Evidence based targeting of districts for active surveillance of skin-related neglected tropical diseases in Ghana

Bibliographic Data

ID19593553
AuthorsWilliam Jones-Warner (0000-0002-5619-9763, London School of Hygiene & Tropical Medicine, corresponding author), Yaw Ampem Amoako (0000-0002-4642-789X, Kwame Nkrumah University of Science and Technology), Joseph Opare (Ghana Health Service), Nana Konama Kotey (Ghana Health Service), Dorothy Yeboah-Manu (University of Ghana), Richard Odame Phillips (0000-0001-8992-0222, Kwame Nkrumah University of Science and Technology), Rachel Pullan (London School of Hygiene & Tropical Medicine), Rachel L Pullan (0000-0001-9844-1362), Hope Simpson (0000-0002-2956-5342, Brighton and Sussex Medical School)
EditorsJulia Robinson (0000-0003-0719-3995)
Year2026
Volume6
Issue3
Pagese0006074
Publication date2026-03-27
Open AccessYes
TypeARTICLE
VenuePLOS Global Public Health (JOURNAL)
Journal identifiersISSN: 2767-3375 • E-ISSN: 2767-3375
PublisherPublic Library of Science (PLoS) (PUBLISHER)
DOI10.1371/journal.pgph.0006074
PMID41894359
OpenAlexW7141300531
LanguageEN
References cited37

To improve control and management of skin-neglected tropical diseases (NTDs), district-level integration of case finding and management is recommended. However, these strategies are costly and should be targeted to co-endemic areas. Identifying districts with high burdens of undiagnosed cases, particularly where access to healthcare is limited, can better direct efforts. We developed an evidence consensus framework—a structured decision-making approach that combines information from multiple sources to support decision-makers. Using this approach, we built an interactive dashboard that brings together data on factors such as indicators of disease endemicity from model predictions, population vulnerability to disease, access to and availability of health services, and risk factors for poor clinical outcomes. Each factor is given a score, which is then adjusted so that no single type of information outweighs the others. Districts were scored and ranked based on levels of each indicator, and districts scoring highest across combined criteria were identified. We visualised results on an interactive dashboard, or webpage, intended for use by decision-makers in NTD programs in Ghana. We identified 108 districts potentially endemic for both Buruli ulcer (BU) and lymphatic filariasis (LF). Of these, 17 districts ranked in the highest quintile for overall score and were deemed suitable for active case detection of skin NTDs. Notably, Pru East, Shama, and Nzema East scored highest, despite mixed BU endemicity. Six districts, including Shama, Awutu Senya East, and Ekumfi, scored high for both BU and LF, making them priority areas for active BU detection. This evidence-based framework offers a practical method for integrating datasets to guide surveillance and decision-making in skin NTDs. It emphasizes prioritizing districts with high overall scores and predicted LF or BU prevalence, while addressing gaps in knowledge about BU risk factors. By simplifying data integration, this framework enhances surveillance efforts, improving coverage and resource allocation

Dashboard · Disease burden · Evidence-based practice · Neglected tropical diseases · Population · Public health · Tropical disease · Vulnerability (computing) · Dermatological diseases and infestations · Parasites and Host Interactions · Parasitic Diseases Research and Treatment

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