Abstract
The objective of the current investigation was to produce a generalized computational model to predict consequences of various reopening scenarios on COVID-19 infections rates and available hospital resources in São Paulo - Brazil. We were able to use the Susceptible-Exposed-Infected-Recovered (SEIR) model to fit both accumulated death data and corrected accumulated cases data associated with COVID-19 for both Brazil and the state of São Paulo. In addition, we were able to simulate the consequences of reopening under different possible scenarios in Brazil, in special for the state of São Paulo. The model was able to provide a predicted scenario in which reopening could occur with minimal impact on human life considering people careful behavior in combination with continued social distancing measures.
Competing Interest Statement
The authors have declared no competing interest.
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not applicable
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All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.
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I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
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Paper in collection COVID-19 SARS-CoV-2 preprints from medRxiv and bioRxiv
The Chan Zuckerberg Initiative, Cold Spring Harbor Laboratory, the Sergey Brin Family Foundation, California Institute of Technology, Centre National de la Recherche Scientifique, Fred Hutchinson Cancer Center, Imperial College London, Massachusetts Institute of Technology, Stanford University, The University of Edinburgh, University of Washington, and Vrije Universiteit Amsterdam.
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