Predicting the Environmental Suitability and Population at Risk of Podoconiosis in Africa

Abstract

BackgroundPodoconiosis is a type of tropical lymphedema that causes massive swelling of the lower limbs. The disease is associated with both economic insecurity, due to long-term morbidity-related loss of productivity, and intense social stigma. The geographical distribution and burden of podoconiosis in Africa is uncertain.MethodsWe applied statistical modelling to the most comprehensive database compiled to date to predict the environmental suitability of podoconiosis in the African continent. By combining climate and environmental data and overlaying population figures, we predicted the suitability and human population at risk.ResultsIn Africa, environmental suitability for podoconiosis was predicted in 29 countries. By 2020, the total population in areas suitable for podoconiosis was estimated at 114.5 million people, (95% confidence interval: 109.4-123.9) with 16.9 million in areas suitable for both lymphatic filariasis and podoconiosis. Of the total 5,712 implementation units defined by WHO in Africa, 1,655 (29.0%) were found to be environmentally suitable for podoconiosis. The majority of IUs with high environmental suitability are located in Angola (80 IUs), Cameroon (170 IUs), the DRC (244 IUs), Ethiopia (495 IUs), Kenya (217 IUs), Uganda (116 IUs) and Tanzania (112 IUs). Of the 1,655 environmental suitable IUs, 960 (58.0%) require more detailed community-level mappingConclusionsOur estimates provide key evidence of the population at risk and geographical extent of podoconiosis in Africa, which will help decision-makers to better plan more integrated intervention programmes.

A geopositioned, evidence-graded, pan-species compendium of Mayaro Virus occurrence

“…However, any reports of disease absence must be considered carefully as true absence is difficult to establish and false absence data can result in miscalibration of distribution models 28 . Ideally, representative country-wide surveys should be used to ascertain "true" absence locations that can be used in subsequent modelling efforts 29,30 .…”