Optimizing the survey design for assessing schistosomiasis at the sub-district for treatment decision making
Year: 2024
Type: article
Abstract: BACKGROUND: Schistosomiasis control programs typically launch with district-level, school-based preventive chemotherapy (PC). Recent World Health Organization recommendations are to shift to community-wide treatment where schistosomiasis prevalence is >10%. Simultaneously there is a push to move to sub-district PC to prioritize communities in need of treatment and alleviate the pressure on global praziquantel need, but few countries have sub-district prevalence data and no guidelines on how to collect this information. METHODS/PRINCIPAL FINDINGS: Data collected from 57,161 school-aged children (SAC) across six countries (Burkina Faso, Ghana, Mali, Senegal, Sierra Leone, and Togo) to generate spatially realistic gold standard datasets that were used to evaluate different numbers of schools per sub-district (1-10) and district (5-30), number of SAC sampled per school (10-50), on accuracy of prevalence estimates. Sampling fewer children in more schools maximized accuracy of prevalence at the sub-district and district level. Surveying three schools per sub-district or 15 schools per district gave precise prevalence estimates. Increasing the number of SAC beyond 30 per school led to negligible improvements in reliably detecting schistosomiasis. Failure to detect schistosomiasis occurred more frequently in low (1-10%) prevalence and larger districts/sub-districts. CONCLUSION: This study provides guidelines for evaluating sub-district schistosomiasis in a range of transmission settings. Among two-stage cluster surveys for schistosomiasis, our simulations show surveying three schools per sub-district and 20-30 SAC per school optimized cost-efficiency and minimized risk of mistreatment. Population size and endemicity influenced survey estimates, with the probability of misclassification being greater as populations increased or prevalence decreased.
Source: Acta Tropica
Authors: AE Phillips, L Klein, M Dorkenoo, J Opare, P Gnossike, SCL Knowles, DM Stukel, Y Zhang, A Kabore, C Bougouma, I Kargbo-Labor, NM Kane, M Traoré, J Shott, DS Evans
Institutions: Family Health International 360, University of Lomé, Ghana Health Service, Togolese Ministry of Health, University of Oxford, Helen Keller International, Ministère De La Santé, Ministry of Health and Sanitation, Ministère de la Santé Publique et Action Sociale, Ministère de la Santé et de l'Hygiène Publique, United States Agency for International Development
Language: English
Subfield: Parasitology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,070
OpenAlex ID: W4403527271
