Login / Signup

Socio-environmental factors associated with the occurrence of triatomines (Hemiptera: Reduviidae) in an endemic municipality in northern Minas Gerais, Brazil.

Thainara da Silva GonçalvesRenata Luiz UrsineMiriam CardozoRosanna Lorrane Francisco Dos Reis MatosRita de Cássia Moreira de SouzaLiléia Gonçalves DiotaiutiDavid Eladio GorlaSílvio Fernando Guimarães de CarvalhoThallyta Maria Vieira
Published in: Zoonoses and public health (2023)
Triatomines are the vectors of Trypanosoma cruzi, the etiological agent of Chagas disease. The study aimed to evaluate the association between sociodemographic and environmental factors, and changes in land use and cover, with the occurrence and abundance of triatomines by census sectors in an endemic municipality of northern Minas Gerais, Brazil. The study was conducted in Montes Claros, located in the north of Minas Gerais, Brazil. The entomological data used in the study were collected by active surveillance in the rural area from 2015 to 2019 and by passive surveillance in the urban area from 2009 to 2019. Data on sociodemographic and environmental factors and changes in land use and land cover were obtained from the urban and rural census sectors. A total of 1404 triatomines, belonging to eight species, were captured in domiciles in the rural area (2015-2019) and 277 triatomines in domiciles in the urban area (2009-2019) of the municipality of Montes Claros. The variables the number of domiciles, household economic income, pavement, NDVI, deforestation, unchanged, and anthropic proved to be positively associated with the occurrence and/or number of triatomines in census sectors, within the models. The occurrence of triatomines in the domestic environment of the municipality of Montes Claros should be considered a public health problem, as it suggests a potential risk of establishment and transmission of T. cruzi to domestic animals, farm animals, and humans.
Keyphrases
  • public health
  • risk assessment
  • south africa
  • physical activity
  • big data
  • machine learning
  • trypanosoma cruzi
  • microbial community
  • artificial intelligence
  • wastewater treatment
  • antibiotic resistance genes