Examining the effects of voluntary avoidance behaviour and policy-mediated behaviour change on the dynamics of SARS-CoV-2:A mathematical model  

作　　者：Gabrielle Brankston David N.Fisman Zvonimir Poljak Ashleigh R.Tuite Amy L.Greer 

机构地区：[1]Department of Population Medicine,University of Guelph,Canada [2]Dalla Lana School of Public Health,University of Toronto,Canada [3]Centre for Immunization Readiness,Public Health Agency of Canada,Ottawa,Ontario,Canada

出　　处：《Infectious Disease Modelling》2024年第3期701-712,共12页传染病建模（英文）

基　　金：GB and AG are supported by the Canada Research Chairs program;DN and AT are supported by the Canadian Institutes for Health Research(CIHR);ZP is supported by the Natural Sciences and Engineering Research Council(NSERC);Funding to support data collection was provided by the Public Health Agency of Canada(PHAC),The National Collaborating Centre for Infectious Diseases(NCCID),and the University of Guelph.

摘　　要：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 self-protective 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.

关 键 词：Mathematical modelling COVID-19 SARS-CoV-2 Human behaviour 

分 类 号：R563.1[医药卫生—呼吸系统]