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School and Community Reopening During the COVID-19 Pandemic: A Mathematical Modeling Study

37 Pages Posted: 2 Feb 2021

See all articles by pei yuan

pei yuan

York University

Elena Aruffo

York University - Centre for Diseases Modeling (CDM)

Nicholas Ogden

Public Health Agency Canada - Public Health Risk Sciences Division

Evgenia Gatov

City of Toronto - Toronto Public Health

effie gournis

City of Toronto - Toronto Public Health

Sarah Collier

Toronto Public Health, City of Toronto

Qi Li

Department of Mathematics, Shanghai Normal University

Iain Moyles

York University - Centre for Diseases Modeling (CDM)

Nasri Bouchra

Department of Social and Preventive Medicine, Université de Montréal

Huaiping Zhu

York University - Centre for Diseases Modeling (CDM)

More...

Abstract

Background: The closure of communities, including schools, has been adopted to control the coronavirus disease 2019 (COVID-19) epidemic in most countries. Operating schools safely during the pandemic requires a balance between health risks and the need for in-person learning. We use compartmental models to explore school reopening scenarios.

Methods: Using demographic and epidemiological data between July 31 and November 23, 2020 from the city of Toronto, we developed a Susceptible-Exposed-Asymptomatic-Infectious-Recovered-Hospitalized-Isolated model. Our model with age, household, and community transmission allow us to study the impact of schools open in September 2020. The model mimics the transmission in households, the community, and schools, accounting for differences in infectiousness between adults and children and youth and adults' working status. We assessed the extent to which school opening may have contributed to COVID-19 resurgence in the fall and simulated scenarios for the safe reopening of schools up to May 31, 2021. We further considered the impact of the introduction of the new variant of concern.

Findings: Though a slight increase in infections among adults (2.8%) and children (5.4%) is anticipated by the end of the year, safe school opening is possible with stringent nonpharmaceutical interventions  (NPIs) decreasing the risk of transmission in the community and the household. We found that while school reopening was not the key driver in virus resurgence, but rather it was community spread that determined the outbreak trajectory, brief school closures did reduce infections when transmission risk within the home was low. When considered possible cross-infection amongst households, communities, and schools, we found that home transmission was crucial for mitigating the epidemic and safely operating schools. Simulating the introduction of a new strain with higher infectiousness, we observed substantial increases in infections, even when both schools and communities are closed.

Interpretatio: nSchools can open safely under strict maintenance of strict public health measures in the community. The gradual opening of schools and communities can only be achieved by maintaining NPIs and mitigating household transmission risk to avoid the broader escape of infections acquired in schools into the community via households. If the new COVID-19 strain is more infectious for children, public spaces, including schools, should be closed, and additional NPIs, including the use of masks, should be extended to toddlers.

Funding: This research was supported by Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada and York University Research Chair program.

Declaration of Interests: The authors declare no conflict of interest.

Keywords: COVID-19; school reopening; community opening; transmission model; household structure; age structure; household transmission; nonpharmaceutical interventions; workplaces reopen

Suggested Citation

yuan, pei and Aruffo, Elena and Ogden, Nicholas and Gatov, Evgenia and gournis, effie and Collier, Sarah and Li, Qi and Moyles, Iain and Bouchra, Nasri and Zhu, Huaiping, School and Community Reopening During the COVID-19 Pandemic: A Mathematical Modeling Study. Available at SSRN: https://ssrn.com/abstract=3766283 or http://dx.doi.org/10.2139/ssrn.3766283

Pei Yuan

York University

Elena Aruffo

York University - Centre for Diseases Modeling (CDM) ( email )

Canada

Nicholas Ogden

Public Health Agency Canada - Public Health Risk Sciences Division ( email )

Ontario
Canada

Evgenia Gatov

City of Toronto - Toronto Public Health ( email )

Effie Gournis

City of Toronto - Toronto Public Health ( email )

Sarah Collier

Toronto Public Health, City of Toronto

Qi Li

Department of Mathematics, Shanghai Normal University

Iain Moyles

York University - Centre for Diseases Modeling (CDM)

Canada

Nasri Bouchra

Department of Social and Preventive Medicine, Université de Montréal ( email )

Huaiping Zhu (Contact Author)

York University - Centre for Diseases Modeling (CDM)

Canada

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