Optimising cluster survey design for planning schistosomiasis preventive chemotherapy

Background: The cornerstone of current schistosomiasis control programmes is delivery of praziquantel to at-risk populations. Such preventive chemotherapy requires accurate information on the geographic distribution of infection, yet the performance of alternative survey designs for estimating prevalence and converting this into treatment decisions has not been thoroughly evaluated. Methodology/Principal findings: We used baseline schistosomiasis mapping surveys from three countries (Malawi, Côte d’Ivoire and Liberia) to generate spatially realistic gold standard datasets, against which we tested alternative two-stage cluster survey designs. We assessed how sampling different numbers of schools per district (2–20) and children per school (10–50) influences the accuracy of prevalence estimates and treatment class assignment, and we compared survey cost-efficiency using data from Malawi. Due to the focal nature of schistosomiasis, up to 53% simulated surveys involving 2–5 schools per district failed to detect schistosomiasis in low endemicity areas (1–10% prevalence). Increasing the number of schools surveyed per district improved treatment class assignment far more than increasing the number of children sampled per school. For Malawi, surveys of 15 schools per district and 20–30 children per school reliably detected endemic schistosomiasis and maximised cost-efficiency. In sensitivity analyses where treatment costs and the country considered were varied, optimal survey size was remarkably consistent, with cost-efficiency maximised at 15–20 schools per district. Conclusions/Significance: Among two-stage cluster surveys for schistosomiasis, our simulations indicated that surveying 15–20 schools per district and 20–30 children per school optimised cost-efficiency and minimised the risk of under-treatment, with surveys involving more schools of greater cost-efficiency as treatment costs rose. Author summary: Many countries are currently scaling up efforts to control schistosomiasis, a helminthic disease for which preventive chemotherapy with praziquantel is the main control tool. In order to apply WHO guidelines on how frequently to treat a given district or similar geographic unit for schistosomiasis, survey-based estimates of infection prevalence are required. However, the optimal size and design of survey for generating such data is not clear, and there is a clear trade-off between accuracy and cost–larger surveys provide more accurate information with which to target treatment, but cost more to carry out. Here, we systematically assess what size and design of simple 2-stage cluster survey (where primary school children are tested for infection), might best enable control programmes to implement WHO treatment guidelines. We use empirical data on schistosomiasis distribution from three African countries together with computer simulations to compare survey performance, in terms of accuracy and cost-efficiency–the ability of a survey to accurately determine treatment frequency, per unit cost. We show that although small surveys of around 5 schools per district are frequently adopted for mapping schistosomiasis, such small surveys are prone to miss endemic schistosomiasis fairly often, and are also not cost efficient. Our results suggest that among the designs tested, surveys involving 15–20 schools per district optimise cost-efficiency, providing the most accurate treatment decisions per dollar spent. These findings have important implications for the schistosomiasis control community, and provide the first evidence-based suggestion of a simple survey design for mapping schistosomiasis in endemic countries.