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Preprint em Inglês | medRxiv | ID: ppmedrxiv-20035873

RESUMO

In January 2020 China reported to the World Health Organization an outbreak of pneumonia of undetermined origin in the city of Wuhan, Hubei. In January 30, 2020, the World Health Organization declared the outbreak of COVID-19 as a Public Health Emergency of International Interest (PHEI). ObjectivesThe aim of this study is to assess the impact of a COVID-19 epidemic in the metropolitan region of Sao Paulo, Brazil. MethodsWe used a generalized SEIR (Susceptibles, Exposed, Infectious, Recovered) model, with additional Hospitalized variables (SEIHR model) and age-stratified structure to analyze the expected time evolution during the onset of the epidemic in the metropolitan area of Sao Paulo. The model allows to determine the evolution of the number of cases, the number of patients admitted to hospitals and deaths caused by COVID-19. In order to investigate the sensibility of our results with respect to parameter estimation errors we performed Monte Carlo analysis with 100 000 simulations by sampling parameter values from an uniform distribution in the confidence interval. ResultsWe estimate 1 368 (IQR: 880, 2 407) cases, 301 (22%) in older people ([≥]60 years), 81 (50, 143) hospitalizations, and 14 (9, 26) deaths in the first 30 days, and 38 583 (IQR: 16 698, 113, 163) cases, 8 427 (21.8%) in older people ([≥]60 years), 2181 (914, 6392) hospitalizations, and 397(166, 1205) deaths in the first 60 days. LimitationsWe supposed a constant transmission probability Pc among different age-groups, and that every severe and critic case will be hospitalized, as well as that the detection capacity in all the primary healthcare services does not change during the outbreak. ConclusionSupposing the reported parameters in the literature apply in the city of Sao Paulo, our study shows that it is expected that the impact of a COVID-19 outbreak will be important, requiring special planning from the authorities. This is the first study for a major metropolitan center in the south hemisphere, and we believe it can provide policy makers with a prognosis of the burden of the pandemic not only in Brazil, but also in other tropical zones, allowing to estimate total cases, hospitalization and deaths, in support to the management of the public health emergence caused by COVID-19.

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