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A tale of 141 municipalities: the spatial distribution of dengue in Mato Grosso, Brazil.
Fernandes, Keli Aparecida Paludo; de Almeida Filho, Ariel Rocha; Moura Alves, Taynná Vacaro; Bernardo, Christine Steiner São; Montibeller, Maria Jara; Mondini, Adriano; Bronzoni, Roberta Vieira de Morais.
Afiliação
  • Fernandes KAP; Instituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop 78550-267, Mato Grosso, Brazil.
  • de Almeida Filho AR; Instituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop 78550-267, Mato Grosso, Brazil.
  • Moura Alves TV; Instituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop 78550-267, Mato Grosso, Brazil.
  • Bernardo CSS; Instituto de Ciências Naturais, Humanas e Sociais, Universidade Federal de Mato Grosso, Sinop 78550-267, Mato Grosso, Brazil.
  • Montibeller MJ; School of Pharmaceutical Sciences, São Paulo State University, Araraquara 14800-903, São Paulo, Brazil.
  • Mondini A; School of Pharmaceutical Sciences, São Paulo State University, Araraquara 14800-903, São Paulo, Brazil.
  • Bronzoni RVM; Instituto de Ciências da Saúde, Universidade Federal de Mato Grosso, Sinop 78550-267, Mato Grosso, Brazil.
Trans R Soc Trop Med Hyg ; 117(10): 751-759, 2023 10 03.
Article em En | MEDLINE | ID: mdl-37665762
BACKGROUND: In recent years, the state of Mato Grosso has presented one of the highest dengue incidence rates in Brazil. The meeting of the Amazon, Cerrado and Pantanal biomes results in a large variation of rainfall and temperature across different regions of the state. In addition, Mato Grosso has been undergoing intense urban growth since the 1970s, mainly due to the colonization of the Mid-North and North regions. We analyzed factors involved in dengue incidence in Mato Grosso from 2008 to 2019. METHODS: The Moran Global Index was used to assess spatial autocorrelation of dengue incidence using explanatory variables such as temperature, precipitation, deforestation, population density and municipal development index. Areas at risk of dengue were grouped by the Local Moran Indicator. RESULTS: We noticed that areas at risk of dengue expanded from the Mid-North region to the North; the same pattern occurred from the Southeast to the Northeast; the South region remained at low-risk levels. The increase in incidence was influenced by precipitation, deforestation and the municipal development index. CONCLUSIONS: The identification of risk areas for dengue in space and time enables public health authorities to focus their control and prevention efforts, reducing infestation and the potential impact of dengue in the human population.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Dengue Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Ecossistema / Dengue Tipo de estudo: Prognostic_studies Limite: Humans País/Região como assunto: America do sul / Brasil Idioma: En Ano de publicação: 2023 Tipo de documento: Article