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dc.contributor.authorPinto Neto, Osmar et al.
dc.date.accessioned2020-05-29T19:39:44Z
dc.date.available2020-05-29T19:39:44Z
dc.date.issued2020-05-01
dc.identifier.urihttps://doi.org/10.1101/2020.04.26.20081208en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12663/1635
dc.description.abstractThe 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 Sao 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 Sao Paulo. In addition, we were able to simulate the consequences of reopening under different possible scenarios in Brazil, in special for the state of Sao 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.en_US
dc.languageEnglishen_US
dc.subjectCOVID-19en_US
dc.subjectCoronavirusen_US
dc.subjectInfectious Diseasesen_US
dc.subjectModels, Theoreticalen_US
dc.subjectComputer Simulationen_US
dc.subjectBrazilen_US
dc.titleCOVID-19 mathematical model reopening scenarios for Sao Paulo - Brazilen_US
eihealth.countryGlobal (WHO/OMS)en_US
eihealth.categoryEpidemiology and epidemiological studiesen_US
eihealth.typePublished Articleen_US
eihealth.maincategorySlow Spread / Reducir la Dispersiónen_US
dc.relation.ispartofjournalmedRxiven_US


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