Abstract
The aim of the present study was to use an integrated approach for the identification of risk areas for Schistosoma mansoni transmission in an area of low endemicity in Minas Gerais, Brazil. For that, areas of distribution of Biomphalaria glabrata were identified and were related to environmental variables and communities with reported schistosomiasis cases, in order to determine the risk of infection by spatial analyses with predictive models. The research was carried out in the municipality of Alvorada de Minas, with data obtained between the years 2017 and 2019 inclusive. The Google Earth Engine was used to obtain geo-climatic variables (temperature, precipitation, vegetation index and digital elevation model), R software to determine Pearson's correlation and MaxEnt software to obtain an ecological model. ArcGis Software was used to create maps with data spatialization and risk maps, using buffer models (diameters: 500, 1,000 and 1,500 m) and CoKriging. Throughout the municipality, 46 collection points were evaluated. Of these, 14 presented snails of the genus Biomphalaria. Molecular analyses identified the presence of different species of Biomphalaria, including B. glabrata. None of the snails eliminated S. mansoni cercariae. The distribution of B. glabrata was more abundant in areas of natural vegetation (forest and cerrado) and, for spatial analysis (Buffer), the main risk areas were identified especially in the main urban area and toward the northern and eastern extensions of the municipality. The distribution of snails correlated with temperature and precipitation, with the latter being the main variable for the ecological model. In addition, the integration of data from malacological surveys, environmental characterization, fecal contamination, and data from communities with confirmed human cases, revealed areas of potential risk for infection in the northern and eastern regions of the municipality. In the present study, information was integrated on epidemiological aspects, transmission and risk areas for schistosomiasis in a small, rural municipality with low endemicity. Such integrated methods have been proposed as important tools for the creation of schistosomiasis transmission risk maps, serve as an example for other communities and can be used for control actions by local health authorities, e.g., indicate priority sectors for sanitation measures.
Highlights
In 2018, a centenary had passed since the discovery and description of the intermediate hosts of Schistosoma mansoni Sambon, 1907 in Brazil by Adolpho Lutz [1]
In the State of Minas Gerais (MG), schistosomiasis is still endemic, but such substantial progress in the control of the disease has been achieved during the past decades, due to the implementation of the National Schistosomiasis Control Program (NSCP), that the positivity rate fell from 10.1% in 1977 to 3.86% in 2015, during the latest national survey [4]
The first three of those are natural intermediate host species of S. mansoni and B. cousini and are considered potential intermediate hosts, which is based on experimental infections in the laboratory [47]
Summary
In 2018, a centenary had passed since the discovery and description of the intermediate hosts of Schistosoma mansoni Sambon, 1907 in Brazil by Adolpho Lutz [1]. This human parasitic disease, endemic in other Latin American countries, remains one of the major public health problems in tropical and subtropical regions of the world [2]. It is estimated that approximately 240 million individuals are infected with schistosome species and 700–800 million people worldwide are at risk of infection [3]. Three snail species were found naturally infected with S. mansoni: Biomphalaria glabrata (Say, 1,818), Biomphalaria tenagophila (Orbigny, 1,835) and Biomphalaria straminea (Dunker, 1,848). Community and individual parasite loads have dropped during the last decades with more or less regular treatment rounds by NSCP and, nowadays, most individuals from endemic areas present with reduced parasite loads, are hard to detect by common diagnostic methods [6]
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