Please use this identifier to cite or link to this item: https://www.arca.fiocruz.br/handle/icict/41985
Title: Predictive model of COVID-19 incidence and socioeconomic description of municipalities in Brazil
Authors: Carneiro, Isadora C. R.
Ferreira, Eloiza D.
Silva, Janaina C. da
Soares, Guilherme
Strottmann, Daisy Maria
Silveira, Guilherme Ferreira
Affilliation: Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil.
Universidade Estadual do Oeste do Paraná. Laboratório de Biologia de Tumores. UNIOESTE. Francisco Beltrão, PR.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil. / Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratórios de Referência em Viroses Emergentes e Reemergentes. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Virologia Molecular. Curitiba, PR, Brasil.
Fundação Oswaldo Cruz. Instituto Carlos Chagas. Curitiba, PR, Brasil.
Abstract: Coronaviruses are enveloped viruses that can cause respiratory, 38 gastrointestinal, hepatic, and neurological diseases. In December 2019, a new 39 highly contagious coronavirus termed severe acute respiratory syndrome 40 coronavirus 2 (SARS-CoV-2) emerged in China. SARS-CoV-2 causes a 41 potentially lethal human respiratory infection, COVID-19, that is associated with 42 fever and cough and can progress to pneumonia and dyspnea in severe cases. 43 Since the virus emerged, it has spread rapidly, reaching all continents around 44 the world. A previous study has shown that, despite being the best alternative in 45 the current pandemic context, social distancing measures alone may not be 46 sufficient to prevent COVID-19 spread, and the overall impact of the virus is of 47 great concern. The present study aims to describe the demographic and 48 socioeconomic characteristics of 672 cities with cases of COVID-19, as well as 49 to determine a predictive model for the number of cases. We analyzed data 50 from cities with at least 1 reported case of COVID-19 until June 26, 2020. It was 51 observed that cities with confirmed cases of the disease are present in all 52 Brazilian states, affecting 36.5% of the municipalities in Rio de Janeiro State. 53 The inhabitants in cities with reported cases of COVID-19 represent more than 54 73.1% of the Brazilian population. Stratifying the age groups of the inhabitants 55 and accounting for the percentage of women and men does not affect COVID56 19 incidence (confirmed cases/100,000 inhabitants). The demographic density, 57 the MHDI and the per capita income of the municipalities with cases of COVID58 19 do not affect disease incidence. In addition, if conditions are maintained, our 59 model predicts 2,358,703 (2,172,930 to 2,544,477) cumulative cases on July 60 25, 2020.
Keywords: Coronavirus Infections
Data Interpretation, Statistical
Computational Biology
Epidemiology
Brazil
COVID-19
Keywords in spanish: Infecciones por Coronavirus
Interpretación Estadística de Datos
Biología Computacional
Epidemiología
COVID-19
keywords: COVID-19
Infecções por Coronavirus
Interpretação Estatística de Dados
ARIMA
Biologia Computacional
Epidemiologia
Brasil
Issue Date: 2020
Publisher: Laboratório Cold Spring Harbor
Citation: CARNEIRO, Isadora C. R. et al. Predictive model of COVID-19 incidence and socioeconomic description of municipalities in Brazil. medRxiv, p. 1-21, 2020.
DOI: 10.1101/2020.06.28.20141952
Copyright: open access
Appears in Collections:PR - ICC - Preprint

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