Evidence map›Paper›PMID 33886822›Full record

ArticleRevista da Sociedade Brasileira de Medicina Tropical2021

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.

Raquel Gardini Sanches Palasio, Aline Nazaré Bortoleto, Roseli Tuan, Francisco Chiaravalloti-Neto

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Article in Revista da Sociedade Brasileira de Medicina Tropical, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Raquel Gardini Sanches PalasioUniversidade de São Paulo, Faculdade de Saúde Pública, Departamento de Epidemiologia, Laboratório de Análise Espacial em Saúde, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0003-1564-0871
Aline Nazaré BortoletoUniversidade de São Paulo, Faculdade de Saúde Pública, Departamento de Epidemiologia, Laboratório de Análise Espacial em Saúde, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0002-9661-7341
Roseli TuanSuperintendência de Controle de Endemias, Laboratório de Bioquímica e Biologia Molecular, Luz, SP, Brasil.ORCID http://orcid.org/0000-0001-7379-783X
Francisco Chiaravalloti-NetoUniversidade de São Paulo, Faculdade de Saúde Pública, Departamento de Epidemiologia, Laboratório de Análise Espacial em Saúde, São Paulo, SP, Brasil.ORCID http://orcid.org/0000-0003-2686-8740

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOurinhos 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.

methodsGi 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.

resultsWe 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.

conclusionsThe 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.

Indexed as

BiomphalariaSchistosomiasisSchistosomiasis mansoniAnimalsBrazilDisease VectorsGeographic Information SystemsHumansSchistosoma mansoniSewageSewage

Identifiers

PMID33886822
PMCPMC8047698

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