Modeling the impact of school reopening and contact tracing strategies on COVID-19 dynamics in different epidemiologic settings in Brazil

Marcelo Eduardo Borges, Leonardo Souto Ferreira, Silas Poloni, Angela Maria Bagattini, Caroline Franco, Michelle Quarti Machado da Rosa, Lorena Mendes Simon, Suzi Alves Camey, Ricardo de Souza Kuchenbecker, Paulo Inácio Prado, José Alexandre Felizola Diniz Filho, Roberto André Kraenkel, Renato Mendes Coutinho, Cristiana Maria Toscano

Research output: Working paperPreprint

Abstract

Among the various non-pharmaceutical interventions implemented in response to the COVID-19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long-term impacts of prolonged suspension of in-person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of COVID-19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening.

Our model shows that reopening schools results in a non-linear increase of reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within-school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.
Original languageEnglish
PublisherMedRxiv
DOIs
Publication statusPublished - 26 Oct 2021
Externally publishedYes

Bibliographical note

This study was funded by the Brazilian National Council for Scientific and Technological Development (CNPq) - Process # 402834/2020-8 (request for proposals MCTIC/CNPq/FNDCT/MS/SCTIE/Decit Number 07/2020). The funding sources played no role in the study design; collection, analysis, or interpretation of the data; writing the report, or decision to submit the paper for publication. MEB received a technological and industrial scholarship from CNPq (grant number 315854/2020-0). LSF received a masters scholarship from Coordination of Superior Level Staff Improvement (CAPES) (finance code 001). SP was supported by Sao Paulo State Research Support Foundation (FAPESP) (grant number: 2018/24037-4). CF was supported by FAPESP (grant number: 2019/26310-2 and 2017/26770-8). RAK has been supported by CNPq (grant number: 311832/2017-2) and FAPESP (contract number: 2016/01343-7). PIP has been supported by CNPq (grant number: 313055/2020-3). RSK has been supported by CNPq (proc. 312378/2019-0). MQMR received a postdoctoral scholarship from CAPES (grant number 305269/2020-8). CMT has been supported by CNPq productivity fellowship and the National Institute of Science and Technology for Health Technology Assessment (IATS) (proc: 465518/2014-1). AMB received a technological and industrial scholarship from CNPq (grant number 402834/2020-8). LMS received a technological and industrial scholarship from CNPq (grant number 315866/2020-9). JAFD-F has been supported by CNPq productivity fellowship and the National Institutes for Science and Technology in Ecology, Evolution and Biodiversity Conservation (INCT-EEC), supported by MCTIC/CNPq (proc. 465610/2014-5) and FAPEG (proc. 201810267000023).

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