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Geographic Information System-based association between the sewage network, geographical location of intermediate hosts, and autochthonous cases for the estimation of risk areas of schistosomiasis infection in Ourinhos, São Paulo, Brazil

Abstract

INTRODUCTION:

Ourinhos is a municipality located between the Pardo and Paranapanema rivers, and it has been characterized by the endemic transmission of schistosomiasis since 1952. We used geospatial analysis to identify areas prone to human schistosomiasis infections in Ourinhos. We studied the association between the sewage network, co-occurrence of Biomphalaria snails (identified as intermediate hosts [IHs] of Schistosoma mansoni), and autochthonous cases.

METHODS:

Gi spatial statistics, Ripley’s K12-function, and kernel density estimation were used to evaluate the association between schistosomiasis data reported during 2007-2016 and the occurrence of IHs during 2015-2017. These data were superimposed on the municipality sewage network data.

RESULTS:

We used 20 points with reported IH; they were colonized predominantly by Biomphalaria glabrata, followed by B. tenagophila and B. straminea. Based on Gi statistics, a significant cluster of autochthonous cases was superimposed on the Christoni and Água da Veada water bodies, with distances of approximately 300 m and 2200 m from the points where B. glabrata and B. straminea were present, respectively.

CONCLUSIONS:

The residence geographical location of autochthonous cases allied with the spatial analysis of IHs and the coverage of the sewage network provide important information for the detection of human-infection areas. Our results demonstrated that the tools used for direct surveillance, control, and elimination of schistosomiasis are appropriate.

Keywords:
Schistosomiasis; Biomphalaria; Spatial analysis; Gi statistics; Georeferencing; Epidemiology

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