Análise temporal da relação entre dengue e variáveis climáticas na cidade de Uberlândia - MG

• Ano de defesa: 2023
• Autor(a) principal: Leite, Eduardo Soares
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia; Brasil; Programa de Pós-graduação em Geografia
• Palavras-chave em Português: Uberlândia; Dengue; Variáveis climáticas; Climate variables; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS; Geografia; Dengue - Uberlândia - MG; Mudanças climáticas - Uberlândia - MG; Climatologia urbana - Uberlândia - MG
• Link de acesso: https://repositorio.ufu.br/handle/123456789/37954; http://doi.org/10.14393/ufu.te.2023.8041

Problems involving tropical diseases are considered key elements in analysis related to the urban climate of Brazilian cities, especially in analysis of epidemic outbreaks of dengue correlated with the socio environmental conditions that involve urban dynamism. In this context, this study aimed to analyze the relationship between some climatic variables and the dynamics of dengue cases in Uberlândia, Minas Gerais. Monthly data from climate variables (average, maximum and minimum temperatures, relative humidity and precipitation) and dengue cases were used within two series, the first from January 2010 to December 2019 and the other from June 2021 to June 2022. Climatic data were taken from the meteorological station located at the Federal University of Uberlândia and dengue notifications from DATASUS and the Municipal Health Department of Uberlândia. The results indicate, for the series from 2010 to 2019, an increase in dengue cases along with the increase in the minimum temperature, above the range of 18 ºC, the average temperature, mainly in the range of 26 ºC to 28 ºC and relative humidity, above 70%. On the other hand, there was a reduction in cases in years with monthly average maximum temperature above 30 ºC. For the series from 2021 to 2022, each sector of the city presented a peculiar climatic condition in the prediction of dengue cases by the statistical model. For example, in the central sector, the increase in relative humidity showed a positive correlation with dengue cases. In the eastern sector, the minimum temperature variable had greater statistical predictability. Within the limitations that the dynamics of dengue offers, due to its multi causality, the analysis made it possible to verify a direct relationship between the climatic variables and the number of dengue cases and epidemic years in the city, information that can serve as a subsidy for action and management plans aimed at reducing the negative impacts of dengue epidemics on the population of Uberlandia.