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 studie...
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ftdoajarticles:oai:doaj.org/article:a728c457b3bb4a0e8ba732075f927847 2023-05-15T15:11:00+02:00 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 2021-04-01T00:00:00Z https://doi.org/10.1590/0037-8682-0851-2020 https://doaj.org/article/a728c457b3bb4a0e8ba732075f927847 EN eng Sociedade Brasileira de Medicina Tropical (SBMT) http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822021000100318&tlng=en https://doaj.org/toc/1678-9849 1678-9849 doi:10.1590/0037-8682-0851-2020 https://doaj.org/article/a728c457b3bb4a0e8ba732075f927847 Revista da Sociedade Brasileira de Medicina Tropical, Vol 54 (2021) Schistosomiasis Biomphalaria Spatial analysis Gi statistics Georeferencing Epidemiology Arctic medicine. Tropical medicine RC955-962 article 2021 ftdoajarticles https://doi.org/10.1590/0037-8682-0851-2020 2022-12-31T02:02:37Z 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Revista da Sociedade Brasileira de Medicina Tropical 54 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Schistosomiasis Biomphalaria Spatial analysis Gi statistics Georeferencing Epidemiology Arctic medicine. Tropical medicine RC955-962 |
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Schistosomiasis Biomphalaria Spatial analysis Gi statistics Georeferencing Epidemiology Arctic medicine. Tropical medicine RC955-962 Raquel Gardini Sanches Palasio Aline Nazaré Bortoleto Roseli Tuan Francisco Chiaravalloti-Neto 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 |
topic_facet |
Schistosomiasis Biomphalaria Spatial analysis Gi statistics Georeferencing Epidemiology Arctic medicine. Tropical medicine RC955-962 |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Raquel Gardini Sanches Palasio Aline Nazaré Bortoleto Roseli Tuan Francisco Chiaravalloti-Neto |
author_facet |
Raquel Gardini Sanches Palasio Aline Nazaré Bortoleto Roseli Tuan Francisco Chiaravalloti-Neto |
author_sort |
Raquel Gardini Sanches Palasio |
title |
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 |
title_short |
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 |
title_full |
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 |
title_fullStr |
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 |
title_full_unstemmed |
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 |
title_sort |
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 |
publisher |
Sociedade Brasileira de Medicina Tropical (SBMT) |
publishDate |
2021 |
url |
https://doi.org/10.1590/0037-8682-0851-2020 https://doaj.org/article/a728c457b3bb4a0e8ba732075f927847 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Revista da Sociedade Brasileira de Medicina Tropical, Vol 54 (2021) |
op_relation |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0037-86822021000100318&tlng=en https://doaj.org/toc/1678-9849 1678-9849 doi:10.1590/0037-8682-0851-2020 https://doaj.org/article/a728c457b3bb4a0e8ba732075f927847 |
op_doi |
https://doi.org/10.1590/0037-8682-0851-2020 |
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Revista da Sociedade Brasileira de Medicina Tropical |
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54 |
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