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Peer reviewedOpen accessSchistosomiasis

Adaptive integrated intervention approaches for schistosomiasis elimination in Pemba: A 4-year intervention study and focus on hotspots

PLOS Neglected Tropical Diseases·

Lydia Trippler, Said Mohammed Ali, Mohammed Nassor Ali, Ulfat Amour Mohammed, Khamis Rashid Suleiman, Naomi Chi Ndum, Saleh Juma, Shaali Makame Ame, Fatma Kabole, Jan Hattendorf, Stefanie Knopp

DOI
10.1371/journal.pntd.0013079
PMID
40455753
PMCID
PMC12129218
OpenAlex
W4410950572
Study type
Cross-sectional study
Publisher
Public Library of Science (PLoS)
Article type
journal-article
Integrity
current

Why this research matters now

The study demonstrates that adaptive multidisciplinary interventions can maintain very low schistosomiasis prevalence but may not achieve transmission interruption within a four-year period. Persistent and resurgent hotspots highlight that elimination efforts require sustained comprehensive intervention packages and broader investments in poverty reduction and water, sanitation, and hygiene infrastructure to achieve equity in global health.

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Structured evidence summary

Research question

The study assessed whether multidisciplinary interventions adapted to local micro-epidemiology could achieve schistosomiasis elimination in Pemba, Tanzania, and sought to identify drivers of persistent hotspot areas.

Study design

Annual cross-sectional surveys were conducted in schools and communities across 20 implementation units from 2020 to 2024. Implementation units were stratified annually by prevalence into hotspots receiving mass drug administration, snail control, and behavior change interventions, or low-prevalence areas receiving surveillance-response. A random effects model examined associations between infection and environmental and economic factors.

Population and setting

The study was conducted in 20 implementation units in Pemba, Tanzania, enrolling school-aged children and community members in areas with varying schistosomiasis prevalence and environmental and economic conditions.

Main findings

Overall S. haematobium prevalence remained very low throughout the study period, changing from 1.2% to 1.0% in schools and 0.8% to 1.2% in communities between 2021 and 2024. The number of hotspot implementation units fluctuated, decreasing from 5 in 2021 to 3 in 2023 before rising again to 5 in 2024, with some hotspots resurging when interventions shifted to surveillance-response. Infection was significantly associated with higher kernel density of water bodies containing Bulinus snails, very low economic score, and living far from roads.

Public-health relevance

The study demonstrates that adaptive multidisciplinary interventions can maintain very low schistosomiasis prevalence but may not achieve transmission interruption within a four-year period. Persistent and resurgent hotspots highlight that elimination efforts require sustained comprehensive intervention packages and broader investments in poverty reduction and water, sanitation, and hygiene infrastructure to achieve equity in global health.

Important limitations

The authors note that adaptive multidisciplinary interventions failed to interrupt transmission within four years, and some hotspots persisted despite intense interventions or resurged when intervention intensity was reduced. This summary is limited to the supplied single-article abstract and metadata; the original paper is required for decision-grade interpretation of study limitations including potential selection bias, intervention fidelity, generalizability, and measurement validity.

GIDS interpretation

This article would be discoverable in surveillance systems monitoring schistosomiasis in Tanzania or tracking intervention effectiveness for neglected tropical diseases. The classifier links to schistosomiasis, Tanzania, and topics including climate and environment, surveillance, and transmission dynamics reflect the study's focus on hotspot persistence and environmental drivers. The presence of this metadata aids in systematic retrieval for evidence synthesis but does not imply that surveillance data confirm the study findings.

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Related GIDS surveillance

Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.

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Evidence relationships

This article has 9 auditable classifier relationships to diseases, places, topics, and study design.

about diseaseaddresses topicaddresses topicaddresses topicstudied instudied population settingstudies populationstudies populationuses study design