Predicted distribution and burden of podoconiosis in Cameroon

Abstract

IntroductionUnderstanding the number of cases of podoconiosis, its geographical distribution and the population at risk are crucial to estimating the burden of this disease in endemic countries. We assessed each of these using nationwide data on podoconiosis prevalence in Cameroon.MethodsWe analysed data arising from two cross-sectional surveys in Cameroon. The dataset was combined with a suite of environmental and climate data and analysed within a robust statistical framework, which included machine learning-based approaches and geostatistical modelling. The environmental limits, spatial variation of predicted prevalence, population at risk and number of cases of podoconiosis were each estimated.ResultsA total of 214 729 records of individuals screened for podoconiosis were gathered from 748 communities in all 10 regions of Cameroon. Of these screened individuals, 882 (0.41%; 95% CI 0.38 to 0.44) were living with podoconiosis. High environmental suitability for podoconiosis was predicted in three regions of Cameroon (Adamawa, North West and North). The national population living in areas environmentally suitable for podoconiosis was estimated at 5.2 (95% CI 4.7 to 5.8) million, which corresponds to 22.3% of Cameroon’s population in 2015. Countrywide, in 2015, the number of adults estimated to be suffering from podoconiosis was 41 556 (95% CI, 1170 to 240 993). Four regions (Central, Littoral, North and North West) contributed 61.2% of the cases.ConclusionIn Cameroon, podoconiosis is more widely distributed geographically than was initially expected. The number of cases and the population at risk are considerable. Expanding morbidity management and follow-up of cases is of utmost necessity. Promotion of footwear use and regular foot hygiene should be at the forefront of any intervention plan.

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

“…Our model predicted environmental suitability for podoconiosis in many areas in Africa, with the strongest prediction largely in East, West and Central Africa Regions. In agreement with previous work, our model showed podoconiosis environmental suitability is largely influenced by annual precipitation, elevation, clay fraction and pH of the soil 17–19,36,47 . The novelty of this study was in translating suitability to the IU level: aggregated risk at the IU level aids in mapping podoconiosis.…”

“…regions/states, districts/zones). Health workers were trained to identify all cases of lymphoedema of lower limbs within the communities, and podoconiosis was subsequently confirmed by expert clinical diagnostic teams 18,19,47,48 . Therefore, we considered communities not reporting cases as ‘ true ’ absences and give them the same weight (1) as the presence records in the analysis.…”

“…Podoconiosis national programmes require a detailed understanding of the geographical distribution of the disease so that all endemic areas can be targeted. Previous attempts to map podoconiosis include a detailed literature review 12 and mapping at national 17,19,20 and subnational levels 24–26 . However, there are no maps outlining the potential distribution of podoconiosis at higher geographical levels.…”

“…In the current investigation, we aimed to predict the environmental limits of podoconiosis across the African continent, using available data from field surveys and other sources, and empirical evidence of its distribution 17–19,28 . Building on methods used to map the distribution of podoconiosis in known endemic countries, we developed a model to outline the environmental suitability across Africa.…”

Measuring the spatial heterogeneity on the reduction of vaginal fistula burden in Ethiopia between 2005 and 2016

“…This instrument measures visible and infrared radiation emitted at night-time, resulting in remote imagery of lights on the ground. This information has been correlated with gross domestic product in developed countries [35][36][37] and, although far from precise, would provide an indirect measure of poverty in developing countries 38,39 .…”