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Though widely applied in other epidemiological fields, the case-cohort study design has seen little application in the field of vaccinology. Case-cohort studies use probabilistic sampling and reweighting to draw inferences about effects (in this case vaccine efficacy) at the population level in an efficient manner. The SARS-CoV-2 pandemic was met with high vaccine uptake, and high rates of population testing prior to the emergence of Omicron variants of concern, in Ontario, Canada, providing an ideal environment for application of case-cohort methodology. We combined a population-based case line list and vaccination database for the province of Ontario between December 2020 and October 2021. Risk of infection after vaccination was evaluated in all laboratory-confirmed vaccinated SARS-CoV-2 cases, and a 2 % sample of vaccinated controls, evaluated using survival analytic methods, including construction of Cox proportional hazards models. Vaccination status was treated as a time-varying covariate. First and second doses of SARS-CoV-2 vaccine markedly reduced risk of infection (first dose efficacy 68 %, 95 % CI 67 %-69 %; second dose efficacy 88 %, 95 % CI 87-88 %). In multivariable models, extended dosing intervals were associated with lowest risk of breakthrough infection (HR for redosing 0.64 (95 % CI 0.61-0.67) at 6-8 weeks). Heterologous vaccine schedules that mixed viral vector vaccine first doses with mRNA second doses were significantly more effective than mRNA only vaccines. Risk of infection largely vanished during the time period 4-6 months after the second vaccine dose, but rose markedly thereafter. We conclude that a case-cohort design provided an efficient means to identify strong protective effects associated with SARS-CoV-2 vaccination in real time, and also served to quantify the timing and magnitude of infection breakthrough risk in the same cohort. Heterologous vaccination and extended dosing intervals improved the durability of immune response., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Fisman reports financial support was provided by Canadian Institutes of Health Research. David Fisman reports a relationship with Pfizer Inc that includes: consulting or advisory. David Fisman reports a relationship with Seqirus Inc that includes: consulting or advisory. David Fisman reports a relationship with AstraZeneca Canada Inc that includes: consulting or advisory. David Fisman reports a relationship with Merck & Co Inc that includes: consulting or advisory. David Fisman reports a relationship with Sanofi Pasteur Inc that includes: consulting or advisory. David Fisman reports a relationship with Elementary Teachers’ Federation of Ontario that includes: paid expert testimony. David Fisman reports a relationship with Ontario Nurses’ Association that includes: paid expert testimony. Ashleigh Tuite reports a relationship with Public Health Agency of Canada that includes: employment. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Ltd.)

Background: We previously demonstrated that when vaccines prevent infection, the dynamics of mixing between vaccinated and unvaccinated sub-populations is such that use of imperfect vaccines markedly decreases risk for vaccinated people, and for the population overall. Risks to vaccinated people accrue disproportionately from contact with unvaccinated people. In the context of the emergence of Omicron SARS-CoV-2 and evolving understanding of SARS-CoV-2 epidemiology, we updated our analysis to evaluate whether our earlier conclusions remained valid., Methods: We modified a previously published Susceptible-Infectious-Recovered (SIR) compartmental model of SARS-CoV-2 with two connected sub-populations: vaccinated and unvaccinated, with non-random mixing between groups. Our expanded model incorporates diminished vaccine efficacy for preventing infection with the emergence of Omicron SARS-CoV-2 variants, waning immunity, the impact of prior immune experience on infectivity, "hybrid" effects of infection in previously vaccinated individuals, and booster vaccination. We evaluated the dynamics of an epidemic within each subgroup and in the overall population over a 10-year time horizon., Results: Even with vaccine efficacy as low as 20%, and in the presence of waning immunity, the incidence of COVID-19 in the vaccinated subpopulation was lower than that among the unvaccinated population across the full 10-year time horizon. The cumulative risk of infection was 3-4 fold higher among unvaccinated people than among vaccinated people, and unvaccinated people contributed to infection risk among vaccinated individuals at twice the rate that would have been expected based on the frequency of contacts. These findings were robust across a range of assumptions around the rate of waning immunity, the impact of "hybrid immunity", frequency of boosting, and the impact of prior infection on infectivity in unvaccinated people., Interpretation: Although the emergence of the Omicron variants of SARS-CoV-2 has diminished the protective effects of vaccination against infection with SARS-CoV-2, updating our earlier model to incorporate loss of immunity, diminished vaccine efficacy and a longer time horizon, does not qualitatively change our earlier conclusions. Vaccination against SARS-CoV-2 continues to diminish the risk of infection among vaccinated people and in the population as a whole. By contrast, the risk of infection among vaccinated people accrues disproportionately from contact with unvaccinated people., (Copyright: © 2024 Fisman et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., (© 2023 His Majesty the King in Right of Canada. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society. Reproduced with the permission of the Minister of Public Health Agency of Canada.)

The 50% plaque reduction neutralization assay (PRNT 50 ) 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 × 10 4 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 PRNT 50 studies, 63 previously analyzed specimens by PRNT 50 versus SARS-CoV-2 wild-type, Alpha, Beta, Gamma, and Delta were analyzed by PRNT 50 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 PRNT 50 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 PRNT 50 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 × 10 4 BAU/mL. Vaccinated donors were more likely than unvaccinated donors to neutralize Omicron when assessed by a PRNT 50 assay. IMPORTANCE SARS-CoV-2 Omicron emergence occurred in Canada during the period from November 2021 to January 2022. This study assessed the ability of donor plasma collected earlier (January to March 2021) to generate any neutralizing capacity against Omicron BA.1 SARS-CoV-2. Vaccinated individuals, regardless of infection status, were more likely to neutralize Omicron BA.1 than unvaccinated individuals. This study then used a semiquantitative binding antibody assay to screen a larger number of specimens (4,453) for individual specimens that might have high-titer neutralizing capacity against Omicron BA.1. None of the 4,453 specimens tested by the semiquantitative SARS-CoV-2 assay had a binding capacity suggestive of a high-titer neutralizing capacity against Omicron BA.1. These data do not imply that Canadians lacked immunity to Omicron BA.1 during the study period. Immunity to SARS-CoV-2 is complex, and there is still no wide consensus on correlation of protection to SARS-CoV-2., Competing Interests: The authors declare a conflict of interest. The following authors have no conflicts of interest: Sheila F. O’Brien, Qi-Long Yi, Ashleigh Tuite, Karen Colwill, Bhavisha Rathod, Kento T. Abe, and Yi-Chan J. Lin. Stated conflicts of interest are as follows. David H. Evans consults for, and holds research contracts from Tonix Pharmaceuticals, New York relating to the construction of COVID-19 vaccines. Support for the operations of the University of Alberta BSL3 facility was also received from the Li Ka Shing Institute of Virology, Canada Foundation for Innovation, and Alberta Innovates. Steven J. Drews has functioned as a content expert for respiratory viruses for Johnson & Johnson (Janssen) and has received funding in-kind from Abbott. Guillermo Orjuela and Ninette F. Robbins are current employees and shareholders of Abbott Laboratories. Anne-Claude Gingras has received research funds from a research contract with Providence Therapeutics Holdings, Inc for other projects.

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., (© 2023. The Author(s).)

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., Competing Interests: DNF has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus, Pfizer, AstraZeneca, and Sanofi-Pasteur Vaccines, and has served as a legal expert on issues related to COVID-19 epidemiology for the Elementary Teachers Federation of Ontario and the Registered Nurses Association of Ontario. ART was employed by the Public Health Agency of Canada when the research was conducted. The work does not represent the views of the Public Health Agency of Canada. This does not alter our adherence to PLOS ONE policies on sharing data and materials., (Copyright: © 2023 Simmons et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

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., Competing Interests: Potential conflicts of interest. D. N. F. has served on advisory boards related to influenza and severe acute respiratory syndrome coronavirus 2 vaccines for Seqirus, Pfizer, AstraZeneca, and Sanofi-Pasteur Vaccines and has served as a legal expert on issues related to coronavirus disease 2019 epidemiology for the Elementary Teachers Federation of Ontario and the Registered Nurses Association of Ontario. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.)

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., Competing Interests: Potential conflicts of interest. D. N. F. has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus, Pfizer, Astrazeneca, and Sanofi-Pasteur Vaccines, and has served as a legal expert on issues related to COVID-19 epidemiology for the Elementary Teachers Federation of Ontario and the Registered Nurses Association of Ontario. A. R. T. was employed by the Public Health Agency of Canada when this research was conducted. The work does not represent the views of the Public Health Agency of Canada. All other authors report no potential conflicts. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Infectious Diseases Society of America.)

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 (PRNT 50 ) assay to qualify convalescent plasma for clinical trials and virus-like particle (VLP) assays to validate PRNT 50 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 PRNT 50 . 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 × 10 3 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 (PRNT 50 ) 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.

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., (© The Author(s) 2022. Published by Oxford University Press for the Infectious Diseases Society of America.)

Our group has previously used laboratory and commercially developed assays to understand the IgG responses to SARS-CoV-2 antigens, including nucleocapsid (N), spike (S), and receptor binding domain (RBD), in Canadian blood donors. In this current study, we analyzed 17,428 available and previously characterized retention samples collected from April 2020 to March 2021. The analysis compared the characteristics of the Abbott SARS-CoV-2 IgG II Quant assay (Abbott anti-spike [S], Abbott, Chicago, IL) against four other IgG assays. The Abbott anti-S assay has a qualitative threshold of 50 AU/mL. The four comparator assays were the Abbott anti-nucleocapsid (N) assay and three commonly used Canadian in-house IgG enzyme-linked immunosorbent assays (ELISAs) recognizing distinct recombinant viral antigens, full-length spike glycoprotein, glycoprotein RBD, and nucleocapsid. The strongest qualitative relationship was between Sinai RBD and the Abbott anti-S assay (kappa, 0.707; standard error [SE] of kappa, 0.018; 95% confidence interval, 0.671 to 0.743). We then scored each previously characterized specimen as positive when two anti-SARS-COV-2 assays identified anti-SARS-CoV-2 IgG in the specimen. Using this composite reference standard approach, the sensitivity of the Abbott anti-S assay was 95.96% (95% confidence interval [CI], 93.27 to 97.63%). The specificity of the Abbott anti-S assay was 99.35% (95% CI, 99.21 to 99.46%). Our study provides context on the use of commonly used SARS-CoV-2 serologies in Canada and identifies how these assays qualitatively compare to newer commercial assays. Our next steps are to assess how well the Abbott anti-S assays quantitatively detect wild-type and SARS-CoV-2 variants of concern. IMPORTANCE We describe the qualitative test characteristics of the Abbott SARS-CoV-2 IgG II Quant assay against four other anti-SARS-CoV-2 IgG assays commonly used in Canada. Although there is no gold standard for identifying anti-SARS-CoV-2 seropositivity, aggregate standards can be used to assess seropositivity. In this study, we used a specimen bank of previously well-characterized specimens collected between April 2020 and March 2021. The Abbott anti-S assay showed the strongest qualitative relationship with a widely used laboratory-developed IgG assay for the SARS-CoV-2 receptor binding domain. Using the composite reference standard approach, we also showed that the Abbott anti-S assay was highly sensitive and specific. As new anti-SARS-CoV-2 assays are developed, it is important to compare their test characteristics against other assays that have been extensively used in prior research.

Background: The speed of vaccine development has been a singular achievement during the COVID-19 pandemic, although uptake has not been universal. Vaccine opponents often frame their opposition in terms of the rights of the unvaccinated. We sought to explore the impact of mixing of vaccinated and unvaccinated populations on risk of SARS-CoV-2 infection among vaccinated people., Methods: We constructed a simple susceptible-infectious-recovered compartmental model of a respiratory infectious disease with 2 connected subpopulations: people who were vaccinated and those who were unvaccinated. We simulated a spectrum of patterns of mixing between vaccinated and unvaccinated groups that ranged from random mixing to complete like-with-like mixing (complete assortativity), in which people have contact exclusively with others with the same vaccination status. We evaluated the dynamics of an epidemic within each subgroup and in the population as a whole., Results: We found that the risk of infection was markedly higher among unvaccinated people than among vaccinated people under all mixing assumptions. The contact-adjusted contribution of unvaccinated people to infection risk was disproportionate, with unvaccinated people contributing to infections among those who were vaccinated at a rate higher than would have been expected based on contact numbers alone. We found that as like-with-like mixing increased, attack rates among vaccinated people decreased from 15% to 10% (and increased from 62% to 79% among unvaccinated people), but the contact-adjusted contribution to risk among vaccinated people derived from contact with unvaccinated people increased., Interpretation: Although risk associated with avoiding vaccination during a virulent pandemic accrues chiefly to people who are unvaccinated, their choices affect risk of viral infection among those who are vaccinated in a manner that is disproportionate to the portion of unvaccinated people in the population., Competing Interests: Competing interests: David Fisman has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus, Pfizer, AstraZeneca and Sanofi-Pasteur Vaccines, and has served as a legal expert on issues related to COVID-19 epidemiology for the Elementary Teachers Federation of Ontario and the Registered Nurses Association of Ontario. He also served as a volunteer scientist on the Ontario COVID-19 Science Advisory Table. Ashleigh Tuite was employed by the Public Health Agency of Canada when the research was conducted. The work does not represent the views of the Public Health Agency of Canada. No other competing interests were declared., (© 2022 CMA Impact Inc. or its licensors.)

Background: As the largest city in Canada, Toronto has played an important role in the dynamics of SARS-CoV-2 transmission in Ontario, and the burden of disease across Toronto neighbourhoods has shown considerable heterogeneity. The purpose of this study was to investigate the spatial variation of sporadic SARS-CoV-2 cases in Toronto neighbourhoods by detecting clusters of increased risk and investigating effects of neighbourhood-level risk factors on rates., Methods: Data on sporadic SARS-CoV-2 cases, at the neighbourhood level, for Jan. 25 to Nov. 26, 2020, were obtained from the City of Toronto COVID-19 dashboard. We used a flexibly shaped spatial scan to detect clusters of increased risk of sporadic COVID-19. We then used a generalized linear geostatistical model to investigate whether average household size, population density, dependency ratio and prevalence of low-income households were associated with sporadic SARS-CoV-2 rates., Results: We identified 3 clusters of elevated risk of SARS-CoV-2 infection, with standardized morbidity ratios ranging from 1.59 to 2.43. The generalized linear geostatistical model found that average household size (relative risk [RR] 2.17, 95% confidence interval [CI] 1.80-2.61) and percentage of low-income households (RR 1.03, 95% CI 1.02-1.04) were significant predictors of sporadic SARS-CoV-2 cases at the neighbourhood level., Interpretation: During the study period, 3 clusters of increased risk of sporadic SARS-CoV-2 infection were identified, and average household size and percentage of low-income households were found to be associated with sporadic SARS-CoV-2 rates at the neighbourhood level. The findings of this study can be used to target resources and create policy to address inequities that are shown through heterogeneity of SARS-CoV-2 cases at the neighbourhood level in Toronto, Ontario., Competing Interests: Competing interests: Lindsay Obress reports student stipend support from the OVC Scholarships & Fellowships Program. David Fisman reports 2019 COVID-19 Rapid Research Funding (OV4-170360); payment or honoraria for serving on advisory boards for Pfizer, Seqirus, Sanofi and AstraZeneca vaccines; and payment for serving as a legal expert for the Ontario Nurses Association and Elementary Teachers’ Federation of Ontario. Amy Greer reports research funding from the Canada Research Chairs Program, COVID-19 research funding from the University of Guelph and the Public Health Agency of Canada (PHAC), consulting fees from the Ontario Secondary School Teachers’ Federation for serving as a scientific advisor related to epidemiology of COVID-19 in Ontario, unpaid work as an advisory board member on pandemic responsive design for Fabrik Architects Inc., unpaid work as a coauthor on “School Operation for the 2021–2022 Academic Year in the Context of the COVID-19 Pandemic” for the Ontario COVID-19 Science Advisory Table, unpaid work as an advisory board member for the National Collaborating Centre for Infectious Diseases, and unpaid work as a member of the PHAC Modelling Expert Advisory Group. No other competing interests were declared., (© 2022 CMA Impact Inc. or its licensors.)

We have previously used composite reference standards and latent class analysis (LCA) to evaluate the performance of laboratory assays in the presence of tarnished gold standards. Here, we apply these techniques to repeated, cross-sectional study of Canadian blood donors, whose sera underwent parallel testing with four separate SARS-CoV-2 antibody assays. We designed a repeated cross-sectional design with random cross-sectional sampling of all available retention samples ( n  = 1500/month) for a 12 -month period from April 2020 until March 2021. Each sample was evaluated for SARS-CoV-2 IgG antibodies using four assays an Abbott Architect assay targeting the nucleocapsid antigen (Abbott-NP, Abbott, Chicago IL) and three in-house IgG ELISAs recognizing distinct recombinant viral antigens: full-length spike glycoprotein (Spike), spike glycoprotein receptor binding domain (RBD) and nucleocapsid (NP). We used two analytic approaches to estimate SAR-CoV-2 seroprevalence: a composite reference standard and LCA. Using LCA to estimate true seropositivity status based on the results of the four antibody tests, we estimated that seroprevalence increased from 0.8% (95% CI: 0.5-1.4%) in April 2020 to 6.3% (95% CI: 5.1-7.6%) in March 2021. Our study provides further support for the use of LCA in upcoming public health crises, epidemics, and pandemics when a gold standard assay may not be available or identifiable. IMPORTANCE Here, we describe an approach to estimating seroprevalence in a low prevalence setting when multiple assays are available and yet no known gold standard exists. Because serological studies identify cases through both diagnostic testing and surveillance, and otherwise silent, unrecognized infections, serological data can be used to estimate the true infection fatality ratio of a disease. However, seroprevalence studies rely on assays with imperfect sensitivity and specificity. Seroreversion (loss of antibody response) also occurs over time, and with the advent of vaccination, distinction of antibody response resulting from vaccination as opposed to antibody response due to infection has posed an additional challenge. Our approach indicates that seroprevalence on Canadian blood donors by the end of March 2021was less than 10%. Our study supports the use of latent class analysis in upcoming public health crises, epidemics, and pandemics when a gold standard assay may not be available or identifiable.

Background: Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada., Methods: We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool-Outbreaks Near Me (ONM)-from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings., Results: Between 3,849-11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents., Interpretation: Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: IIB has consulted to BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. DNF reports personal consultant fees from Pfizer, AstraZeneca, and Seqirus, outside the submitted work. This does not alter our adherence to PLOS ONE policies on sharing data and materials

Background: This pilot study assesses the ability of plasma collected from Canadian blood donors in the first wave of the SARS-CoV-2 pandemic to neutralize later SARS-CoV-2 variants of concern (VOCs)., Study Design and Methods: A repeated cross-sectional design was used, and a random cross-sectional sample of all available Canadian Blood Services retention samples (n = 1500/month) was drawn monthly for April and May of 2020. Qualitative IgG analysis was performed on aliquots of specimens using anti-spike, anti-receptor binding domain, and anti-nucleocapsid protein enzyme-linked immunosorbent assays as well as the Abbott Architect SARS CoV-2 IgG assay (Abbott Laboratories) against the anti-nucleocapsid protein. Selected plasma specimens were then assessed for neutralization against VOCs using pseudotyped lentivirus inhibition assays as well as plaque reduction neutralization test 50% (PRNT 50 )., Results: Six specimens with a high neutralizing titer against wild-type SARS-CoV-2 and three specimens with a low neutralizing titer against wild-type SARS-CoV-2 were chosen for further analysis against VOCs. Four of six high neutralizing titer specimens had a reduced neutralizing capacity against beta VOCs by both neutralization methods. Three of six high neutralizing titer specimens had reduced neutralization capacity against gamma VOCs., Conclusions: This preliminary data can be used as a justification for limiting the use of first wave plasma products in upcoming clinical trials but cannot be used to speculate on general trends in the immunity of Canadian blood donors to SARS-CoV-2., (© 2021 The Authors. Transfusion published by Wiley Periodicals LLC on behalf of AABB.)

Background: A variety of public health measures have been implemented during the COVID-19 pandemic in Canada to reduce contact between individuals. The objective of this study was to provide empirical contact pattern data to evaluate the impact of public health measures, the degree to which social contacts rebounded to normal levels, as well as direct public health efforts toward age- and location-specific settings., Methods: Four population-based cross-sectional surveys were administered to members of a paid panel representative of Canadian adults by age, gender, official language, and region of residence during May (Survey 1), July (Survey 2), September (Survey 3), and December (Survey 4) 2020. A total of 4981 (Survey 1), 2493 (Survey 2), 2495 (Survey 3), and 2491 (Survey 4) respondents provided information about the age and setting for each direct contact made in a 24-h period. Contact matrices were constructed and contacts for those under the age of 18 years imputed. The next generation matrix approach was used to estimate the reproduction number (R t ) for each survey. Respondents with children under 18 years estimated the number of contacts their children made in school and extracurricular settings., Results: Estimated R t values were 0.49 (95% CI: 0.29-0.69) for May, 0.48 (95% CI: 0.29-0.68) for July, 1.06 (95% CI: 0.63-1.52) for September, and 0.81 (0.47-1.17) for December. The highest proportion of reported contacts occurred within the home (51.3% in May), in 'other' locations (49.2% in July) and at work (66.3 and 65.4% in September and December). Respondents with children reported an average of 22.7 (95% CI: 21.1-24.3) (September) and 19.0 (95% CI 17.7-20.4) (December) contacts at school per day per child in attendance., Conclusion: The skewed distribution of reported contacts toward workplace settings in September and December combined with the number of reported school-related contacts suggest that these settings represent important opportunities for transmission emphasizing the need to support and ensure infection control procedures in both workplaces and schools., (© 2021. The Author(s).)

Background: Between February and June 2021, the initial wild-type strains of SARS-CoV-2 were supplanted in Ontario, Canada, by new variants of concern (VOCs), first those with the N501Y mutation (i.e., Alpha/B1.1.17, Beta/B.1.351 and Gamma/P.1 variants) and then the Delta/B.1.617 variant. The increased transmissibility of these VOCs has been documented, but knowledge about their virulence is limited. We used Ontario's COVID-19 case data to evaluate the virulence of these VOCs compared with non-VOC SARS-CoV-2 strains, as measured by risk of hospitalization, intensive care unit (ICU) admission and death., Methods: We created a retrospective cohort of people in Ontario who tested positive for SARS-CoV-2 and were screened for VOCs, with dates of test report between Feb. 7 and June 27, 2021. We constructed mixed-effect logistic regression models with hospitalization, ICU admission and death as outcome variables. We adjusted models for age, sex, time, vaccination status, comorbidities and pregnancy status. We included health units as random intercepts., Results: Our cohort included 212 326 people. Compared with non-VOC SARS-CoV-2 strains, the adjusted elevation in risk associated with N501Y-positive variants was 52% (95% confidence interval [CI] 42%-63%) for hospitalization, 89% (95% CI 67%-117%) for ICU admission and 51% (95% CI 30%-78%) for death. Increased risk with the Delta variant was more pronounced at 108% (95% CI 78%-140%) for hospitalization, 235% (95% CI 160%-331%) for ICU admission and 133% (95% CI 54%-231%) for death., Interpretation: The increasing virulence of SARS-CoV-2 VOCs will lead to a considerably larger, and more deadly, pandemic than would have occurred in the absence of the emergence of VOCs., Competing Interests: Competing interests: David Fisman has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus, Pfizer, AstraZeneca and Sanofi-Pasteur, and has served as a legal expert on issues related to COVID-19 epidemiology for the Elementary Teachers Federation of Ontario and the Registered Nurses Association of Ontario. He was previously a member of the Ontario COVID-19 Modelling Consensus Table. Ashleigh Tuite serves on the Ontario COVID-19 Modelling Consensus Table., (© 2021 CMA Joule Inc. or its licensors.)

Background: Despite expected initial universal susceptibility to a novel pandemic pathogen like SARS-CoV-2, the pandemic has been characterized by higher observed incidence in older persons and lower incidence in children and adolescents., Objective: To determine whether differential testing by age group explains observed variation in incidence., Design: Population-based cohort study., Setting: Ontario, Canada., Participants: Persons diagnosed with SARS-CoV-2 and those tested for SARS-CoV-2., Measurements: Test volumes from the Ontario Laboratories Information System, number of laboratory-confirmed SARS-CoV-2 cases from the Integrated Public Health Information System, and population figures from Statistics Canada. Demographic and temporal patterns in incidence, testing rates, and test positivity were explored using negative binomial regression models and standardization. Sources of variation in standardized ratios were identified and test-adjusted standardized infection ratios (SIRs) were estimated by metaregression., Results: Observed disease incidence and testing rates were highest in the oldest age group and markedly lower in those younger than 20 years; no differences in incidence were seen by sex. After adjustment for testing frequency, SIRs were lowest in children and in adults aged 70 years or older and markedly higher in adolescents and in males aged 20 to 49 years compared with the overall population. Test-adjusted SIRs were highly correlated with standardized positivity ratios (Pearson correlation coefficient, 0.87 [95% CI, 0.68 to 0.95]; P  < 0.001) and provided a case identification fraction similar to that estimated with serologic testing (26.7% vs. 17.2%)., Limitations: The novel methodology requires external validation. Case and testing data were not linkable at the individual level., Conclusion: Adjustment for testing frequency provides a different picture of SARS-CoV-2 infection risk by age, suggesting that younger males are an underrecognized group at high risk for SARS-CoV-2 infection., Primary Funding Source: Canadian Institutes of Health Research.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence studies bridge the gap left from case detection, to estimate the true burden of the COVID-19 pandemic. While multiple anti-SARS-CoV-2 immunoassays are available, no gold standard exists., Methods: This serial cross-sectional study was conducted using plasma samples from 8999 healthy blood donors between April-September 2020. Each sample was tested by four assays: Abbott SARS-Cov-2 IgG assay, targeting nucleocapsid (Abbott-NP) and three in-house IgG ELISA assays (targeting spike glycoprotein, receptor binding domain, and nucleocapsid). Seroprevalence rates were compared using multiple composite reference standards and by a series of Bayesian Latent Class Models., Result: We found 13 unique diagnostic phenotypes; only 32 samples (0.4%) were positive by all assays. None of the individual assays resulted in seroprevalence increasing monotonically over time. In contrast, by using the results from all assays, the Bayesian Latent Class Model with informative priors predicted seroprevalence increased from 0.7% (95% credible interval (95% CrI); 0.4, 1.0%) in April/May to 0.7% (95% CrI 0.5, 1.1%) in June/July to 0.9% (95% CrI 0.5, 1.3) in August/September. Assay characteristics varied over time. Overall Spike had the highest sensitivity (93.5% (95% CrI 88.7, 97.3%), while the sensitivity of the Abbott-NP assay waned from 77.3% (95% CrI 58.7, 92.5%) in April/May to 64.4% (95% CrI 45.6, 83.0) by August/September., Discussion: Our results confirmed very low seroprevalence after the first wave in Canada. Given the dynamic nature of this pandemic, Bayesian Latent Class Models can be used to correct for imperfect test characteristics and waning IgG antibody signals., Competing Interests: Steven J Drews has acted as a content expert for respiratory viruses for Johnson & Johnson (Janssen). Anne-Claude Gingras receives funds from a research contract with Providence Therapeutics Holdings, Inc. The remaining authors have no conflicts of interest to disclose. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Competing Interests: Competing interest statement: D.N.F. serves on advisory boards of Seqirus, Sanofi Pasteur, Pfizer, and Astrazeneca vaccines, and consults for the Ontario Nurses Association, Elementary Teachers' Federation of Ontario, JP Morgan-Chase, WE Foundation, and Farallon Capital, outside the submitted work.

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public., (© 2021. The Author(s).)

Objectives: The effectiveness of public health interventions for mitigation of the COVID-19 pandemic depends on individual attitudes, compliance, and the level of support available to allow for compliance with these measures. The aim of this study was to describe attitudes and behaviours towards the Canadian COVID-19 public health response, and identify risk-modifying behaviours based on socio-demographic characteristics., Methods: A cross-sectional online survey was administered in May 2020 to members of a paid panel representative of the Canadian population by age, gender, official language, and region of residence. A total of 4981 respondents provided responses for indicators of self-reported risk perceptions, attitudes, and behaviours towards COVID-19 public health measures., Results: More than 90% of respondents reported confidence in the ability to comply with a variety of public health measures. However, only 51% reported preparedness for illness in terms of expectation to work if sick or access to paid sick days. Risk perceptions, attitudes, and behaviours varied by demographic variables. Men, younger age groups, and those in the paid workforce were less likely to consider public health measures to be effective, and had less confidence in their ability to comply. Approximately 80% of respondents reported that parents provided childcare and 52% reported that parents in the workforce provided childcare while schools were closed., Conclusion: Policies to help address issues of public adherence include targeted messaging for men and younger age groups, social supports for those who need to self-isolate, changes in workplace policies to discourage presenteeism, and provincially co-ordinated masking and safe school policies.

Competing Interests: IIB reports consulting for BlueDot, a social benefit corporation that tracks the spread of emerging infectious diseases. DNF reports personal fees from Pfizer, AstraZeneca, and Seqirus, outside the submitted work. This research was supported by the Department of Medicine COVID-19 Funding Opportunity, University of Toronto (LL-S). LL-S is supported by the University of Toronto, the Women's College Institute for Health System Solutions and Virtual Care, and The Peter Gilgan Centre for Women's Cancers at Women's College Hospital, in partnership with the Canadian Cancer Society. Acute Care Enhanced Surveillance is funded by the Ministry of Health and administrative support is provided by Kingston, Frontenac and Lennox & Addington Public Health. Data for this study were obtained from the Ontario Ministry of Health and Long-term Care as part of the province's emergency modelling table. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. All authors had full access to all the data in the study and had final responsibility for the decision to submit for publication.

Background: Throughout the SARS-CoV-2 pandemic, policymakers have had to navigate between recommending voluntary behaviour change and policy-driven behaviour change to mitigate the impact of the virus. While individuals will voluntarily engage in selfprotective behaviour when there is an increasing infectious disease risk, the extent to which this occurs and its impact on an epidemic is not known. Methods: This paper describes a deterministic disease transmission model exploring the impact of individual avoidance behaviour and policy-mediated avoidance behaviour on epidemic outcomes during the second wave of SARS-CoV-2 infections in Ontario, Canada (September 1, 2020 to February 28, 2021). The model incorporates an information feedback function based on empirically derived behaviour data describing the degree to which avoidance behaviour changed in response to the number of new daily cases COVID-19. Results: Voluntary avoidance behaviour alone was estimated to reduce the final attack rate by 23.1%, the total number of hospitalizations by 26.2%, and cumulative deaths by 27.5% over 6 months compared to a counterfactual scenario in which there were no interventions or avoidance behaviour. A provincial shutdown order issued on December 26, 2020 was estimated to reduce the final attack rate by 66.7%, the total number of hospitalizations by 66.8%, and the total number of deaths by 67.2% compared to the counterfactual scenario. Conclusion: Given the dynamics of SARS-CoV-2 in a pre-vaccine era, individual avoidance behaviour in the absence of government action would have resulted in a moderate reduction in disease however, it would not have been sufficient to entirely mitigate transmission and the associated risk to the population in Ontario. Government action during the second wave of the COVID-19 pandemic in Ontario reduced infections, protected hospital capacity, and saved lives. [ABSTRACT FROM AUTHOR]

Background: Vaccination has been a key part of Canada’s coronavirus disease 2019 (COVID-19) pandemic response. Although the clinical benefits of vaccination are clear, an understanding of the population-level benefits of vaccination relative to the programmatic costs is of value. The objective of this article is to quantify the economic impact of COVID-19 vaccination in the Canadian population between December 2020 and March 2022. Methods: We conducted a model-based cost-benefit analysis of Canada’s COVID-19 vaccination program. We used an epidemiological model to estimate the number of COVID-19 symptomatic cases, hospitalizations, post-COVID condition (PCC) cases, and deaths in the presence and absence of vaccination. Median, lower and upper 95% credible interval (95% CrI) outcome values from 100 model simulations were used to estimate the direct and indirect costs of illness, including the value of health. We used a societal perspective and a 1.5% discount rate. Results: We estimated that the costs of the vaccination program were far outweighed by the savings associated with averted infections and associated downstream consequences. Vaccination increased the net benefit by CAD $298.1 billion (95% CrI: 27.2–494.6) compared to the no vaccination counterfactual. The largest benefits were due to averted premature mortality, resulting in an estimated $222.0 billion (95% CrI: 31.2–379.0) benefit. Conclusion: Our model-based economic evaluation provides a retrospective assessment of COVID-19 vaccination during the first 16 months of the program in Canada and suggests that it was welfare-improving, considering the decreased hospitalizations and use of healthcare resources, deaths averted and lower morbidity from conditions such as PCC. [ABSTRACT FROM AUTHOR]

Background: Syndromic surveillance through web or phone-based polling has been used to track the course of infectious diseases worldwide. Our study objective was to describe the characteristics, symptoms, and self-reported testing rates of respondents in three different COVID-19 symptom surveys in Canada. Methods: This was a cross-sectional study using three distinct Canada-wide web-based surveys, and phone polling in Ontario. All three sources contained self-reported information on COVID-19 symptoms and testing. In addition to describing respondent characteristics, we examined symptom frequency and the testing rate among the symptomatic, as well as rates of symptoms and testing across respondent groups. Results: We found that over March- April 2020, 1.6% of respondents experienced a symptom on the day of their survey, 15% of Ontario households had a symptom in the previous week, and 44% of Canada-wide respondents had a symptom in the previous month. Across the three surveys, SARS-CoV-2-testing was reported in 2–9% of symptomatic responses. Women, younger and middle-aged adults (versus older adults) and Indigenous/First nations/Inuit/Métis were more likely to report at least one symptom, and visible minorities were more likely to report the combination of fever with cough or shortness of breath. Interpretation: The low rate of testing among those reporting symptoms suggests significant opportunity to expand testing among community-dwelling residents of Canada. Syndromic surveillance data can supplement public health reports and provide much-needed context to gauge the adequacy of SARS-CoV-2 testing rates. [ABSTRACT FROM AUTHOR]

Background: Physical-distancing interventions are being used in Canada to slow the spread of severe acute respiratory syndrome coronavirus 2, but it is not clear how effective they will be. We evaluated how different nonpharmaceutical interventions could be used to control the coronavirus disease 2019 (COVID-19) pandemic and reduce the burden on the health care system.Methods: We used an age-structured compartmental model of COVID-19 transmission in the population of Ontario, Canada. We compared a base case with limited testing, isolation and quarantine to scenarios with the following: enhanced case finding, restrictive physical-distancing measures, or a combination of enhanced case finding and less restrictive physical distancing. Interventions were either implemented for fixed durations or dynamically cycled on and off, based on projected occupancy of intensive care unit (ICU) beds. We present medians and credible intervals from 100 replicates per scenario using a 2-year time horizon.Results: We estimated that 56% (95% credible interval 42%-63%) of the Ontario population would be infected over the course of the epidemic in the base case. At the epidemic peak, we projected 107 000 (95% credible interval 60 760-149 000) cases in hospital (non-ICU) and 55 500 (95% credible interval 32 700-75 200) cases in ICU. For fixed-duration scenarios, all interventions were projected to delay and reduce the height of the epidemic peak relative to the base case, with restrictive physical distancing estimated to have the greatest effect. Longer duration interventions were more effective. Dynamic interventions were projected to reduce the proportion of the population infected at the end of the 2-year period and could reduce the median number of cases in ICU below current estimates of Ontario's ICU capacity.Interpretation: Without substantial physical distancing or a combination of moderate physical distancing with enhanced case finding, we project that ICU resources would be overwhelmed. Dynamic physical distancing could maintain health-system capacity and also allow periodic psychological and economic respite for populations. [ABSTRACT FROM AUTHOR]

Serial interval is the average time between cases in a chain of transmission and is used to calculate the number of generations in an epidemic (time since epidemic start ÷ serial interval duration). I Discussion: i Using a simple model of epidemic growth that includes the representation of control efforts can provide helpful insights into the growth of the 2019-nCoV epidemic that are not directly observable in publicly reported data. [Extracted from the article]

A recent publication in I CMAJ i [1] highlights the critical need for timely, accurate and accessible epidemiologic data for the ongoing coronavirus disease 2019 (COVID-19) outbreak to inform public health response efforts. Data sharing, standardization and visualization will continue to be crucial for supporting evidence-based control strategies and directing public health response efforts in Canada.[3] Footnotes 1 B Competing interests: b None declared. [Extracted from the article]