Geostatistical modelling of the distribution, risk and burden of podoconiosis in Kenya. (21st September 2022)

• Record Type: Journal Article
• Authors: Deribe, Kebede; Sultani, Hadley Matendechero; Okoyo, Collins; Omondi, Wyckliff P; Ngere, Isaac; Newport, Melanie J; Cano, Jorge
• Is Part Of: Transactions of the Royal Society of Tropical Medicine and Hygiene. Volume 117:Number 2(2023)
• Page Start: 72
• Page End: 82
• Publication Date: 2022-09-21
• Subjects: geostatistical modelling, Kenya -- podoconiosis -- risk -- spatial analysis; Tropical medicine -- Periodicals; 616.9883
• DOI: 10.1093/trstmh/trac092
• Languages: English
• ISSNs: 0035-9203

Abstract

Abstract: 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.