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

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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement MIN acknowledges funding from a Royal Veterinary College, University of London PhD Studentship. GCM, JPW and MW were supported through the FibroScHot project which is part of the EDCTP2 programme supported by the European Union (RIA2017NIM-1842-FibroScHot). MW acknowledges funding by the Bill & Melinda Gates Foundation through the NTD Modelling Consortium (grant INV-030046). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The model code used to produce the results from this work can be found at https://github.com/martwalker/simpleschisto