[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.

[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.

Citerank: (7) 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, 701020CANMOD – PublicationsPublications by CANMOD Members144B5ACA0, 701037MfPH – Publications144B5ACA0

[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.