Environmental inducers of schistosomiasis mansoni in Campinas, Brazil

Submitted: 19 December 2014
Accepted: 19 December 2014
Published: 1 November 2010
Abstract Views: 1119
PDF: 742
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Human occupation/activity in the suburbs of the large cities in Brazil, together with high social vulnerability associated with poor living conditions, influence the dynamics of schistosomiasis mansoni as well as several other emerging and re-emerging diseases. Previous notification data surveys for Campinas, São Paulo state, Brazil, carried out by the Information System for Notification Disease, show that there are distinct prevalence differences across healthcare districts of the city. This paper supports the hypothesis that the distribution of schistosomiasis is not random and that the centralized location of cases are linked to human behaviour, in particular to human activities that interfere with basic landscape structure. This paper analyzes the spatial patterns of the parasitic worm Schistosoma mansoni and its intermediate host Biomphalaria comparing disease prevalence with natural conditions and the current pattern of territory occupation by the population. The spatial and hierarchical distribution of factors related to the environmental conditions and land use that indicate the risk for schistosomiasis has been surveyed. It was found that landscape characteristics define the areas at risk for this endemic disease and, as a result, a risk map comprising different risk classes was established. This risk map highlights the regions prone to become new foci for infection or that serves to maintain an existing focus. The research approach used attempts to introduce geotechnology, i.e. a social application in which better knowledge about these foci, designated endemic hot spots can assist preventive public intervention measures in a way that is inexpensive and easy to handle.

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Anaruma Filho, F., Sant’Ana, J. M., Ferreira dos Santos, R., & Castagna, C. L. (2010). Environmental inducers of schistosomiasis mansoni in Campinas, Brazil. Geospatial Health, 5(1), 79–91. https://doi.org/10.4081/gh.2010.189