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In 2020, WHO recognised the importance of strongyloidiasis alongside soil-transmitted helminths (STH) in their 2021–30 roadmap, which aspires to target Strongyloides stercoralis with preventive chemotherapy by use of ivermectin. Combination treatment with both albendazole, the primary drug used to treat STH, and ivermectin, would improve the efficiency of mass drug administration targeting both STH and S stercoralis. In this Personal View, we discuss the challenges and opportunities towards the development of an efficient control programme for strongyloidiasis, particularly if it is to run concurrently with STH control. We argue the need to define the prevalence threshold to implement preventive chemotherapy for S stercoralis, the target populations and optimal dosing schedules, and discuss the added benefits of a fixed-dose coformulation of ivermectin and albendazole. Implementation of an efficient control programme will require improvements to current diagnostics, and validation of new diagnostics, to target and monitor S stercoralis infections, and consideration of the challenges of multispecies diagnostics for S stercoralis and STH control. Finally, the evolution of ivermectin resistance represents a credible risk to control S stercoralis; we argue that genome-wide approaches, together with improved genome resources, are needed to characterise and prevent the emergence of resistance. Overcoming these challenges will help to reduce strongyloidiasis burden and enhance the feasibility of controlling it worldwide.

Background: Schistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at districts or larger spatial units. Improved mapping strategies are required to accurately and cost-effectively target preventive chemotherapy to remaining foci across all possible spatial distributions of schistosomiasis. Methods: Here, we use geostatistical models to quantify the spatial heterogeneity of Schistosoma haematobium and S. mansoni across sub-Saharan Africa using the most comprehensive dataset available on school-based surveys. Applying this information to parameterise simulations, we assess the accuracy and cost of targeting alternative implementation unit sizes across the range of plausible schistosomiasis distributions. We evaluate the consequences of decisions based on survey designs implemented at district and subdistrict levels sampling different numbers of schools. Cost data were obtained from field surveys conducted across multiple countries and years, with cost effectiveness evaluated as the cost per correctly identified school. Results: Models identified marked differences in prevalence and spatial distributions between countries and species; however, results suggest implementing surveys at subdistrict level increase the accuracy of treatment classifications across most scenarios. While sampling intensively at the subdistrict level resulted in the highest classification accuracy, this sampling strategy resulted in the highest costs. Alternatively, sampling the same numbers of schools currently recommended at the district level but stratifying by subdistrict increased cost effectiveness. Conclusions: This study provides a new tool to evaluate schistosomiasis survey designs across a range of transmission settings. Results highlight the importance of consideri