ABSTRACT
Fascioliasis is a condition caused by the trematode Fasciola hepatica. In this paper, the spatial distribution of F. hepatica in bovines in Brazil was modelled using a decision tree approach and a logistic regression, combined with a geographic information system (GIS) query. In the decision tree and the logistic model, isothermality had the strongest influence on disease prevalence. Also, the 50-year average precipitation in the warmest quarter of the year was included as a risk factor, having a negative influence on the parasite prevalence. The risk maps developed using both techniques, showed a predicted higher prevalence mainly in the South of Brazil. The prediction performance seemed to be high, but both techniques failed to reach a high accuracy in predicting the medium and high prevalence classes to the entire country. The GIS query map, based on the range of isothermality, minimum temperature of coldest month, precipitation of warmest quarter of the year, altitude and the average dailyland surface temperature, showed a possibility of presence of F. hepatica in a very large area. The risk maps produced using these methods can be used to focus activities of animal and public health programmes, even on non-evaluated F. hepatica areas.
Subject(s)
Animal Distribution , Cattle Diseases/epidemiology , Fasciola hepatica/physiology , Fascioliasis/epidemiology , Animals , Brazil/epidemiology , Cattle , Cattle Diseases/parasitology , Climate , Decision Trees , Fascioliasis/parasitology , Geographic Information Systems , Logistic Models , Models, Theoretical , Prevalence , Risk Assessment , Risk Factors , Spatial AnalysisABSTRACT
Leishmaniases are serious diseases caused by trypanosomatid protozoans of the genus Leishmania transmitted by the bite of phlebotomine sand flies. We analyzed records pertaining to Lutzomyia longipalpis (Lutz and Neiva, 1912) and Lutzomyia cruzi (Mangabeira, 1938) in Brazil from the following sources: the collection of phlebotomine sand flies of the Centro de Pesquisas René Rachou/Fiocruz (FIOCRUZ-COLFLEB), the "SpeciesLink" (CRIA) database, from systematic surveys of scientific articles and gray literature (dissertations, theses, and communications), and disease data obtained from the Information System for Notifiable Diseases/Ministry of Health (SINAN/MS). Environmental data and ecological niche modeling (ESMS) using the approach of MaxEnt algorithm produced maps of occurrence probability for both Lu. longipalpis and Lu. cruzi. Lutzomyia longipalpis was found in 229 Brazilian municipalities and Lu. cruzi in 27. The species were sympatric in 16 municipalities of the Central-West region of Brazil. Our results show that Lu. longipalpis is widely distributed and associated with the high number of cases of visceral leishmaniasis reported in Brazil.
