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Infections by trypanosomatid (Kinetoplastida: Trypanosomatidae) in triatomines (Hemiptera: Triatominae): A spatiotemporal assessment in an endemic area for Chagas disease.

Tatiene Rossana Móta SilvaEdyniesky Ferrer-MirandaJéssica Cardoso Pessoa de OliveiraKleber Régis SantoroLeucio Câmara AlvesLílian Silva Sampaio de BarrosRafael Antonio Nascimento RamosGílcia Aparecida de Carvalho
Published in: Zoonoses and public health (2021)
This research analysed the spatiotemporal distribution of triatomines infected by trypanosomatid parasites in an endemic region for Chagas disease, in the state of Pernambuco, Northeastern Brazil. The database included the total number of triatomines captured from intradomicile and peridomicile areas, as well as the infection rate (IR) by trypanosomatid. The G i ∗ by Getis-Ord method was used to statistically identify significant concentration clusters and the IR of triatomines by trypanosomatids. A generalized linear regression model with a binomial distribution was used to evaluate the probability of finding an IR by trypanosomatids. Overall, of 4,800 triatomines examined, trypanosomatid forms similar to Trypanosoma cruzi were detected in 10.29% of them, and the majority of positive specimens (98.17%) were collected at intradomicile. The geospatial analyses identified triatomines clusters in intradomicile and peridomicile environments. According to the logistic regression data for species (Panstrongylus lutzi, P. megistus, Triatoma brasiliensis and T. pseudomaculata), the probability of detection of T. cruzi infection remains constant in up to 50 specimens examined or more. The findings of this research revealed a scenario never studied in this area through this type of spatiotemporal analysis, which is essential to identify areas of vulnerability for the occurrence of these vectors and consequently for Chagas disease.
Keyphrases
  • trypanosoma cruzi
  • climate change
  • emergency department
  • machine learning
  • big data