Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil
We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guideli...
| Main Authors: | , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
|
| Series: | Global Epidemiology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590113322000244 |
| _version_ | 1798006380576112640 |
|---|---|
| author | 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 |
| author_facet | 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 |
| author_sort | Marcelo Eduardo Borges |
| collection | DOAJ |
| description | We simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and community, 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, and also estimate the number of hospitalization and deaths averted by the implementation of contact tracing. Reopening schools results in a non-linear increase in reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects in reducing the total number of hospitalizations and deaths. Policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. While contact tracing strategies prevent new infections within school environments, they alone are not sufficient to avoid significant impacts on community transmission. |
| first_indexed | 2024-04-11T12:54:58Z |
| format | Article |
| id | doaj.art-403aeaa92fc74543a006e658042749db |
| institution | Directory Open Access Journal |
| issn | 2590-1133 |
| language | English |
| last_indexed | 2024-04-11T12:54:58Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Global Epidemiology |
| spelling | doaj.art-403aeaa92fc74543a006e658042749db2022-12-22T04:23:06ZengElsevierGlobal Epidemiology2590-11332022-12-014100094Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in BrazilMarcelo Eduardo Borges0Leonardo Souto Ferreira1Silas Poloni2Angela Maria Bagattini3Caroline Franco4Michelle Quarti Machado da Rosa5Lorena Mendes Simon6Suzi Alves Camey7Ricardo de Souza Kuchenbecker8Paulo Inácio Prado9José Alexandre Felizola Diniz-Filho10Roberto André Kraenkel11Renato Mendes Coutinho12Cristiana Maria Toscano13Universidade Federal de Goiás, Instituto de Patologia Tropical e Saúde Pública, Rua 235, s/n.°, Setor Leste Universitário, Goiânia, Goiás 74605-050, Brazil; Corresponding author.Instituto de Física Teórica - Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz, 271, Várzea da Barra Funda, São Paulo, SP 01140-070, BrazilInstituto de Física Teórica - Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz, 271, Várzea da Barra Funda, São Paulo, SP 01140-070, BrazilUniversidade Federal de Goiás, Instituto de Patologia Tropical e Saúde Pública, Rua 235, s/n.°, Setor Leste Universitário, Goiânia, Goiás 74605-050, BrazilInstituto de Física Teórica - Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz, 271, Várzea da Barra Funda, São Paulo, SP 01140-070, Brazil; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Old Road Campus, OX3 7LF Oxford, UKUniversidade Federal de Goiás, Instituto de Patologia Tropical e Saúde Pública, Rua 235, s/n.°, Setor Leste Universitário, Goiânia, Goiás 74605-050, BrazilDepartamento de Ecologia, Instituto de Ciências Biológicas, Universidade Federal de Goiás, CP 131, Goiânia, Goiás 74001, BrazilUniversidade Federal do Rio Grande do Sul, Instituto de Matemática e Estatística, Departamento de Estatística, Avenida Bento Gonçalves, 9500, Agronomia, Porto Alegre, RS 91501-970, BrazilUniversidade Federal do Rio Grande do Sul, Programa de Pós-graduação em Epidemiologia, Faculdade de Medicina, Campus Saúde, Rua Ramiro Barcelos, 2400, 2° andar, Floresta, Porto Alegre, RS 90035003, BrazilInstituto de Biociências - Universidade de São Paulo, A101, Tv. 14, Butantã, São Paulo, SP 05508-090, BrazilDepartamento de Ecologia, Instituto de Ciências Biológicas, Universidade Federal de Goiás, CP 131, Goiânia, Goiás 74001, BrazilInstituto de Física Teórica - Universidade Estadual Paulista, Rua Dr. Bento Teobaldo Ferraz, 271, Várzea da Barra Funda, São Paulo, SP 01140-070, BrazilCentro de Matemática, Computação e Cognição - Universidade Federal do ABC, Avenida dos Estados, 5001, Santa Terezinha, Santo André, SP 09210-580, BrazilUniversidade Federal de Goiás, Instituto de Patologia Tropical e Saúde Pública, Rua 235, s/n.°, Setor Leste Universitário, Goiânia, Goiás 74605-050, BrazilWe simulate the impact of school reopening during the COVID-19 pandemic in three major urban centers in Brazil to identify the epidemiological indicators and the best timing for the return of in-school activities and the effect of contact tracing as a mitigation measure. Our goal is to offer guidelines for evidence-based policymaking. We implement an extended SEIR model stratified by age and considering contact networks in different settings – school, home, work, and community, 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, and also estimate the number of hospitalization and deaths averted by the implementation of contact tracing. Reopening schools results in a non-linear increase in reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects in reducing the total number of hospitalizations and deaths. Policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. While contact tracing strategies prevent new infections within school environments, they alone are not sufficient to avoid significant impacts on community transmission.http://www.sciencedirect.com/science/article/pii/S2590113322000244Decision support techniquesCOVID-19BrazilSchoolsNon-pharmaceutical interventionsDynamic transmission models |
| spellingShingle | 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 Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil Global Epidemiology Decision support techniques COVID-19 Brazil Schools Non-pharmaceutical interventions Dynamic transmission models |
| title | Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil |
| title_full | Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil |
| title_fullStr | Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil |
| title_full_unstemmed | Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil |
| title_short | Modelling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil |
| title_sort | modelling the impact of school reopening and contact tracing strategies on covid 19 dynamics in different epidemiologic settings in brazil |
| topic | Decision support techniques COVID-19 Brazil Schools Non-pharmaceutical interventions Dynamic transmission models |
| url | http://www.sciencedirect.com/science/article/pii/S2590113322000244 |
| work_keys_str_mv | AT marceloeduardoborges modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT leonardosoutoferreira modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT silaspoloni modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT angelamariabagattini modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT carolinefranco modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT michellequartimachadodarosa modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT lorenamendessimon modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT suzialvescamey modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT ricardodesouzakuchenbecker modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT pauloinacioprado modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT josealexandrefelizoladinizfilho modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT robertoandrekraenkel modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT renatomendescoutinho modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil AT cristianamariatoscano modellingtheimpactofschoolreopeningandcontacttracingstrategiesoncovid19dynamicsindifferentepidemiologicsettingsinbrazil |