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

Bibliographic Data

ID21880068
AuthorsNelson Ouma (0000-0002-5889-9536, Kenya Medical Research Institute), Samuel K Muchiri (0000-0003-4028-4346, Kenya Medical Research Institute), Christopher Nyundo (0000-0003-4046-7476, Kenya Medical Research Institute), David Walumbe (Kenya Medical Research Institute), Amek Nyaguara (0000-0002-7865-8756, Kenya Medical Research Institute), Marta Maia (0000-0003-1645-7550, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya), Marta F Maia (0000-0003-3302-5610, Kenya Medical Research Institute), Ifedayo Adetifa (0000-0003-2556-9407, Kenya Medical Research Institute), Benedict Orindi (0000-0002-4601-7890, Kenya Medical Research Institute), Phillip Bejon (Kenya Medical Research Institute), Ulrike Fillinger (0000-0002-4037-431X, International Centre of Insect Physiology and Ecology), Lynne Elson (0000-0003-2264-4459, Kenya Medical Research Institute)
Year2026
Volume11
Issue3
Pagese020057
Publication date2026-03-01
Open AccessYes
TypeARTICLE
VenueBMJ Global Health (JOURNAL)
Journal identifiersISSN: 2059-7908 • E-ISSN: 2059-7908
PublisherBMJ (PUBLISHER • GB)
DOI10.1136/bmjgh-2025-020057
PMID41781022
OpenAlexW7133549402
LanguageEN
References cited28

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

Logistic regression · Odds · Odds ratio · Population · Public health · Rural area · Dermatological diseases and infestations · Nail Diseases and Treatments · Syphilis Diagnosis and Treatment · Epidemiology

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