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Rev. Soc. Bras. Med. Trop ; Rev. Soc. Bras. Med. Trop;52: e20180447, 2019. tab, graf
Article de Anglais | LILACS | ID: biblio-1013310

RÉSUMÉ

Abstract INTRODUCTION: The Middle Paranapanema watershed is known for the transmission of schistosomiasis, and there have been autochthonous cases since 1952. This study aimed to describe this disease in space and time and evaluate its current importance as a public health problem. METHODS: Thematic maps showing the risk areas for transmission of schistosomiasis, using scan statistics, and flow maps were created in the period 1978-2016. Incidence was calculated, and the existence of spatial dependence between autochthonous and imported cases was evaluated using Ripley's K12-function. Species of snails were identified in high-risk clusters. RESULTS: A total of 1,511 autochthonous cases were reported in eight of the 25 municipalities in the study area, of which 92.8% occurred in Ourinhos. A total of 2,189 imported cases were reported (27% in Ourinhos and 20% in Assis), mainly originating in the states of Paraná and Minas Gerais. Clusters of autochthonous and imported cases with higher risk were identified in Ourinhos, Assis and Ipaussu. However, over the years, the cases began to occur in low density in Ourinhos and no longer in other municipalities in the region. The cluster detected in the period 2007-2016 in Ourinhos still has risk for the transmission of schistosomiasis. K12-function analysis indicated positive spatial dependence between autochthonous and imported cases. CONCLUSIONS: The study showed that, currently, schistosomiasis as a public health problem in Middle Paranapanema is restricted to Ourinhos. This fact may be related to the presence of Biomphalaria glabrata at a specific point and low coverage of basic sanitation.


Sujet(s)
Humains , Animaux , Schistosomiase à Schistosoma mansoni/épidémiologie , Schistosoma mansoni , Biomphalaria , Schistosomiase à Schistosoma mansoni/transmission , Brésil/épidémiologie , Caractéristiques de l'habitat , Santé publique , Incidence , Rivières , Analyse spatiale
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