Optimising cluster survey design for planning schistosomiasis preventive chemotherapy

Knowles, S C L; Sturrock, H J W; Turner, H; Whitton, J M; Gower, C M; Jemu, S; Phillips, A E; Meite, A; Thomas, B; Kollie, K; Thomas, C; Rebollo, M P; Styles, B; Clements, M; Fenwick, A; Harrison, W E; Fleming, F M

Abstract

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.

Citation

Knowles, S. C. L., Sturrock, H. J. W., Turner, H., Whitton, J. M., Gower, C. M., Jemu, S., …Fleming, F. M. (2017). Optimising cluster survey design for planning schistosomiasis preventive chemotherapy. PLoS Neglected Tropical Diseases, 11(5), https://doi.org/10.1371/journal.pntd.0005599

• Journal Article Type: Article
• Acceptance Date: Apr 26, 2017
• Publication Date: May 26, 2017
• Deposit Date: Jul 19, 2017
• Publicly Available Date: Jul 19, 2017
• Journal: PLOS NEGLECTED TROPICAL DISEASES
• Print ISSN: 1935-2727
• Publisher: Public Library of Science
• Peer Reviewed: Peer Reviewed
• Volume: 11
• Issue: 5
• DOI: https://doi.org/10.1371/journal.pntd.0005599
• Public URL: https://rvc-repository.worktribe.com/output/1391745