Journal
TRANSACTIONS OF THE ROYAL SOCIETY OF TROPICAL MEDICINE AND HYGIENE
Volume 117, Issue 2, Pages 72-82Publisher
OXFORD UNIV PRESS
DOI: 10.1093/trstmh/trac092
Keywords
geostatistical modelling; Kenya; podoconiosis; risk; spatial analysis
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This study used nationwide survey data in Kenya to predict the environmental suitability, population at risk, and number of cases of podoconiosis. The results showed that the burden of podoconiosis in Kenya is relatively low and mostly restricted to specific geographic areas. The findings can guide targeted prevention and treatment approaches in the local context.
Background Understanding and accurately predicting the environmental limits, population at risk and burden of podoconiosis are critical for delivering targeted and equitable prevention and treatment services, planning control and elimination programs and implementing tailored case finding and surveillance activities. Methods This is secondary analysis of a nationwide podoconiosis mapping survey in Kenya. We combined national representative prevalence survey data of podoconiosis with climate and environmental data, overlayed with population figures in a geostatistical modelling framework, to predict the environmental suitability, population living in at-risk areas and number of cases of podoconiosis in Kenya. Results In 2020, the number of people living with podoconiosis in Kenya was estimated to be 9344 (95% uncertainty interval 4222 to 17 962). The distribution of podoconiosis varies by geography and three regions (Eastern, Nyanza and Western) represent >90% of the absolute number of cases. High environmental suitability for podoconiosis was predicted in four regions of Kenya (Coastal, Eastern, Nyanza and Western). In total, 2.2 million people live in at-risk areas and 4.2% of the total landmass of Kenya is environmentally predisposed for podoconiosis. Conclusions The burden of podoconiosis is relatively low in Kenya and is mostly restricted to certain small geographical areas. Our results will help guide targeted prevention and treatment approaches through local planning, spatial targeting and tailored surveillance activities.
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