ArticlePLoS neglected tropical diseases2025
Seroprevalence and geospatial epidemiology of yaws: Evidence from Ghana.
Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Recent advances in machine learning and Bayesian modeling for tropical disease prediction, diagnosis, and risk analysis: a scoping review.BMC infectious diseases · 2026Article
- Community awareness, symptom recognition, and perceived causes of skin neglected tropical diseases in selected regions of Ghana.Frontiers in public health · 2026Article
- Article
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12 authors.
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Abstract
backgroundYaws, a neglected tropical disease caused by Treponema pallidum subsp. pertenue remains a public health challenge in endemic regions. Although the World Health Organization (WHO) has earmarked yaws for eradication by the year 2030, there is a dearth of accurate epidemiological data to facilitate eradication efforts. The WHO recommends the use of seroprevalence surveys and geospatial analysis to guide planned interventions. METHODOLOGY AND
findingsWe conducted a cross-sectional study in Wassa Amenfi East and Aowin districts in Ghana, clinically screening 11,505 school children for yaws. Treponemal Rapid Diagnostic Test (RDTs) detected 117 individuals, and the Dual Path Platform (DPP) confirmed 73 cases, giving an overall prevalence of 0.63%; and 3.85% for Aowin district compared to 0.31% for the Wassa Amenfi East district. Prevalence among RDT-tested was 7.79%, (34.54% from Aowin and 4.42% from Wassa Amenfi East) and DPP seroprevalence was 62.39% (Aowin, 70.69% and Wassa Amenfi East, 54.24%). A prevalence rate of 0.02% for latent infection was recorded in Wassa Amenfi East. Spatial analysis employing multiple mapping techniques including spatial autocorrelation analysis (Moran's I), kriging, nearest neighbour analysis, and kernel density estimation using data from the surveyed communities indicated significantly clustered hotspots in Aowin's central and Wassa Amenfi East's southeastern part. Kriging interpolation with barriers and Empirical Bayesian kriging revealed consistent spatial trends in unsurveyed communities in the study area.
conclusionThis study found an overall yaws prevalence of 0.63% but with significantly clustered hotspots in some parts of the districts. The findings from this study highlight the importance of serosurveys and geospatial modeling in generating critical data to guide surveillance, education, and mass drug administration (MDA) efforts in endemic regions to support the WHO's goal of eradicating yaws by 2030.
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