Socio-ecological heterogeneity and uncertainty in the elimination of human schistosomiasis

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Abstract

Schistosomiasis is a neglected tropical disease caused by parasitic flatworms which infect approximately 240 million people worldwide living in poverty, mostly in sub-Saharan Africa. The World Health Organization (WHO) aims to eliminate schistosomiasis by 2030, predominantly relying on a strategy of mass drug administration (MDA) using praziquantel. The effectiveness of MDA can vary widely among disease foci. Mathematical modelling is increasingly being used to understand the transmission dynamics of schistosomiasis and for predicting the effectiveness of MDA and time frames to elimination. Due to the highly focal nature of schistosomiasis, many key parameters influencing its transmission are likely highly geographically variable. Yet typically models do not fully integrate this uncertainty into predictions. This can lead to unrealistic expectations on the prospects for elimination. Here, we present a schistosomiasis transmission model to evaluate how uncertainty in parameters relating to local socio-ecological conditions influence resilience of the parasite population to intervention and the effectiveness of MDA. We discuss the growing importance of incorporating uncertainty in mathematical models for this and other NTDs to enable transparent communication of predictions as we move towards the 2030 elimination goals.

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