Population Attributable Mortality Associated with Respiratory Viruses in Ontario

Population Attributable Mortality Associated with Respiratory Viruses in Ontario | medRxiv Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search Population Attributable Mortality Associated with Respiratory Viruses in Ontario View ORCID Profile David N. Fisman , Alicia A. Grima , Natalie J. Wilson , Simran Mann , View ORCID Profile Ashleigh R. Tuite , Clara Eunyoung Lee doi: https://doi.org/10.64898/2025.12.27.25343084 David N. Fisman 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada MD MPH Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David N. Fisman For correspondence: david.fisman{at}utoronto.ca Alicia A. Grima 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada MPH PhD(c) Find this author on Google Scholar Find this author on PubMed Search for this author on this site Natalie J. Wilson 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada MPH PhD (c) Find this author on Google Scholar Find this author on PubMed Search for this author on this site Simran Mann 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada MPH Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashleigh R. Tuite 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada 2 Centre for Immunization Surveillance and Programs , Public Health Agency of Canada , Ottawa ON, Canada PhD MPH Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ashleigh R. Tuite Clara Eunyoung Lee 1 Dalla Lana School of Public Health, University of Toronto , Toronto ON, Canada MD PhD Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Data/Code Preview PDF Abstract Background Respiratory viruses are major contributors to population mortality, but cause-of-death coding undercounts their impact. Ecological regression models linking viral circulation to mortality fluctuations can address this limitation. Aim To estimate the population attributable fraction (PAF) of mortality associated with influenza A and B, respiratory syncytial virus (RSV), and SARS-CoV-2 in Ontario, Canada (1993–2025), and to characterize temporal changes in virus-attributable mortality across the pandemic transition. Methods We analysed monthly all-cause mortality data with laboratory surveillance indicators for influenza A, B, RSV, and SARS-CoV-2. Negative binomial models with secular trends, Fourier seasonal terms, and population offsets were fit for pre-pandemic (January 1993–February 2020) and combined pandemic (March 2020–February 2025) periods. PAFs were derived from counterfactual predictions setting viral coefficients to zero. Sensitivity analyses examined temporal stratification of the pandemic period (Public Health Emergency of International Concern [PHEIC] period: March 2020–April 2023; post-PHEIC: May 2023–February 2025), exclusion of the early pandemic period (March–June 2020), and models without Fourier seasonal adjustment. Wald tests compared coefficients across specifications. Results Pre-pandemic, influenza A accounted for 1.8% (95% CI 1.4–2.3%) of mortality; influenza B showed no detectable impact. RSV demonstrated inverse associations in seasonally adjusted models but positive associations (PAF 1.9%, 95% CI 1.3–2.4%) without seasonal adjustment. Over the combined pandemic period (March 2020–February 2025; n=60 months), amid elevated baseline mortality (IRR 1.050, P=0.027), SARS-CoV-2 accounted for 6.1% (95% CI 4.2–8.0%) of deaths, approximately 4-fold the pre-pandemic influenza A burden, despite widespread vaccination and antiviral availability. Model-estimated SARS-CoV-2-attributable deaths closely matched reported COVID-19 deaths from Public Health Ontario over the same period. Temporal stratification identified a significant increase in SARS-CoV-2-attributable mortality in the post-PHEIC period (PAF 9.8%, 95% CI 1.1–17.7%; p=0.027), while post-PHEIC influenza A and B attributable fractions did not differ significantly from pre-pandemic baselines. Excluding March-June 2020 yielded a conservative SARS-CoV-2 PAF of 5.7% (95% CI 3.3–8.1%), confirming robustness of primary estimates. Meta-analyses showed substantial heterogeneity for influenza A (I²=92.8%) and RSV (I²=89.1%) across modeling approaches, but minimal heterogeneity for SARS-CoV-2 (I²=5.5%). Conclusion SARS-CoV-2 was associated with a 3–4-fold higher population mortality burden than seasonal influenza A despite available countermeasures. Post-PHEIC data suggest that the burden of respiratory virus mortality, including for influenza, has not returned to pre-pandemic levels, highlighting the continued importance of respiratory virus prevention strategies. Estimates for influenza A and RSV were sensitive to seasonal adjustment, highlighting the importance of modelling choices when quantifying virus-attributable mortality. Competing Interest Statement DNF has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus and Pfizer vaccines. 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. Other authors: no competing interests. Funding Statement The research was supported by a grant to DNF from the Canadians Institutes for Health Research (CIHR) (2019 COVID-19 rapid researching funding OV4-170360 and by CIHR project grant #518192). Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: All data used in this study were aggregate-level, with viral positivity data and monthly mortality being publicly available. All data and analysis code are available at https://github.com/fismanda/respiratory-virus-mortality-ontario (archived at https://zenodo.org/records/17887720 ). Approval for use of aggregate level, test-adjusted SARS-CoV-2 case counts was granted by the University of Toronto Research Ethics Board (Protocol # 41690). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov . I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Footnotes Competing Interest Statement DNF has served on advisory boards related to influenza and SARS-CoV-2 vaccines for Seqirus and Pfizer vaccines. 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. Other authors: no competing interests. The PDF is a revised and extended version of the original manuscript (DOCX). Key differences are as follows: Authorship. Simran Mann (MPH) has been added as a co-author. Extended time series. The study period extends through February 2025 (n=60 pandemic months), approximately one year beyond the original's March 2024 cutoff. PHEIC/post-PHEIC stratification. The central new contribution. The revision formally stratifies the pandemic period into PHEIC (March 2020 to April 2023) and post-PHEIC (May 2023 to February 2025) phases, finding a higher post-PHEIC SARS-CoV-2 PAF (9.8%, 95% CI 1.1 to 17.7%) with no evidence of a post-pandemic influenza mortality rebound. Revised primary PAF. The SARS-CoV-2 PAF is 6.1% (95% CI 4.2 to 8.0%), modestly lower than the original's 6.5% (95% CI 4.5 to 8.4%). Additional sensitivity analysis. An analysis excluding March to June 2020 (absent from the original) yields a conservative PAF of 5.7% (95% CI 3.3 to 8.1%). Meta-analysis, methods, and reporting. The forest plot incorporates PHEIC/post-PHEIC strata, methods detail is expanded, and the abstract, discussion, and reference list are updated accordingly. Ethics and Data Availability All data used in this study were aggregate-level, with viral positivity data and monthly mortality being publicly available. All data and analysis code are available at https://github.com/fismanda/respiratory-virus-mortality-ontario (archived at https://zenodo.org/records/19035861 ). Approval for use of aggregate level, test-adjusted SARS-CoV-2 case counts was granted by the University of Toronto Research Ethics Board (Protocol # 41690). Age-specific mortality attribution will be addressed in future work. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Back to top Previous Next Posted March 19, 2026. Download PDF Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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