Revista de Saúde Pública (Oct 2021)

The socio-environmental production of malaria in three municipalities in the Carajás region, Pará, Brazil

  • Alba Lucia Ribeiro Raithy Pereira,
  • Claudia do Socorro Carvalho Miranda,
  • Juan Andrade Guedes,
  • Rafael Aleixo Coelho de Oliveira,
  • Pedro Silvestre da Silva Campos,
  • Vera Regina Da Cunha Menezes Palácios,
  • Camylle Maia Costa Faria,
  • Tainara Carvalho G. M. Filgueiras,
  • Roberto Carlos Figueiredo,
  • Nelson Veiga Gonçalves

DOI
https://doi.org/10.11606/s1518-8787.2021055003463
Journal volume & issue
Vol. 55

Abstract

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ABSTRACT OBJECTIVE To analyze the environmental production of malaria in the municipalities of Marabá, Parauapebas, and Canaã dos Carajás, in Pará, from 2014 to 2018. METHODS This ecological, cross-sectional study used epidemiological data in the Sistema de Informações de Vigilância Epidemiológica da Malária (Malaria Epidemiological Surveillance Information System) from the Secretaria de Saúde do Estado do Pará (State of Pará Health Department), cartographic data from the Brazilian Institute of Geography and Statistics (IBGE), and environmental data in the Projeto TerraClass (TerraClass Project) from the National Institute of Space Research (INPE). Statistical analyses used the chi-square test, while the spatial ones, the kernel and Moran’s (I) global bivariate techniques. RESULTS We analyzed a total of 437 confirmed cases of malaria in the selected area and period. The highest percentage of cases occurred among male miners and farmers, living in rural areas; Plasmodium vivax was the most frequent species; and the most used diagnosis, the thick drop/smear. We also observed a heterogeneous distribution of the disease — with evidence of spatial dependence between incidence areas and different forms of land use, and spatial autocorrelations related to the high variability of anthropic activities in the municipalities. CONCLUSION The environmental production of malaria relates mainly to cattle production and mining — anthropisms related to land use and occupation in the observed municipalities. Spatial data analysis technologies sufficed for the construction of the epidemiological scenario of the disease.

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