2020
DOI: 10.1101/2020.04.26.20081208
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Mathematical model of COVID-19 intervention scenarios for São Paulo-Brazil

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 … Show more

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Cited by 5 publications
(4 citation statements)
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“…On the other hand, although our estimations of the percentage of population infected for Argentina, Brazil, Chile and Colombia significantly differ from modelled seroprevalence estimations for those countries, 21 our estimations of the percentage of undiagnosed infections are similar to those showed by seroprevalence studies. According to our results, at least the 96% of the infections in the analyzed countries (excluding Brazil) are not diagnosed, that agrees with serological community based studies in Hubei, China that suggests that 97% of infections might have gone undiagnosed during the epidemic, 22 and in Geneva, Switzerland that showed that for every confirmed case there were 11.6 infections in the community. 23…”
Section: Discussionsupporting
confidence: 90%
“…On the other hand, although our estimations of the percentage of population infected for Argentina, Brazil, Chile and Colombia significantly differ from modelled seroprevalence estimations for those countries, 21 our estimations of the percentage of undiagnosed infections are similar to those showed by seroprevalence studies. According to our results, at least the 96% of the infections in the analyzed countries (excluding Brazil) are not diagnosed, that agrees with serological community based studies in Hubei, China that suggests that 97% of infections might have gone undiagnosed during the epidemic, 22 and in Geneva, Switzerland that showed that for every confirmed case there were 11.6 infections in the community. 23…”
Section: Discussionsupporting
confidence: 90%
“…Factors affecting mortality are widely discussed, including air quality, meteorological conditions (Rahman et al, 2021), travel habits (B. Wang et al, 2020) and social distance (Neto et al, 2021). Among them, air quality and meteorological conditions are relatively uncontrollable factors.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, many such public health measures involve reducing social contact in the population and, consequently, the transmission rate of the virus, alleviating the pressure on the health system and providing time for auxiliary measures to be put in place (expansion of the system, creation of military hospitals, and so on). In this regard, another critical aspect is the difference in population adherence to social isolation measures in the different cities and states of the country (14).…”
mentioning
confidence: 99%