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Smart testing and critical care bed sharing for COVID-19 control

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 s...

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Autores principales: Silva, Paulo J. S., Pereira, Tiago, Sagastizábal, Claudia, Nonato, Luis, Cordova, Marcelo M., Struchiner, Claudio J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494319/
https://www.ncbi.nlm.nih.gov/pubmed/34613981
http://dx.doi.org/10.1371/journal.pone.0257235
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author Silva, Paulo J. S.
Pereira, Tiago
Sagastizábal, Claudia
Nonato, Luis
Cordova, Marcelo M.
Struchiner, Claudio J.
author_facet Silva, Paulo J. S.
Pereira, Tiago
Sagastizábal, Claudia
Nonato, Luis
Cordova, Marcelo M.
Struchiner, Claudio J.
author_sort Silva, Paulo J. S.
collection PubMed
description 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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spelling pubmed-84943192021-10-07 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. PLoS One Research Article 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. Public Library of Science 2021-10-06 /pmc/articles/PMC8494319/ /pubmed/34613981 http://dx.doi.org/10.1371/journal.pone.0257235 Text en © 2021 Silva et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Silva, Paulo J. S.
Pereira, Tiago
Sagastizábal, Claudia
Nonato, Luis
Cordova, Marcelo M.
Struchiner, Claudio J.
Smart testing and critical care bed sharing for COVID-19 control
title Smart testing and critical care bed sharing for COVID-19 control
title_full Smart testing and critical care bed sharing for COVID-19 control
title_fullStr Smart testing and critical care bed sharing for COVID-19 control
title_full_unstemmed Smart testing and critical care bed sharing for COVID-19 control
title_short Smart testing and critical care bed sharing for COVID-19 control
title_sort smart testing and critical care bed sharing for covid-19 control
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8494319/
https://www.ncbi.nlm.nih.gov/pubmed/34613981
http://dx.doi.org/10.1371/journal.pone.0257235
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