Estimating and mapping the population at risk of sleeping sickness

Abstract

Background: Human African trypanosomiasis (HAT), also known as sleeping sickness, persists as a public health problem in several sub-Saharan countries. Evidence-based, spatially explicit estimates of population at risk are needed to inform planning and implementation of field interventions, monitor disease trends, raise awareness and support advocacy. Comprehensive, geo-referenced epidemiological records from HAT-affected countries were combined with human population layers to map five categories of risk, ranging from "very high" to "very low," and to estimate the corresponding at-risk population.

Results: Approximately 70 million people distributed over a surface of 1.55 million km(2) are estimated to be at different levels of risk of contracting HAT. Trypanosoma brucei gambiense accounts for 82.2% of the population at risk, the remaining 17.8% being at risk of infection from T. b. rhodesiense. Twenty-one million people live in areas classified as moderate to very high risk, where more than 1 HAT case per 10,000 inhabitants per annum is reported.

Discussion: Updated estimates of the population at risk of sleeping sickness were made, based on quantitative information on the reported cases and the geographic distribution of human population. Due to substantial methodological differences, it is not possible to make direct comparisons with previous figures for at-risk population. By contrast, it will be possible to explore trends in the future. The presented maps of different HAT risk levels will help to develop site-specific strategies for control and surveillance, and to monitor progress achieved by ongoing efforts aimed at the elimination of sleeping sickness.

Figure 1. Three-dimensional rendering of the disease intensity surface for one case of HAT, as derived from spatial smoothing (Kernel function k(·): quadratic; bandwidth τ: 30 km; output resolution: 1 km).

Figure 2. The foci of Bodo-Moissala in Chad and Batangafo-Maitikoulou in Central African Republic.

(a) Distribution of HAT cases; (b) Average population distribution (Landscan); (c) Annual intensity of HAT cases as derived from (a) through spatial smoothing; (d) Population intensity as derived from (b) through spatial smoothing.

Figure 3. The risk of T. b. gambiense infection in central Africa (2000–2009).

Figure 4. The risk of T. b. gambiense infection in western Africa (2000–2009).

Figure 5. The risk of T. b. rhodesiense infection in eastern and southern Africa (2000–2009).