Background: Dual dose SARS-CoV-2 vaccines demonstrate high efficacy and will be critical in public health efforts to mitigate the COVID-19 pandemic and its health consequences; however, many jurisdictions face very constrained vaccine supply. We examined the impacts of extending the interval between two doses of mRNA vaccines in Canada in order to inform deliberations of Canada’s National Advisory Committee on Immunization.

Methods: We developed an age-stratified, deterministic, compartmental model of SARS-CoV-2 transmission and disease to reproduce the epidemiologic features of the epidemic in Canada. Simulated vaccination comprised mRNA vaccines with explicit examination of effectiveness against disease (67% [first dose], 94% [second dose]), hospitalization (80% [first dose], 96% [second dose]), and death (85% [first dose], 96% [second dose]) in adults aged 20 years and older. Effectiveness against infection was assumed to be 90% relative to the effectiveness against disease. We used a 6-week mRNA dose interval as our base case (consistent with early program rollout across Canadian and international jurisdictions) and compared extended intervals of 12 weeks, 16 weeks, and 24 weeks. We began vaccinations on January 1, 2021 and simulated a third wave beginning on April 1, 2021.

Results: Extending mRNA dose intervals were projected to result in 12.1-18.9% fewer symptomatic cases, 9.5-13.5% fewer hospitalizations, and 7.5-9.7% fewer deaths in the population over a 12-month time horizon. The largest reductions in hospitalizations and deaths were observed in the longest interval of 24 weeks, though benefits were diminishing as intervals extended. Benefits of extended intervals stemmed largely from the ability to accelerate coverage in individuals aged 20-74 years as older individuals were already prioritized for early vaccination. Conditions under which mRNA dose extensions led to worse outcomes included: first-dose effectiveness < 65% against death; or protection following first dose waning to 0% by month three before the scheduled 2nd dose at 24-weeks. Probabilistic simulations from a range of likely vaccine effectiveness values did not result in worse outcomes with extended intervals.

Conclusion: Under real-world effectiveness conditions, our results support a strategy of extending mRNA dose intervals across all age groups to minimize symptomatic cases, hospitalizations, and deaths while vaccine supply is constrained.

[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.

[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.

[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.

[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.

[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.

[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.

Citerank: (9) 679844Mathieu Maheu-GirouxCanada Research Chair (Tier 2) in Population Health Modeling and Associate Professor, McGill University.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, 701020CANMOD – PublicationsPublications by CANMOD Members144B5ACA0, 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.

[BMC Public Health, 20 October 2023]

Background: HIV programming in Ukraine largely targets “key population” groups. Men who purchase sex are not directly reached. The aim of our study was to explore the prevalence of sexually transmitted and blood-borne infections (STBBIs) among men who purchase sex from female sex workers.

Methods: Following geographic mapping and population size estimation at each “hotspot”, we conducted a cross-sectional bio-behavioural survey with men who purchase sex between September 2017 and March 2018 in Dnipro, Ukraine. Eligibility criteria included purchasing sex services at a “hotspot” and being ≥ 18 years. Participants completed a structured questionnaire, followed by HIV/HCV rapid testing and a dried blood spot (DBS) sample collection for confirmatory serology.

Results: The study enrolled 370 participants. The median age was 32 (interquartile range [IQR] = 27–38) and the median age of first purchase of sexual services was 22 (IQR = 19–27). Over half (56%) of participants reported ever testing for HIV; four participants (2%, N = 206) reported having tested positive for HIV, with three out of the four reporting being on ART. Forty percent of participants had ever tested for HCV, with three (2%, N = 142) having ever tested positive for HCV. In DBS testing, nine participants (2.4%) tested positive for HIV and 24 (6.5%) tested positive for ever having an HCV infection.

Conclusion: Prevalence of HIV and HCV in this population was high. Given high rates of study enrolment and testing, efforts should be made to reach men who purchase sex with expanded STBBI programming.

[Global Public Health, 18 October 2023]

Inferring HIV transmission networks from HIV sequences is gaining popularity in the field of HIV molecular epidemiology. However, HIV sequences are often analyzed at distance from those affected by HIV epidemics, namely without the involvement of communities most affected by HIV. These remote analyses often mean that knowledge is generated in absence of lived experiences and socio-economic realities that could inform the ethical application of network-derived information in ‘real world’ programmes. Procedures to engage communities are noticeably absent from the HIV molecular epidemiology literature. Here we present our team’s protocol for engaging community activists living in Nairobi, Kenya in a knowledge exchange process – The CIPHR Project (Community Insights in Phylogenetic HIV Research). Drawing upon a community-based participatory approach, our team will (1) explore the possibilities and limitations of HIV molecular epidemiology for key population programmes, (2) pilot a community-based HIV molecular study, and (3) co-develop policy guidelines on conducting ethically safe HIV molecular epidemiology. Critical dialogue with activist communities will offer insight into the potential uses and abuses of using such information to sharpen HIV prevention programmes. The outcome of this process holds importance to the development of policy frameworks that will guide the next generation of the global response.

[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.

[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.

[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.

[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 the International AIDS Society, 6 December 2023]

Introduction: HIV pre-exposure prophylaxis (PrEP) has been recommended and partly subsidized in Québec, Canada, since 2013. We evaluated the population-level impact of PrEP on HIV transmission among men who have sex with men (MSM) in Montréal, Québec's largest city, over 2013–2021.

Methods: We used an agent-based mathematical model of sexual HIV transmission to estimate the fraction of HIV acquisitions averted by PrEP compared to a counterfactual scenario without PrEP. The model was calibrated to local MSM survey, surveillance, and cohort data and accounted for COVID-19 pandemic impacts on sexual activity, HIV prevention, and care. PrEP was modelled from 2013 onwards, assuming 86% individual-level effectiveness. The PrEP eligibility criteria were: any anal sex unprotected by condoms (past 6 months) and either multiple partnerships (past 6 months) or multiple uses of post-exposure prophylaxis (lifetime). To assess potential optimization strategies, we modelled hypothetical scenarios prioritizing PrEP to MSM with high sexual activity (≥11 anal sex partners annually) or aged ⩽45 years, increasing coverage to levels achieved in Vancouver, Canada (where PrEP is free-of-charge), and improving retention.

Results: Over 2013–2021, the estimated annual HIV incidence decreased from 0.4 (90% credible interval [CrI]: 0.3–0.6) to 0.2 (90% CrI: 0.1–0.2) per 100 person-years. PrEP coverage among HIV-negative MSM remained low until 2015 (<1%). Afterwards, coverage increased to a maximum of 10% of all HIV-negative MSM, or about 16% of the 62% PrEP-eligible HIV-negative MSM in 2020. Over 2015–2021, PrEP averted an estimated 20% (90% CrI: 11%–30%) of cumulative HIV acquisitions. The hypothetical scenarios modelled showed that, at the same coverage level, prioritizing PrEP to high sexual activity MSM could have averted 30% (90% CrI: 19%–42%) of HIV acquisitions from 2015-2021. Even larger impacts could have resulted from higher coverage. Under the provincial eligibility criteria, reaching 10% coverage among HIV-negative MSM in 2015 and 30% in 2019, like attained in Vancouver, could have averted up to 63% (90% CrI: 54%–70%) of HIV acquisitions from 2015 to 2021.

Conclusions: PrEP reduced population-level HIV transmission among Montréal MSM. However, our study suggests missed prevention opportunities and adds support for public policies that reduce PrEP barriers, financial or otherwise, to MSM at risk of HIV acquisition.

[bioRxiv, 21 December 2023]

School closures were used as strategies to mitigate transmission in the COVID-19 pandemic. Understanding the nature of SARS-CoV-2 outbreaks and the distribution of infections in classrooms could help inform targeted or ‘precision’ preventive measures and outbreak management in schools, in response to future pandemics. In this work, we derive an analytical model of Probability Density Function (PDF) of SARS-CoV-2 secondary infections and compare the model with infection data from all public schools in Ontario, Canada between September-December, 2021. The model accounts for major sources of variability in airborne transmission like viral load and dose-response (i.e., the human body’s response to pathogen exposure), air change rate, room dimension, and classroom occupancy. Comparisons between reported cases and the modeled PDF demonstrated the intrinsic overdispersed nature of the real-world and modeled distributions, but uncovered deviations stemming from an assumption of homogeneous spread within a classroom. The inclusion of near-field transmission effects resolved the discrepancy with improved quantitative agreement between the data and modeled distributions. This study provides a practical tool for predicting the size of outbreaks from one index infection, in closed spaces such as schools, and could be applied to inform more focused mitigation measures.

[American Journal of Epidemiology, February 2024]

Transmissible infections such as those caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread according to who contacts whom. Therefore, many epidemic models incorporate contact patterns through contact matrices. Contact matrices can be generated from social contact survey data. However, the resulting matrices are often imbalanced, such that the total number of contacts reported by group A with group B do not match those reported by group B with group A. We examined the theoretical influence of imbalanced contact matrices on the estimated basic reproduction number (R0). We then explored how imbalanced matrices may bias model-based epidemic projections using an illustrative simulation model of SARS-CoV-2 with 2 age groups (<15 and ≥15 years). Models with imbalanced matrices underestimated the initial spread of SARS-CoV-2, had later time to peak incidence, and had smaller peak incidence. Imbalanced matrices also influenced cumulative infections observed per age group, as well as the estimated impact of an age-specific vaccination strategy. Stratified transmission models that do not consider contact balancing may generate biased projections of epidemic trajectory and the impact of targeted public health interventions. Therefore, modeling studies should implement and report methods used to balance contact matrices for stratified transmission models.

[BMC Infectious Diseases, 2 February 2024]

Background: Accurate estimation of SARS-CoV-2 re-infection is crucial to understanding the connection between infection burden and adverse outcomes. However, relying solely on PCR testing results in underreporting. We present a novel approach that includes longitudinal serologic data, and compared it against testing alone among people experiencing homelessness.

Methods: We recruited 736 individuals experiencing homelessness in Toronto, Canada, between June and September 2021. Participants completed surveys and provided saliva and blood serology samples every three months over 12 months of follow-up. Re-infections were defined as: positive PCR or rapid antigen test (RAT) results > 90 days after initial infection; new serologic evidence of infection among individuals with previous infection who sero-reverted; or increases in anti-nucleocapsid in seropositive individuals whose levels had begun to decrease.

Results: Among 381 participants at risk, we detected 37 re-infections through PCR/RAT and 98 re-infections through longitudinal serology. The comprehensive method identified 37.4 re-infection events per 100 person-years, more than four-fold more than the rate detected through PCR/RAT alone (9.0 events/100 person-years). Almost all test-confirmed re-infections (85%) were also detectable by longitudinal serology.

Conclusions: Longitudinal serology significantly enhances the detection of SARS-CoV-2 re-infections. Our findings underscore the importance and value of combining data sources for effective research and public health surveillance.

[Mathematics of Public Health, 7 August 2023]

Compartmental disease transmission models often stratify populations by factors such as risk, age, and geography. In such models, average rates of contact between each combination of population strata can be summarized as contact matrices. These matrices are key determinants of epidemic dynamics and intervention impact. In this chapter, we review the definition and application of contact matrices in compartmental transmission models. We explore different types of contacts and sources of data to support them, summarize key properties of contact matrices, examine the problem of restratifying contact matrices, and develop a method to incorporate age-stratified contact data and geographic mobility data. Throughout the chapter, we illustrate the concepts and methods discussed using a motivating example of developing contact matrices for SARS-CoV-2 transmission modelling. Overall, the chapter aims to be a practical introduction to contact matrices that will support the reader to construct and apply contact matrices in their own work.

[JMIR Public Health Surveillance, 27 August 2024]

Background: SARS-CoV-2 variants of concern (VOCs) emerged and rapidly replaced the original strain worldwide. The increased transmissibility of these new variants led to increases in infections, hospitalizations, and mortality. However, there is a scarcity of retrospective investigations examining the severity of all the main VOCs in presence of key public health measures and within various social determinants of health (SDOHs).

Objective: This study aims to provide a retrospective assessment of the clinical severity of COVID-19 VOCs in the context of heterogenous SDOHs and vaccination rollout.

Methods: We used a population-based retrospective cohort design with data from the British Columbia COVID-19 Cohort, a linked provincial surveillance platform. To assess the relative severity (hospitalizations, intensive care unit [ICU] admissions, and deaths) of Gamma, Delta, and Omicron infections during 2021 relative to Alpha, we used inverse probability treatment weighted Cox proportional hazard modeling. We also conducted a subanalysis among unvaccinated individuals, as assessed severity differed across VOCs and SDOHs.

Results: We included 91,964 individuals infected with a SARS-CoV-2 VOC (Alpha: n=20,487, 22.28%; Gamma: n=15,223, 16.55%; Delta: n=49,161, 53.46%; and Omicron: n=7093, 7.71%). Delta was associated with the most severe disease in terms of hospitalization, ICU admissions, and deaths (hospitalization: adjusted hazard ratio [aHR] 2.00, 95% CI 1.92-2.08; ICU: aHR 2.05, 95% CI 1.91-2.20; death: aHR 3.70, 95% CI 3.23-4.25 relative to Alpha), followed generally by Gamma and then Omicron and Alpha. The relative severity by VOC remained similar in the unvaccinated individual subanalysis, although the proportion of individuals infected with Delta and Omicron who were hospitalized was 2 times higher in those unvaccinated than in those fully vaccinated. Regarding SDOHs, the proportion of hospitalized individuals was higher in areas with lower income across all VOCs, whereas among Alpha and Gamma infections, 2 VOCs that cocirculated, differential distributions of hospitalizations were found among racially minoritized groups.

Conclusions: Our study provides robust severity estimates for all VOCs during the COVID-19 pandemic in British Columbia, Canada. Relative to Alpha, we found Delta to be the most severe, followed by Gamma and Omicron. This study highlights the importance of targeted testing and sequencing to ensure timely detection and accurate estimation of severity in emerging variants. It further sheds light on the importance of vaccination coverage and SDOHs in the context of pandemic preparedness to support the prioritization of allocation for resource-constrained or minoritized groups.

Citerank: (15) 679712CANMOD – PeopleCANMOD is a national network, with members located across the country and associated with a broader Emerging Infectious Disease Modelling (EIDM) initiative. We are a community of modellers, statisticians, epidemiologists, public health decision-makers, and those implementing and delivering interventions.10019D3ABAB, 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, 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, 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, 679775David BuckeridgeDavid is a Professor in the School of Population and Global Health at McGill University, where he directs the Surveillance Lab, an interdisciplinary group that develops, implements, and evaluates novel computational methods for population health surveillance. He is also the Chief Digital Health Officer at the McGill University Health Center where he directs strategy on digital transformation and analytics and he is an Associate Member with the Montreal Institute for Learning Algorithms (Mila).10019D3ABAB, 679776David EarnProfessor of Mathematics and Faculty of Science Research Chair in Mathematical Epidemiology at McMaster University.10019D3ABAB, 679844Mathieu Maheu-GirouxCanada Research Chair (Tier 2) in Population Health Modeling and Associate Professor, McGill University.10019D3ABAB, 679855Nathaniel OsgoodNathaniel D. Osgood is a Professor in the Department of Computer Science and Associate Faculty in the Department of Community Health & Epidemiology at the University of Saskatchewan.10019D3ABAB, 679856Naveed Zafar JanjuaDr. Naveed Zafar Janjua is an epidemiologist and senior scientist at the BC Centre for Disease Control and Clinical Associate Professor at School of Population and Public Health, University of British Columbia. Dr. Janjua is a Medical Doctor (MBBS) with a Masters of Science (MSc) degree in Epidemiology & Biostatistics and Doctorate in Public Health (DrPH). 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, 685387Michael Y LiProfessor of Mathematics in the Department of Mathematical and Statistical Sciences at the University of Alberta, and Director of the Information Research Lab (IRL).10019D3ABAB, 701020CANMOD – PublicationsPublications by CANMOD Members144B5ACA0, 701037MfPH – Publications144B5ACA0, 704045Covid-19859FDEF6, 728553Pandemic modeling questions?140D5CB99

[Canadian Journal of Public Health, 25 July 2024]

Setting: Mathematical modelling played an important role in the public health response to COVID-19 in Canada. Variability in epidemic trajectories, modelling approaches, and data infrastructure across provinces provides a unique opportunity to understand the factors that shaped modelling strategies.

Intervention: Provinces implemented stringent pandemic interventions to mitigate SARS-CoV-2 transmission, considering evidence from epidemic models. This study aimed to summarize provincial COVID-19 modelling efforts. We identified modelling teams working with provincial decision-makers, through referrals and membership in Canadian modelling networks. Information on models, data sources, and knowledge translation were abstracted using standardized instruments.

Outcomes: We obtained information from six provinces. For provinces with sustained community transmission, initial modelling efforts focused on projecting epidemic trajectories and healthcare demands, and evaluating impacts of proposed interventions. In provinces with low community transmission, models emphasized quantifying importation risks. Most of the models were compartmental and deterministic, with projection horizons of a few weeks. Models were updated regularly or replaced by new ones, adapting to changing local epidemic dynamics, pathogen characteristics, vaccines, and requests from public health. Surveillance datasets for cases, hospitalizations and deaths, and serological studies were the main data sources for model calibration. Access to data for modelling and the structure for knowledge translation differed markedly between provinces.

Implication: Provincial modelling efforts during the COVID-19 pandemic were tailored to local contexts and modulated by available resources. Strengthening Canadian modelling capacity, developing and sustaining collaborations between modellers and governments, and ensuring earlier access to linked and timely surveillance data could help improve pandemic preparedness.

[medRxiv, 31 January 2025]

Background: Empirical evidence on the indirect herd benefits of COVID-19 vaccination and/or prior infection is limited. We aimed to examine how area-level immunity interacts with individual-level immunity to affect COVID-19 diagnoses and deaths.

Methods: Ontario residents aged 18 years or older were followed from August-01-2021 to January-30-2022. Individual-level immunity was defined as received a primary series of COVID-19 vaccines or a positive SARS-CoV-2 test in the past 165 days. Area-level immunity was determined based on the proportion of immune individuals in an individuals residing area. We used logistic regression and cause-specific hazard models to examine the relationship between immunity and COVID-19 diagnosis, and between immunity and COVID-19 death, respectively. We included an interaction term between individual-level and area-level immunity in each model.

Results: Of 11,122,816 adults, 7,518,015 (67.6%) were immune at baseline. After accounting for individual-level demographics, baseline health, and area-level social determinants of health, area-level immunity (highest vs. lowest quintiles) was associated with lower odds of COVID-19 diagnosis; the association was larger among non-immune (odds ratios [95% confidence interval]: 0.72 [0.70, 0.75]) than immune individuals (0.93 [0.90, 0.96]). Higher area-level immunity (highest vs. lowest quintiles) was also associated with lower hazard of COVID-19 death among non-immune individuals (hazard ratio: 0.77 [0.60, 1.00]).

Conclusions: Our study provides observational evidence supporting the herd benefits of vaccination or prior infection on SARS-CoV-2 infections and COVID-19 deaths. Findings reinforce the need for high vaccination coverage to protect vaccinated and unvaccinated populations, while providing insights for interpreting vaccine effectiveness estimates in the context of herd immunity.

[International Journal of Infectious Diseases, 21 January 2025]

Objectives: The global mpox (clade II) outbreak of 2022 primarily affected gay, bisexual, and other men who have sex with men (GBM) and was met with swift community and public health responses. We aimed to estimate the relative impact of changes in sexual behaviours, contact tracing/isolation, and first-dose vaccination on transmission in Canadian cities.

Methods: We estimated changes in sexual behaviours during the outbreak using 2022 data from the Engage Cohort Study which recruited self-identified GBM in Montréal, Toronto, and Vancouver (n=1,445). We developed a transmission dynamic model to estimate the averted fraction of new infections attributable to the three interventions in each city.

Results: The empirical estimates of sexual behaviours changes were imprecise: 20% (RR=0.80; 95% credible intervals [95%CrI]: 0.47-1.36) fewer sexual partners in the past 6 months among those reporting ≤7 partners and 33% (RR=0.67; 95%CrI: 0.31-1.43) fewer among those with >7 partners. The three interventions combined averted 46%-58% of cases. Reductions in sexual partners, contact tracing/isolation prevented approximately 12% and 14% of cases, respectively. Vaccination's effect varied across cities by start date and coverage, with 21%-39% mpox infections prevented.

Conclusions: Reduction in sexual activity, contact tracing/isolation, and vaccination all contributed to accelerating epidemic control. Early vaccination had the largest impact.