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Smart testing and critical care bed sharing for COVID-19 control.
Silva, Paulo J S; Pereira, Tiago; Sagastizábal, Claudia; Nonato, Luis; Cordova, Marcelo M; Struchiner, Claudio J.
Afiliação
  • Silva PJS; Instituto de Matemática, Estatística e Computação Científica, Universidade de Campinas, São Paulo, Brazil.
  • Pereira T; Instituto de Ciências Matemáticas e Computação, Universidade de São Paulo, São Paulo, Brazil.
  • Sagastizábal C; Department of Mathematics, Imperial College London, London, United Kingdom.
  • Nonato L; Instituto de Matemática, Estatística e Computação Científica, Universidade de Campinas, São Paulo, Brazil.
  • Cordova MM; Instituto de Ciências Matemáticas e Computação, Universidade de São Paulo, São Paulo, Brazil.
  • Struchiner CJ; Departamento de Engenharia Elétrica, Universidade Federal de Santa Catarina, Florianópolis, Brazil.
PLoS One ; 16(10): e0257235, 2021.
Article em En | MEDLINE | ID: mdl-34613981
During the early months of the current COVID-19 pandemic, social distancing measures effectively slowed disease transmission in many countries in Europe and Asia, but the same benefits have not been observed in some developing countries such as Brazil. In part, this is due to a failure to organise systematic testing campaigns at nationwide or even regional levels. To gain effective control of the pandemic, decision-makers in developing countries, particularly those with large populations, must overcome difficulties posed by an unequal distribution of wealth combined with low daily testing capacities. The economic infrastructure of these countries, often concentrated in a few cities, forces workers to travel from commuter cities and rural areas, which induces strong nonlinear effects on disease transmission. In the present study, we develop a smart testing strategy to identify geographic regions where COVID-19 testing could most effectively be deployed to limit further disease transmission. By smart testing we mean the testing protocol that is automatically designed by our optimization platform for a given time period, knowing the available number of tests, the current availability of ICU beds and the initial epidemiological situation. The strategy uses readily available anonymised mobility and demographic data integrated with intensive care unit (ICU) occupancy data and city-specific social distancing measures. Taking into account the heterogeneity of ICU bed occupancy in differing regions and the stages of disease evolution, we use a data-driven study of the Brazilian state of Sao Paulo as an example to show that smart testing strategies can rapidly limit transmission while reducing the need for social distancing measures, even when testing capacity is limited.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ocupação de Leitos / Cuidados Críticos / Teste para COVID-19 / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ocupação de Leitos / Cuidados Críticos / Teste para COVID-19 / COVID-19 Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Revista: PLoS One Assunto da revista: CIENCIA / MEDICINA Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Brasil País de publicação: Estados Unidos