03828nas a2200325   4500000000100000008004100001260003700042653001000079653002500089653001300114653002900127100001500156700001100171700001100182700001600193700001600209700001200225700001100237700001100248700001300259700001700272700001200289700001300301245014000314856007900454300000700533490000700540520294100547022001403488       2025                            d  bPublic Library of Science (PLoS)10aPemba10aIntervention Studies10aHotspots10aIntegrated interventions1 aTrippler L1 aAli SM1 aAli MN1 aMohammed UA1 aSuleiman KR1 aNdum NC1 aJuma S1 aAme SM1 aKabole F1 aHattendorf J1 aKnopp S1 aDowns JA00aAdaptive integrated intervention approaches for schistosomiasis elimination in Pemba: A 4-year intervention study and focus on hotspots  uhttps://journals.plos.org/plosntds/article?id=10.1371/journal.pntd.0013079  a230 v193 a<p><strong>Background</strong> Schistosomiasis is a disease of poverty. Integrated interventions are recommended for its elimination. Despite major prevalence reductions over the past decades, hotspot areas with persistent or recurring moderate or high prevalence remain. We aimed to assess the contribution of multidisciplinary interventions that were adapted to the local micro-epidemiology for schistosomiasis elimination in Pemba, Tanzania, and to identify drivers for the occurrence of hotspot areas.</p>

<p><strong>Methodology</strong> From 2020 to 2024, annual cross-sectional surveys were conducted in schools and communities in 20 implementation units (IUs) to assess the Schistosoma haematobium prevalence and monitor the impact of interventions. Based on the prevalence, the IUs were annually re-stratified into hotspot and low-prevalence IUs. In hotspots, mass drug administration in schools and communities, snail control and behavior change measures were implemented. Low-prevalence areas received surveillance-response interventions. With a random effects model, the association between S. haematobium infections and environmental and economic factors were assessed. Using risk layers based on the random effects model, hotspot areas were determined geographically.</p>

<p><strong>Principal findings</strong> The overall S. haematobium prevalence in the 20 IUs changed from 1.2% (26/2200, 95% Confidence Interval (CI): 0.5-1.9%) in 2021 to 1.0% (27/2752, 95% CI: 0.4-1.6%) in 2024 in schools, and from 0.8% (31/3885, 95% CI: 0.4-1.2%) in 2021 to 1.2% (43/3711, 95% CI: 0.3-2.0%) in 2024 in communities. Across the study period, 8 IUs were considered a hotspot. The number of hotspot IUs decreased from 5 in 2021, to 4 in 2022, to 3 in 2023 but increased again to 5 in 2024. Some of the hotspot IUs resurged once interventions were adapted to surveillance-response. S. haematobium infections were significantly associated with the standardized kernel density of water bodies with Bulinus presence (Odds Ratio (OR): 2.3; 95% CI: 1.6-3.4), a very low economic score (OR: 4.1; 95% CI: 1.7-9.9) and living far away from a road (OR: 4.7; 95% CI: 2.1-10.6).</p>

<p><strong>Conclusion</strong> Adaptive multidisciplinary interventions maintained the very low prevalence in Pemba but failed to interrupt S. haematobium transmission within 4 years. A comprehensive integrated intervention package contributed to reducing the number of hotspot IUs. However, some hotspots persisted also intense interventions or resurged once interventions were adapted to surveillance-response. To achieve complete elimination in Pemba and elsewhere, poverty needs to be reduced, and investments in global health equity, including the water sanitation and hygiene infrastructure, are essential.</p>

<p><strong>Trial registration</strong> ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493.</p>
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