# Seroprevalence and geospatial epidemiology of yaws: Evidence from Ghana

## TL;DR

This study in Ghana finds yaws prevalence and hotspots using blood tests and maps to help the WHO's 2030 eradication goal.

## Contribution

The study provides geospatial insights and seroprevalence data to guide targeted interventions for yaws eradication.

## Key findings

- Overall yaws prevalence was 0.63% with higher rates in Aowin district.
- Geospatial analysis identified clustered hotspots in central Aowin and southeastern Wassa Amenfi East.
- Seroprevalence was 7.79% with RDTs and 62.39% with DPP tests.

## Abstract

Yaws, 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.

We 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.

This 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.

Yaws is a skin disease caused by the bacterium Treponema pallidum subsp. pertenue and mostly affects people in poor, tropical areas. It is transmitted from one person to the other through direct skin contact with an affected person. Yaws is still a major health problem in places where it is common, and although children are the most affected, all age groups can be affected. The World Health Organization (WHO) wants to completely wipe out the disease by the year 2030. To do this, we need to know exactly how many people have the disease and where they are. This means using the right diagnostic tools in communities and schools to actively look for both those who have the disease and are showing signs, and those who have the disease but are without signs. However, many countries only report cases based on clinical signs without proper testing. To properly fight and end yaws, we need more accurate information. The WHO recommends using blood tests (seroprevalence surveys) and maps (geospatial analysis) to understand how common the disease is in different areas. This will help endemic communities plan better and track their progress over time. In our study, we found an overall yaws prevalence of 0.63%. Seroprevalence among RDT-tested was 7.79% 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 using data from the surveyed communities revealed significantly clustered hotspots in Aowin’s central and Wassa Amenfi East’s southeastern part. We found consistent spatial trends in unsurveyed communities in the study area.

Our findings show 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.