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March 6, 2026BMJ Global Health1 citationsOpen Access

Prevalence, spatial and temporal distribution of tungiasis in the Kilifi Health and Demographic Surveillance System (KHDSS) in Kenya

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NONelson OumaSMSamuel K. MuchiriCNChristopher Nyundo

Key Points

  • To investigate the prevalence and spatial distribution of tungiasis and its environmental predictors in Kilifi, Kenya.
  • Conducted surveys among 90,257 households in Kilifi from May 2021 to May 2022.
  • Collected geospatial data and assessed household cases of tungiasis during three survey rounds.
  • Applied multilevel logistic regression models to analyze associations with environmental and ecological factors.
  • 1.5% of households reported tungiasis at least once during the surveys, with prevalence decreasing over the rounds.
  • Households with earthen floors, rural location, and more children had higher odds of tungiasis.
  • Macrolevel factors like population density, rainfall, and soil quality influenced tungiasis distribution, explaining 23.9% of its variability.

Abstract

Introduction Tungiasis is a highly neglected tropical disease of the skin caused by an embedded female sand flea affecting the most resource-poor communities in sub-Saharan Africa, the Caribbean and South America. The global disease burden is unknown and systematic, fine-resolution spatial data on prevalence and environmental and ecological risk factors are rare. Methods We leveraged the Kilifi Health and Demographic Surveillance System of 90 257 households and asked whether they had a case of tungiasis in the household at interview during three survey rounds of routine surveys, undertaken between May 2021 and May 2022. Precise geospatial data to locate households were matched to macrolevel environmental, ecological and soil covariates, and multilevel logistic regression models were used to test for associations. Results A total of 1376 (1.5%) households reported a case in at least one survey during the year, while only 25 households did for all three surveys. The prevalence decreased over the three rounds from 1.1%, through 0.5–0.2%. The odds of having a tungiasis case in a household were higher in houses with earthen floors and walls, and in rural locations. The odds increased with increases in the number of children in a household and with population density (within 1 km radius), rainfall, Enhanced Vegetation Index, land surface temperature, aridity, altitude and organic carbon in the soil. However, the odds of having a tungiasis case in a household decreased with increasing aluminium content in the soil. These factors accounted for 23.9% of the variability in tungiasis distribution by household. Conclusion Tungiasis distribution was heterogenous and changed over time. Macro level environmental factors predicted the niche maps for tungiasis and could have applications in guiding local surveys and interventions.

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Cite This Study

Ouma et al. (2026) studied this question.

synapsesocial.com/papers/69aa70d6531e4c4a9ff5b0achttps://doi.org/10.1136/bmjgh-2025-020057
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