Identification of Risk Areas for Intestinal Schistosomiasis, Based on Malacological and Environmental Data and on Reported Human Cases

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.

Keywords: Biomphalaria; Schistosoma mansoni; ecological models; malacological survey; risk mapping.

Figure 1

Distribution of water resources and the 46 collection points for the investigation of limnic molluscs, between the years 2018 and 2019, in the Municipality of Alvorada de Minas, Minas Gerais, Brazil.

Figure 2

Distribution of environmental and epidemiological data (malacology, altered environments and the presence of E. coli), and cases of infected humans in the nearby communities, identified by collection points, in the municipality of Alvorada de Minas, Minas Gerais, Brazil. The white circles represent investigated areas that did not show factors associated with schistosomiasis.

Figure 3

Correlation map of Biomphalaria glabrata with precipitation and land surface temperature at night, using 2018–2019 GEE data and land use map, municipality of Alvorada de Minas, Minas Gerais, Brazil.

Figure 4

Spatial distribution of Biomphalaria glabrata in the municipality of Alvorada de Minas, Minas Gerais, Brazil, obtained by MaxEnt.

Figure 5

Distribution of Biomphalaria glabrata habitats and risk zones, according to Buffer estimates, in the period from 2018–2019, Alvorada de Minas, Minas Gerais State, Brazil. Collection points with B. glabrata (red circles) and buffer risk zones for downstream or upstream waterbodies for 500 meters (red), 1,000 meters (orange), and 1,500 meters (yellow) distance.

Figure 6

Risk map for transmission of schistosomiasis, estimated by Cokriging with total arbitrary weight of environmental and human epidemiological data, in the Municipality of Alvorada de Minas, Minas Gerais, Brazil. Relative risk is indicated by a graduated color map, with red areas corresponding to high risk and dark blue areas with absent risk of infection.