Abstract
Schistosomiasis remains of considerable public health concern in many tropical and subtropical regions of the world, including the People's Republic of China (P.R. China). The effectiveness of schistosomiasis control interventions are, among other factors, governed by the social-ecological context. However, eco-social determinants of schistosomiasis are poorly understood, particularly at the household or village levels. In the current study, residents in 26 villages of Eryuan county, Yunnan province, P.R. China, were screened for Schistosoma japonicum infection with a serological assay that was followed by stool examination for sero-positive individuals. Bayesian multilevel models with spatial random effects were employed to profile the S. japonicum infection risk based on known transmission sites of S. japonicum that are scattered across individual land parcels in this part of the country. The key risk factors identified with this approach were the absence of a sanitary stall house for livestock and presence of living and infected intermediate host snails in close proximity. We conclude that a spatially explicit Bayesian multilevel approach can deepen our understanding of eco-social determinants that govern schistosomiasis transmission at a small geographical scale.
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