was used to assess transmission dynamics between vaccine status groups under conditions of high and low vaccine efficacy.

Results: Vaccine homophily was observed among the 1304 respondents, but was lower among those with fewer doses (p<0.0001). Unvaccinated individuals had larger contact networks (p<0.0001), were more likely to report prior COVID-19 (p<0.0001), and reported lower compliance with COVID-19 prevention guidelines (p<0.0001). Mathematical modelling showed that vaccine homophily plays a considerable role in epidemic growth under conditions of high and low vaccine efficacy. Further, vaccine homophily contributes to a high force of infection among unvaccinated individuals under conditions of high vaccine efficacy, as well as elevated force of infection from unvaccinated to vaccinated individuals under conditions of low vaccine efficacy.

Interpretation: The uneven uptake of COVID-19 vaccines and the nature of the contact network in the population play important roles in shaping COVID-19 transmission dynamics.

Citerank: (11) 679761Caroline ColijnDr. Caroline Colijn works at the interface of mathematics, evolution, infection and public health, and leads the MAGPIE research group. She joined SFU's Mathematics Department in 2018 as a Canada 150 Research Chair in Mathematics for Infection, Evolution and Public Health. She has broad interests in applications of mathematics to questions in evolution and public health, and was a founding member of Imperial College London's Centre for the Mathematics of Precision Healthcare.10019D3ABAB, 679814Jonathan DushoffProfessor in the Department Of Biology at McMaster University.10019D3ABAB, 679875Sarah OttoProfessor in Zoology. Theoretical biologist, Canada Research Chair in Theoretical and Experimental Evolution, and Killam Professor at the University of British Columbia.10019D3ABAB, 685445Michael WZ LiMichael Li is Senior Scientist in the Public Health Risk Science Division (PHRS) of the Public Health Agency of Canada (PHAC) and a Research Associate at the South African Centre for Epidemiological Modelling and Analysis (SACEMA).10019D3ABAB, 701023GenomicsWhile virus genomes can describe the global context of introductions and origins of local clusters of cases, CANMOD will focus on building methods for characterizing and modelling local transmission once it is established, and for surveillance for viral determinants of increased fitness and of enhanced risk of spillover, virulence and transmission.859FDEF6, 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 707634Gary Van DomselaarDr. Gary Van Domselaar, PhD (University of Alberta, 2003) is the Chief of the Bioinformatics Laboratory at the National Microbiology Laboratory in Winnipeg Canada, and Adjunct Professor in the Department of Medical Microbiology at the University of Manitoba.10019D3ABAB, 708734Genomics859FDEF6, 715277Covid-19Covid-19 » Relevance » Genomics10000FFFACD, 715329Nick OgdenNicholas Ogden is a senior research scientist and Director of the Public Health Risk Sciences Division within the National Microbiology Laboratory at the Public Health Agency of Canada.10019D3ABAB

[Canada Communicable Disease Report, 6 April 2022]

Genomic surveillance during the coronavirus disease 2019 (COVID-19) pandemic has been key to the timely identification of virus variants with important public health consequences, such as variants that can transmit among and cause severe disease in both vaccinated or recovered individuals. The rapid emergence of the Omicron variant highlighted the speed with which the extent of a threat must be assessed. Rapid sequencing and public health institutions’ openness to sharing sequence data internationally give an unprecedented opportunity to do this; however, assessing the epidemiological and clinical properties of any new variant remains challenging. Here we highlight a “band of four” key data sources that can help to detect viral variants that threaten COVID-19 management: 1) genetic (virus sequence) data; 2) epidemiological and geographic data; 3) clinical and demographic data; and 4) immunization data. We emphasize the benefits that can be achieved by linking data from these sources and by combining data from these sources with virus sequence data. The considerable challenges of making genomic data available and linked with virus and patient attributes must be balanced against major consequences of not doing so, especially if new variants of concern emerge and spread without timely detection and action.

[AIMS Mathematics, 10 January 2022]

Public opinion and opinion dynamics can have a strong effect on the transmission rate of an infectious disease for which there is no vaccine. The coupling of disease and opinion dynamics however, creates a dynamical system that is complex and poorly understood. We present a simple model in which susceptible groups adopt or give up prophylactic behaviour in accordance with the influence related to pro- and con-prophylactic communication. This influence varies with disease prevalence. We observe how the speed of the opinion dynamics affects the total size and peak size of the epidemic. We find that more reactive populations will experience a lower peak epidemic size, but possibly a larger final size and more epidemic waves, and that an increase in polarization results in a larger epidemic.

[arXiv, 11 August 2023]

Efficient coverage for newly developed vaccines requires knowing which groups of individuals will accept the vaccine immediately and which will take longer to accept or never accept. Of those who may eventually accept the vaccine, there are two main types: success-based learners, basing their decisions on others' satisfaction, and myopic rationalists, attending to their own immediate perceived benefit. We used COVID-19 vaccination data to fit a mechanistic model capturing the distinct effects of the two types on the vaccination progress. We estimated that 47 percent of Americans behaved as myopic rationalist with a high variations across the jurisdictions, from 31 percent in Mississippi to 76 percent in Vermont. The proportion was correlated with the vaccination coverage, proportion of votes in favor of Democrats in 2020 presidential election, and education score.

[Advanced Drug Delivery Reviews, 12 August 2023.]

Mucus is a biological hydrogel that coats and protects all non-keratinized wet epithelial surfaces. Mucins, the primary structural components of mucus, are critical components of the gel layer that protect against invading pathogens. For communicable diseases, pathogen-mucin interactions contribute to the pathogen’s fate and the potential for disease progression in-host, as well as the potential for onward transmission. We begin by reviewing in-host mucus filtering mechanisms, including size filtering and interaction filtering, which regulate the permeability of mucus barriers to all molecules including pathogens. Next, we discuss the role of mucins in communicable diseases at the point of transmission (i.e. how the encapsulation of pathogens in emitted mucosal droplets externally to hosts may modulate pathogen infectivity and viability). Overall, mucosal barriers modulate both host susceptibility as well as the dynamics of population-level disease transmission. The study of mucins and their use in models and experimental systems are therefore crucial for understanding the mechanistic biophysical principles underlying disease transmission and the early stages of host infection.

[Evolution, Medicine, and Public Health, 11 November 2022]

Objectives/aims: Prolonged infections of immunocompromised individuals have been proposed as a crucial source of new variants of SARS-CoV-2 during the COVID-19 pandemic. In principle, sustained within-host antigenic evolution in immunocompromised hosts could allow novel immune escape variants to emerge more rapidly, but little is known about how and when immunocompromised hosts play a critical role in pathogen evolution.

Materials and methods: Here, we use a simple mathematical model to understand the effects of immunocompromised hosts on the emergence of immune escape variants in the presence and absence of epistasis.

Conclusions: We show that when the pathogen does not have to cross a fitness valley for immune escape to occur (no epistasis), immunocompromised individuals have no qualitative effect on antigenic evolution (although they may accelerate immune escape if within-host evolutionary dynamics are faster in immunocompromised individuals). But if a fitness valley exists between immune escape variants at the between-host level (epistasis), then persistent infections of immunocompromised individuals allow mutations to accumulate, therefore, facilitating rather than simply speeding up antigenic evolution. Our results suggest that better genomic surveillance of infected immunocompromised individuals and better global health equality, including improving access to vaccines and treatments for individuals who are immunocompromised (especially in lower- and middle-income countries), may be crucial to preventing the emergence of future immune escape variants of SARS-CoV-2.

[BMC Genomic Data, 2 May 2023]

HostSeq was launched in April 2020 as a national initiative to integrate whole genome sequencing data from 10,000 Canadians infected with SARS-CoV-2 with clinical information related to their disease experience. The mandate of HostSeq is to support the Canadian and international research communities in their efforts to understand the risk factors for disease and associated health outcomes and support the development of interventions such as vaccines and therapeutics. HostSeq is a collaboration among 13 independent epidemiological studies of SARS-CoV-2 across five provinces in Canada. Aggregated data collected by HostSeq are made available to the public through two data portals: a phenotype portal showing summaries of major variables and their distributions, and a variant search portal enabling queries in a genomic region. Individual-level data is available to the global research community for health research through a Data Access Agreement and Data Access Compliance Office approval. Here we provide an overview of the collective project design along with summary level information for HostSeq. We highlight several statistical considerations for researchers using the HostSeq platform regarding data aggregation, sampling mechanism, covariate adjustment, and X chromosome analysis. In addition to serving as a rich data source, the diversity of study designs, sample sizes, and research objectives among the participating studies provides unique opportunities for the research community.

[medRxiv, 30 July 2023]

Two different epidemiological models of vaccination are commonly used in dynamical modeling studies. The leaky vaccination model assumes that all vaccinated individuals experience a reduced force of infection by the same amount. The polarized vaccination model assumes that some fraction of vaccinated individuals are completely protected, while the remaining fraction remains completely susceptible; this seemingly extreme assumption causes the polarized model to always predict lower final epidemic size than the leaky model under the same vaccine efficacy. However, the leaky model also makes an implicit, unrealistic assumption: vaccinated individuals who are exposed to infection but not infected remain just as susceptible as they were prior to exposures (i.e., independent of previous exposures). To resolve the independence assumption, we introduce an immune boosting mechanism, through which vaccinated, yet susceptible, individuals can gain protection without developing a transmissible infection. The boosting model further predicts identical epidemic dynamics as the polarized vaccination model, thereby bridging the differences between two models. We further develop a generalized vaccination model to explore how the assumptions of immunity affect epidemic dynamics and estimates of vaccine effectiveness.

Citerank: (22) 679703EIDM?The Emerging Infectious Diseases Modelling Initiative (EIDM) – by the Public Health Agency of Canada and NSERC – aims to establish multi-disciplinary network(s) of specialists across the country in modelling infectious diseases to be applied to public needs associated with emerging infectious diseases and pandemics such as COVID-19. [1]7F1CEB7, 679761Caroline ColijnDr. Caroline Colijn works at the interface of mathematics, evolution, infection and public health, and leads the MAGPIE research group. She joined SFU's Mathematics Department in 2018 as a Canada 150 Research Chair in Mathematics for Infection, Evolution and Public Health. She has broad interests in applications of mathematics to questions in evolution and public health, and was a founding member of Imperial College London's Centre for the Mathematics of Precision Healthcare.10019D3ABAB, 679769Christopher CottonChristopher Cotton is a Professor of Economics at Queen’s University where he holds the Jarislowsky-Deutsch Chair in Economic & Financial Policy.10019D3ABAB, 679776David EarnProfessor of Mathematics and Faculty of Science Research Chair in Mathematical Epidemiology at McMaster University.10019D3ABAB, 679797Huaiping ZhuProfessor of mathematics at the Department of Mathematics and Statistics at York University, a York Research Chair (YRC Tier I) in Applied Mathematics, the Director of the Laboratory of Mathematical Parallel Systems at the York University (LAMPS), the Director of the Canadian Centre for Diseases Modelling (CCDM) and the Director of the One Health Modelling Network for Emerging Infections (OMNI-RÉUNIS). 10019D3ABAB, 679806Jane HeffernanJane Heffernan is a professor of infectious disease modelling in the Mathematics & Statistics Department at York University. She is a co-director of the Canadian Centre for Disease Modelling, and she leads national and international networks in mathematical immunology and the modelling of waning and boosting immunity.10019D3ABAB, 679812Jianhong WuProfessor Jianhong Wu is a University Distinguished Research Professor and Senior Canada Research Chair in industrial and applied mathematics at York University. He is also the NSERC Industrial Research Chair in vaccine mathematics, modelling, and manufacturing. 10019D3ABAB, 679826Laura CowenAssociate Professor in the Department of Mathematics and Statistics at the University of Victoria.10019D3ABAB, 679842Mark LewisProfessor Mark Lewis, Kennedy Chair in Mathematical Biology at the University of Victoria and Emeritus Professor at the University of Alberta.10019D3ABAB, 679858Patrick BrownAssociate Professor in the Centre for Global Health Research at St. Michael’s Hospital, and in the Department of Statistical Sciences at the University of Toronto.10019D3ABAB, 679859Patrick LeightonPatrick Leighton is a Professor of Epidemiology and Public Health at the Faculty of Veterinary Medicine, University of Montreal, and an active member of the Epidemiology of Zoonoses and Public Health Research Group (GREZOSP) and the Centre for Public Health Research (CReSP). 10019D3ABAB, 679869Rob DeardonAssociate Professor in the Department of Production Animal Health in the Faculty of Veterinary Medicine and the Department of Mathematics and Statistics in the Faculty of Science at the University of Calgary.10019D3ABAB, 679875Sarah OttoProfessor in Zoology. Theoretical biologist, Canada Research Chair in Theoretical and Experimental Evolution, and Killam Professor at the University of British Columbia.10019D3ABAB, 679890Troy DayTroy Day is a Professor and the Associate Head of the Department of Mathematics and Statistics at Queen’s University. He is an applied mathematician whose research focuses on dynamical systems, optimization, and game theory, applied to models of infectious disease dynamics and evolutionary biology.10019D3ABAB, 679893Kumar MurtyProfessor Kumar Murty is in the Department of Mathematics at the University of Toronto. His research fields are Analytic Number Theory, Algebraic Number Theory, Arithmetic Algebraic Geometry and Information Security. He is the founder of the GANITA lab, co-founder of Prata Technologies and PerfectCloud. His interest in mathematics ranges from the pure study of the subject to its applications in data and information security.10019D3ABAB, 686724Ellen RaffertyDr. Ellen Rafferty has a Master of Public Health and a PhD in epidemiology and health economics from the University of Saskatchewan. Dr. Rafferty’s research focuses on the epidemiologic and economic impact of public health policies, such as estimating the cost-effectiveness of immunization programs. She is interested in the incorporation of economics into immunization decision-making, and to that aim has worked with a variety of provincial and national organizations.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 701071OSN – Publications144B5ACA0, 701222OMNI – Publications144B5ACA0, 704045Covid-19859FDEF6, 714608Charting a FutureCharting a Future for Emerging Infectious Disease Modelling in Canada – April 2023 [1] 2794CAE1, 715387SMMEID – Publications144B5ACA0

We propose an independent institute of emerging infectious disease modellers and policy experts, with an academic core, capable of renewing itself as needed. This institute will combine science and knowledge translation to inform decision-makers at all levels of government and ensure the highest level of preparedness (and readiness) for the next public health emergency. The Public Health Modelling Institute will provide cost-effective, science-based modelling for public policymakers in an easily visualizable, integrated framework, which can respond in an agile manner to changing needs, questions, and data. To be effective, the Institute must link to modelling groups within government, who are best able to pose questions and convey results for use by public policymakers.

[arXiv, 22 September 2022]

Maruotti et al. 2022 used a mark-recapture approach to estimate bounds on the true number of monkeypox infections in various countries. These approaches are fundamentally flawed; it is impossible to estimate undercounting based solely on a single stream of reported cases. Simulations based on a Richards curve for cumulative incidence show that, for reasonable epidemic parameters, the proposed methods estimate bounds on the ascertainment ratio of ≈0.2−0.5 roughly independently of the true ascertainment ratio. These methods should not be used.

Citerank: (11) 679746Steini BrownProfessor and Dean of the Dalla Lana School of Public Health at the University of Toronto.10019D3ABAB, 679755Ashleigh TuiteAshleigh Tuite is an Assistant Professor in the Epidemiology Division at the Dalla Lana School of Public Health at the University of Toronto.10019D3ABAB, 679757Beate SanderCanada Research Chair in Economics of Infectious Diseases and Director, Health Modeling & Health Economics and Population Health Economics Research at THETA (Toronto Health Economics and Technology Assessment Collaborative).10019D3ABAB, 679777David FismanI am a Professor in the Division of Epidemiology at Division of Epidemiology, Dalla Lana School of Public Health at the University of Toronto. I am a Full Member of the School of Graduate Studies. I also have cross-appointments at the Institute of Health Policy, Management and Evaluation and the Department of Medicine, Faculty of Medicine. I serve as a Consultant in Infectious Diseases at the University Health Network.10019D3ABAB, 679802Isaac BogochClinician Investigator, Toronto General Hospital Research Institute (TGHRI)10019D3ABAB, 679893Kumar MurtyProfessor Kumar Murty is in the Department of Mathematics at the University of Toronto. His research fields are Analytic Number Theory, Algebraic Number Theory, Arithmetic Algebraic Geometry and Information Security. He is the founder of the GANITA lab, co-founder of Prata Technologies and PerfectCloud. His interest in mathematics ranges from the pure study of the subject to its applications in data and information security.10019D3ABAB, 685230Doug ManuelDr. Manuel is a Medical Doctor with a Masters in Epidemiology and Royal College specialization in Public Health and Preventive Medicine. He is a Senior Scientist in the Clinical Epidemiology Program at Ottawa Hospital Research Institute, and a Professor in the Departments of Family Medicine and Epidemiology and Community Medicine.10019D3ABAB, 685420Hospitals16289D5D4, 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 715390Mortality859FDEF6

[Science Briefs of the Ontario COVID-19 Science Advisory Table, 29 March 2021]

Background: As of March 28, 2021 new variants of concern (VOCs) account for 67% of all Ontario SARS-CoV-2 infections. The B.1.1.7 variant originally detected in Kent, United Kingdom accounts for more than 90% of all VOCs in Ontario, with emerging evidence that it is both more transmissible and virulent.

Questions: What are the risks of COVID-19 hospitalization, ICU admission and death caused by VOCs as compared with the early variants of SARS-CoV-2?

What is the early impact of new VOCs on Ontario’s healthcare system?

Findings: A retrospective cohort study of 26,314 people in Ontario testing positive for SARS-CoV-2 between February 7 and March 11, 2021, showed that 9,395 people (35.7%) infected with VOCs had a 62% relative increase in COVID-19 hospitalizations (odds ratio [OR] 1.62, 95% confidence interval [CI] 1.41 to 1.87), a 114% relative increase in ICU admissions (OR 2.14, 95% CI 1.52 to 3.02), and a 40% relative increase in COVID-19 deaths (OR 1.40, 95% CI 1.01 to 1.94), after adjusting for age, sex and comorbidities.

A meta-analysis including the Ontario cohort study and additional cohort studies in the United Kingdom and Denmark showed that people infected with VOCs had a 63% higher risk of hospitalization (RR 1.63, 95% CI 1.44 to 1.83), a doubling of the risk of ICU admission (RR 2.03, 95% CI 1.69 to 2.45), and a 56% higher risk of all-cause death (RR 1.56, 95% CI 1.30 to 1.87). Estimates observed in different studies and regions were completely consistent, and the B.1.1.7 variant was dominant in all three jurisdictions over the study periods.

The number of people hospitalized with COVID-19 on March 28, 2021, is 21% higher than at the start of the province-wide lockdown during the second wave on December 26, 2020, while ICU occupancy is 28% higher.

Between December 14 to 20, 2020, there were 149 new admissions to ICU; people aged 59 years and younger accounted for 30% of admissions. Between March 15, 2021 and March 21, 2021, there were 157 new admissions to ICU; people aged 59 years and younger accounted for 46% of admissions.

Interpretation: The new VOCs will result in a considerably higher burden to Ontario’s health care system during the third wave compared to the impact of early SARS-CoV-2 variants during Ontario’s second wave.

Since the start of the third wave on March 1, 2021, the number of new cases of SARS-CoV-2 infection, and the COVID-19 hospital and ICU occupancies have surpassed prior thresholds at the start of the province-wide lockdown on December 26, 2020.

Citerank: (9) 679844Mathieu Maheu-GirouxCanada Research Chair (Tier 2) in Population Health Modeling and Associate Professor, McGill University.10019D3ABAB, 679880Sharmistha MishraSharmistha Mishra is an infectious disease physician and mathematical modeler and holds a Tier 2 Canadian Research Chair in Mathematical Modeling and Program Science.10019D3ABAB, 685203McMasterPandemicCompartmental epidemic models for forecasting and analysis of infectious disease pandemics: contributions from Ben Bolker, Jonathan Dushoff, David Earn, Weiguang Guan, Morgan Kain, Michael Li, Irena Papst, Steve Walker (in alphabetical order).122C78CB7, 685445Michael WZ LiMichael Li is Senior Scientist in the Public Health Risk Science Division (PHRS) of the Public Health Agency of Canada (PHAC) and a Research Associate at the South African Centre for Epidemiological Modelling and Analysis (SACEMA).10019D3ABAB, 701037MfPH – Publications144B5ACA0, 715290Steve WalkerSteve is the CANMOD Director of Data Science and a postdoctoral fellow in the Department of Mathematics and Statistics at McMaster University.10019D3ABAB, 715291macpan2McMasterPandemic was developed to provide forecasts and insights to Canadian public health agencies throughout the COVID-19 pandemic. The goal of this macpan2 project is to re-imagine McMasterPandemic, building it from the ground up with architectural and technological decisions that address the many lessons that we learned from COVID-19 about software.122C78CB7, 715329Nick OgdenNicholas Ogden is a senior research scientist and Director of the Public Health Risk Sciences Division within the National Microbiology Laboratory at the Public Health Agency of Canada.10019D3ABAB, 715667mpox859FDEF6

[Journal of Medical Virology, 6 December 2023]

The 2022 mpox outbreak predominantly impacted gay, bisexual, and other men who have sex with men (gbMSM). Two models were developed to support situational awareness and management decisions in Canada. A compartmental model characterized epidemic drivers at national/provincial levels, while an agent-based model (ABM) assessed municipal-level impacts of vaccination. The models were parameterized and calibrated using empirical case and vaccination data between 2022 and 2023. The compartmental model explored: (1) the epidemic trajectory through community transmission, (2) the potential for transmission among non-gbMSM, and (3) impacts of vaccination and the proportion of gbMSM contributing to disease transmission. The ABM incorporated sexual-contact data and modeled: (1) effects of vaccine uptake on disease dynamics, and (2) impacts of case importation on outbreak resurgence. The calibrated, compartmental model followed the trajectory of the epidemic, which peaked in July 2022, and died out in December 2022. Most cases occurred among gbMSM, and epidemic trajectories were not consistent with sustained transmission among non-gbMSM. The ABM suggested that unprioritized vaccination strategies could increase the outbreak size by 47%, and that consistent importation (≥5 cases per 10 000) is necessary for outbreak resurgence. These models can inform time-sensitive situational awareness and policy decisions for similar future outbreaks.

Citerank: (8) 679752Amy HurfordAmy Hurford is an Associate Professor jointly appointed in the Department of Biology and the Department of Mathematics and Statistics at Memorial University of Newfoundland and Labrador. 10019D3ABAB, 679805James WatmoughProfessor in the Department of Mathematics and Statistics at the University of New Brunswick.10019D3ABAB, 679817Julien ArinoProfessor and Faculty of Science Research Chair in Fundamental Science with the Department of Mathematics at the University of Manitoba.10019D3ABAB, 690185Brian GaasModeler in the Population and Public Health Evidence and Evaluation branch of the Department of Health and Social Services, Yukon government.10019D3ABAB, 701037MfPH – Publications144B5ACA0, 703963Mobility859FDEF6, 704045Covid-19859FDEF6, 715328Nonpharmaceutical Interventions (NPIs)859FDEF6

During the COVID-19 pandemic, some countries, such as Australia, China, Iceland, New Zealand, Thailand and Vietnam, successfully implemented an elimination strategy. Until June 2021, Atlantic Canada and Canada’s territories had also experienced prolonged periods with few SARS-CoV-2 community cases. Such regions had a need for epidemiological models that could assess the risk of SARS-CoV-2 outbreaks, but most existing frameworks are applicable to regions where SARS-CoV-2 is spreading in the community, and so it was necessary to adapt existing frameworks to meet this need. We distinguish between infections that are travel-related and those that occur in the community, and find that in Newfoundland and Labrador (NL), Nova Scotia, and Prince Edward Island the mean percentage of daily cases that were travel-related was 80% or greater (July 1, 2020 – May 31, 2021). We show that by December 24, 2021, the daily probability of an Omicron variant community outbreak establishing in NL was near one, and nearly twice as high as the previous high, which occurred in September 2021 when the Delta variant was dominant. We evaluate how vaccination and new variants might affect hypothetical future outbreaks in Mt. Pearl, NL. Our modelling framework can be used to evaluate alternative plans to relax public health restrictions when high levels of vaccination are achieved in regions that have implemented an elimination strategy.

[Nature Communications, 20 November 2023]

Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.

[Journal of Agricultural, Biological and Environmental Statistics, 16 November 2023]

The management of forest pests relies on an accurate understanding of the species’ phenology. Thermal performance curves (TPCs) have traditionally been used to model insect phenology. Many such models have been proposed and fitted to data from both wild and laboratory-reared populations. Using Hamiltonian Monte Carlo for estimation, we implement and fit an individual-level, Bayesian hierarchical model of insect development to the observed larval stage durations of a population reared in a laboratory at constant temperatures. This hierarchical model handles interval censoring and temperature transfers between two constant temperatures during rearing. It also incorporates individual variation, quadratic variation in development rates across insects’ larval stages, and “flexibility” parameters that allow for deviations from a parametric TPC. Using a Bayesian method ensures a proper propagation of parameter uncertainty into predictions and provides insights into the model at hand. The model is applied to a population of eastern spruce budworm (Choristoneura fumiferana) reared at 7 constant temperatures. Resulting posterior distributions can be incorporated into a workflow that provides prediction intervals for the timing of life stages under different temperature regimes. We provide a basic example for the spruce budworm using a year of hourly temperature data from Timmins, Ontario, Canada. Supplementary materials accompanying this paper appear on-line.

[Contemporary Clinical Trials Communications, 10 November 2023]

This short communication concerns a biomarker adaptive Phase 2/3 design for new oncology drugs with an uncertain biomarker effect. Depending on the outcome of an interim analysis for adaptive decision, a Phase 2 study that starts in a biomarker enriched subpopulation may continue to the end without expansion to Phase 3, expand to Phase 3 in the same population or expand to Phase 3 in a broader population. Each path can enjoy full alpha for hypothesis testing without inflating the overall Type I error.

[BMC Geriatrics, 9 November 2023]

Background: Prior studies have demonstrated the negative impact of language barriers on access, quality, and safety of healthcare, which can lead to health disparities in linguistic minorities. As the population ages, those with multiple chronic diseases will require increasing levels of home care and long-term services. This study described the levels of multimorbidity among recipients of home care in Ontario, Canada by linguistic group.

Methods: Population-based retrospective cohort of 510,685 adults receiving home care between April 1, 2010, to March 31, 2018, in Ontario, Canada. We estimated and compared prevalence and characteristics of multimorbidity (2 or more chronic diseases) across linguistic groups (Francophones, Anglophones, Allophones). The most common combinations and clustering of chronic diseases were examined. Logistic regression models were used to explore the main predictors of ‘severe’ multimorbidity (defined as the presence of five or more chronic diseases).

Results: The proportion of home care recipients with multimorbidity and severe multimorbidity was 92% and 44%, respectively. The prevalence of multimorbidity was slightly higher among Allophones (93.6%) than among Anglophones (91.8%) and Francophones (92.4%). However, Francophones had higher rates of cardiovascular and respiratory disease (64.9%) when compared to Anglophones (60.2%) and Allophones (61.5%), while Anglophones had higher rates of cancer (34.2%) when compared to Francophones (25.2%) and Allophones (24.3%). Relative to Anglophones, Allophones were more likely to have severe multimorbidity (adjusted OR = 1.04, [95% CI: 1.02–1.06]).

Conclusions: The prevalence of multimorbidity among Ontarians receiving home care services is high; especially for whose primary language is a language other than English or French (i.e., Allophones). Understanding differences in the prevalence and characteristics of multimorbidity across linguistic groups will help tailor healthcare services to the unique needs of patients living in minority linguistic situations.

[Infectious Agents and Cancer, 8 November 2023]

Background: Understanding the role of naturally acquired (i.e., infection-induced) human papillomavirus (HPV) antibodies against reinfection is important given the high incidence of this sexually transmitted infection. However, the protective effect of naturally acquired antibodies in terms of the level of protection, duration, and differential effect by sex remains incompletely understood. We conducted a systematic review and a meta-analysis to (1) strengthen the evidence on the association between HPV antibodies acquired through past infection and subsequent type-specific HPV detection, (2) investigate the potential influence of type-specific HPV antibody levels, and (3) assess differential effects by HIV status.

Methods: We searched Embase and Medline databases to identify studies which prospectively assessed the risk of type-specific HPV detection by baseline homologous HPV serostatus among unvaccinated individuals. Random-effect models were used to pool the measures of association of naturally acquired HPV antibodies against subsequent incident detection and persistent HPV positivity. Sources of heterogeneity for each type were assessed through subgroup analyses stratified by sex, anatomical site of infection, male sexual orientation, age group, and length of follow-up period. Evidence of a dose-response relationship of the association between levels of baseline HPV antibodies and type-specific HPV detection was assessed. Finally, we pooled estimates from publications reporting associations between HPV serostatus and type-specific HPV detection by baseline HIV status.

Results: We identified 26 publications (16 independent studies, with 62,363 participants) reporting associations between baseline HPV serostatus and incident HPV detection, mainly for HPV-16 and HPV-18, the most detected HPV type. We found evidence of protective effects of baseline HPV seropositivity and subsequent detection of HPV DNA (0.70, 95% CI 0.61–0.80, NE = 11) and persistent HPV positivity (0.65, 95% CI 0.42–1.01, NE = 5) mainly for HPV-16 among females, but not among males, nor for HPV-18. Estimates from 8 studies suggested a negative dose–response relationship between HPV antibody level and subsequent detection among females. Finally, we did not observe any differential effect by baseline HIV status due to the limited number of studies available.

Conclusion: We did not find evidence that naturally acquired HPV antibodies protect against subsequent HPV positivity in males and provide only modest protection among females for HPV-16. One potential limitation to the interpretation of these findings is potential misclassification biases due to different causes.

[Journal of Mathematical Biology, 6 November 2023]

Almost all models used in analysis of infectious disease outbreaks contain some notion of population size, usually taken as the census population size of the community in question. In many settings, however, the census population is not equivalent to the population likely to be exposed, for example if there are population structures, outbreak controls or other heterogeneities. Although these factors may be taken into account in the model: adding compartments to a compartmental model, variable mixing rates and so on, this makes fitting more challenging, especially if the population complexities are not fully known. In this work we consider the concept of effective population size in outbreak modelling, which we define as the size of the population involved in an outbreak, as an alternative to use of more complex models. Effective population size is an important quantity in genetics for estimation of genetic diversity loss in populations, but it has not been widely applied in epidemiology. Through simulation studies and application to data from outbreaks of COVID-19 in China, we find that simple SIR models with effective population size can provide a good fit to data which are not themselves simple or SIR.

[Science Advances, 3 November 2023]

The seasonal influenza (flu) vaccine is designed to protect against those influenza viruses predicted to circulate during the upcoming flu season, but identifying which viruses are likely to circulate is challenging. We use features from phylogenetic trees reconstructed from hemagglutinin (HA) and neuraminidase (NA) sequences, together with a support vector machine, to predict future circulation. We obtain accuracies of 0.75 to 0.89 (AUC 0.83 to 0.91) over 2016–2020. We explore ways to select potential candidates for a seasonal vaccine and find that the machine learning model has a moderate ability to select strains that are close to future populations. However, consensus sequences among the most recent 3 years also do well at this task. We identify similar candidate strains to those proposed by the World Health Organization, suggesting that this approach can help inform vaccine strain selection.

[Journal of Cancer Education, 3 November 2023]

Health systems are interested in increasing colorectal cancer (CRC) screening rates as CRC is a leading cause of preventable cancer death. Learning health systems are ones that use data to continually improve care. Data can and should include qualitative local perspectives to improve patient and provider education and care. This study sought to understand local perspectives on CRC screening to inform future strategies to increase screening rates across our integrated health system. Health insurance plan members who were eligible for CRC screening were invited to participate in semi-structured phone interviews. Qualitative content analysis was conducted using an inductive approach. Forty member interviews were completed and analyzed. Identified barriers included ambivalence about screening options (e.g., “If it had the same performance, I’d rather do home fecal sample test. But I’m just too skeptical [so I do the colonoscopy].”), negative prior CRC screening experiences, and competing priorities. Identified facilitators included a positive general attitude towards health (e.g., “I’m a rule follower. There are certain things I’ll bend rules. But certain medical things, you just got to do.”), social support, a perceived risk of developing CRC, and positive prior CRC screening experiences. Study findings were used by the health system leaders to inform the selection of CRC screening outreach and education strategies to be tested in a future simulation model. For example, the identified barrier related to ambivalence about screening options led to a proposed revision of outreach materials that describe screening types more clearly.

[BMJ Open, 2 November 2023]

Introduction: There are limited data on the longitudinal impact of Lyme disease. Predictors of recovery have not been fully established using validated data collection instruments. There are sparse data on the immunological response to infection over time.

Methods and analysis: This study is a longitudinal cohort study that will recruit 120 participants with Lyme disease in Ontario and Nova Scotia, Canada, with follow-up for up to 24 months. Data will be collected using the Short-Form 36 physical and mental component summaries, Depression and Anxiety Severity Scale Questionnaire, Fatigue Severity Scale and a battery of neuropsychological tests. Mononuclear cells, gene expression and cytokine profiling from blood samples will be used to assess immunological response. Analyses will include the use of non-linear mixed-effects modelling and proportional hazards models.

Ethics and dissemination: Ethics approval has been obtained from ethics boards at McMaster University (Hamilton Integrated Research Ethics Board) (7564), Queens University (EMD 315-20) and Nova Scotia Health Research Ethics Board (1027173), and the study is enrolling participants. Written informed consent is obtained from all participants. The results will be disseminated by publication in a peer-reviewed journal and presented at a relevant conference. A brief report will be provided to decision-makers and patient groups.

[Journal of the International AIDS Society, 26 October 2023]

Introduction: People living with HIV (PLWH) and/or who inject drugs may experience lower vaccine effectiveness (VE) against SARS-CoV-2 infection.

Methods: A validated algorithm was applied to population-based, linked administrative datasets in the British Columbia COVID-19 Cohort (BCC19C) to ascertain HIV status and create a population of PLWH and matched HIV-negative individuals. The study population was limited to individuals who received an RT-PCR laboratory test for SARS-CoV-2 between 15 December 2020 and 21 November 2021 in BC, Canada. Any history of injection drug use (IDU) was ascertained using a validated administrative algorithm. We used a test-negative study design (modified case−control analysis) and multivariable logistic regression to estimate adjusted VE by HIV status and history of IDU.

Results: Our analysis included 2700 PLWH and a matched population of 375,043 HIV-negative individuals, among whom there were 351 and 103,049 SARS-CoV-2 cases, respectively. The proportion of people with IDU history was much higher among PLWH compared to HIV-negative individuals (40.7% vs. 4.3%). Overall VE during the first 6 months after second dose was lower among PLWH with IDU history (65.8%, 95% CI = 43.5–79.3) than PLWH with no IDU history (80.3%, 95% CI = 62.7–89.6), and VE was particularly low at 4–6 months (42.4%, 95% CI = −17.8 to 71.8 with IDU history vs. 64.0%; 95% CI = 15.7–84.7 without), although confidence intervals were wide. In contrast, overall VE was 88.6% (95% CI = 88.2–89.0) in the matched HIV-negative population with no history of IDU and remained relatively high at 4–6 months after second dose (84.6%, 95% CI = 83.8–85.4). Despite different patterns of vaccine protection by HIV status and IDU history, peak estimates were similar (≥88%) across all populations.

Conclusions: PLWH with a history of IDU may experience lower VE against COVID-19 infection, although findings were limited by a small sample size. The lower VE at 4–6 months may have implications for booster dose prioritization for PLWH and people who inject drugs. The immunocompromising effect of HIV, substance use and/or co-occurring comorbidities may partly explain these findings.