# Precision mapping of Schistosoma mansoni risk for targeted public health control and elimination > **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $701,991 ## Abstract PROJECT SUMMARY Schistosomiasis is a neglected tropical parasitic disease that infects over 150 million people in low- and middle-income countries. WHO has targeted schistosomiasis for elimination as a public health problem by 2030 but is not on track due to geographically focal areas of persistent endemicity, especially hot spots of high Schistosoma prevalence. After decades of the longstanding public health strategy of mass drug administration (MDA), endemic areas and hot spots are often geographically focal and missed by the standard district-level prevalence surveys that inform MDA decisions. More granular prevalence mapping to inform targeted MDA is limited by: (1) inefficient diagnostics (i.e., stool microscopy) that are slow, insensitive, and prohibitively resource intensive; and (2) lack of understanding of the optimal geographic scale (i.e., district, sub-district, community) for mapping and MDA implementation. Our broad, long-range goal is to evaluate whether more geographically precise mapping with newer diagnostics for targeted MDA, including more intensive efforts in hot spots, can improve schistosomiasis control while being cost-effective. Our proposal will evaluate a novel ‘rapid mapping strategy’ that will compare two rapid, sensitive lateral flow urine antigen tests: (1) WHO endorsed semi-quantitative POC-CCA; and (2) fully quantitative UCP-LF-CAA, in an innovative pooled sampling strategy, which is supported by our preliminary data. Our application will leverage a decade-long, productive collaboration in Côte d'Ivoire and includes a multi-disciplinary team that merges expertise across epidemiology, diagnostics, mathematical modeling, cost-effectiveness analysis, clinical medicine, and policy. In Aim 1, we will evaluate rapid urine antigen tests with pooled sampling for identification of endemic and hot spot locations of Schistosoma mansoni prevalence for improved surveillance. We will test pooled urine samples with two rapid antigen tests (qualitative POC-CCA, pool size 4-8; highly sensitive and quantitative UCP-LF- CAA, pool size 5-10), using a one-stage (pooling only) and two-stage system, in comparison to WHO- recommended thresholds for being an endemic or hot spot location. In Aim 2, we will apply a geospatial model of S. mansoni prevalence and project the impact and cost-effectiveness of implementing surveillance, including the rapid mapping strategies, and MDA against S. mansoni at more granular geographic scales (sub-district, community-level), compared to current standard district-level decisions. We will develop an open-source modeling tool to guide optimal mapping for schistosomiasis, which may be used by national MDA programs across endemic countries. This proposal’s aim to evaluate new rapid mapping strategies to guide precise intervention against schistosomiasis will support the 2030 WHO goal of eliminating schistosomiasis as a public health problem. ## Key facts - **NIH application ID:** 10978140 - **Project number:** 1R01AI179771-01A1 - **Recipient organization:** STANFORD UNIVERSITY - **Principal Investigator:** Nathan Lo - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $701,991 - **Award type:** 1 - **Project period:** 2024-06-05 → 2029-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10978140 ## Citation > US National Institutes of Health, RePORTER application 10978140, Precision mapping of Schistosoma mansoni risk for targeted public health control and elimination (1R01AI179771-01A1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10978140. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*