COVID-19 in medium-sized municipalities in the 14 health macro-regions of Minas Gerais, Brazil

• Autor(a) principal: Paula-Júnior,W. de
• Data de Publicação: 2021
• Outros Autores: Nascimento,R.C.R.M. do, Matiles,R.S., Lima-Neto,F.F. de, Leles,M.C.R., Guimarães,H.N., Grabe-Guimarães,A.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Medical and Biological Research
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2021001100603
• topic: SARS-CoV-2; Epidemiology; Prevalence; ICU beds; Pandemic; Time series analysis

The present study focused on the scenario of confirmed cases of SARS-CoV-2 infection in the state of Minas Gerais (MG), Brazil, from March 2020 to March 2021. We evaluated the evolution of COVID-19 prevalence and death in one municipality from each of the 14 health macro-regions of MG state. Socio-demographic characteristics and variables related to the municipalities were analyzed. The raw dataset used in this study was freely sourced from the website Brasil.io. From the raw dataset, two time series were extracted: the cumulative confirmed cases of COVID-19 and cumulative death counts, and they were compared to the state data using a nowcasting approach. In order to make time series comparisons possible, all data was normalized per 100,000 inhabitants. When analyzing in light of colored wave code interventions initiated in August 2020 in MG, for the majority of the municipalities, there was an absence of clear influence on prevalence and deaths. The national holidays in the first semester of 2020 had a small impact on the COVID-19 prevalence of the municipalities, but the holidays in the second semester of 2020 and beginning of 2021 caused important impacts on COVID-19 prevalence. The low number of ICU beds in some municipalities contributed to the higher number of deaths. The analysis showed here is expected to contribute to the improvement of decision making of the MG government, as it opened a huge possibility to have the total macro-regions and state data analyzed.