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Modelling the spatial distribution of Fasciola hepatica in bovines using decision tree, logistic regression and GIS query approaches for Brazil

Published online by Cambridge University Press:  14 August 2017

S. C. BENNEMA ,
M. B. MOLENTO Open the ORCID record for M. B. MOLENTO [Opens in a new window] ,
R. G. SCHOLTE ,
O. S. CARVALHO  and
I. PRITSCH
S. C. BENNEMA
Affiliation:
Laboratorio de Doencas Parasitarias, Universidade Federal do Parana, R: dos Funcionários, 1540, Curitiba, PR, CEP: 80035-050, Brazil
M. B. MOLENTO*
Affiliation:
Laboratorio de Doencas Parasitarias, Universidade Federal do Parana, R: dos Funcionários, 1540, Curitiba, PR, CEP: 80035-050, Brazil
R. G. SCHOLTE
Affiliation:
Laboratorio de Helmintologia e Malacologia, Fundação Oswaldo Cruz, Av: Augusto Lima, 1715. Belo Horizonte, MG, CEP: 21040-900, Brazil
O. S. CARVALHO
Affiliation:
Laboratorio de Helmintologia e Malacologia, Fundação Oswaldo Cruz, Av: Augusto Lima, 1715. Belo Horizonte, MG, CEP: 21040-900, Brazil
I. PRITSCH
Affiliation:
Laboratorio de Doencas Parasitarias, Universidade Federal do Parana, R: dos Funcionários, 1540, Curitiba, PR, CEP: 80035-050, Brazil
*
*Corresponding author: Laboratorio de Doencas Parasitarias, Universidade Federal do Parana, R: dos Funcionários, 1540, Curitiba, PR, CEP: 80035-050, Brazil. E-mail: molento@ufpr.br
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Summary

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.

Keywords

Liver flukeruminantsprediction mapgeospatial diagnostic

Information

Type
Research Article
Information
Parasitology , Volume 144 , Issue 13 , November 2017 , pp. 1677 - 1685
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Copyright
Copyright © Cambridge University Press 2017 

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