Trypanosomiasis Control, Democratic Republic of Congo, 1993–2003

World Health Organization WHO, Genève, Geneva, Switzerland
Emerging infectious diseases (Impact Factor: 6.75). 10/2005; 11(9):1382-8. DOI: 10.3201/eid1109.041020
Source: PubMed


In the Democratic Republic of Congo (DRC), human African trypanosomiasis (HAT) reached unprecedented levels in the 1990s. To assess recent trends and evaluate control efforts, we analyzed epidemiologic and financial data collected by all agencies involved in HAT control in DRC from 1993 to 2003. Funds allocated to control populations, as well as to the population screened, doubled from 1993 to 1997 and from 1998 to 2003. The number of cases detected decreased from 26,000 new cases per year in 1998 to 11,000 in 2003. Our analysis shows that HAT control in DRC is almost completely dependent on international aid and that sudden withdrawal of such aid in 1990 had a long-lasting effect. Since 1998, control efforts intensified because of renewed donor interest, including a public-private partnership, and this effort led to a major reduction in HAT incidence. To avoid reemergence of this disease, such efforts should be sustained.

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Available from: Pascal Lutumba, Mar 25, 2014
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    • "In the Democratic Republic of Congo (DRC), the estimated detected fraction (including treatment) was <50% in most scenarios, and between 30% and 65% attended and were correctly diagnosed [23]. Screening coverage was 22-98% in other DRC sites (average 70-80%) [7,23], 47-93% in Equatorial Guinea [24], and 70-94% in Angola [25]. "
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    ABSTRACT: Active case detection through mass community screening is a major control strategy against human African trypanosomiasis (HAT, sleeping sickness) caused by T. brucei gambiense. However, its impact can be limited by incomplete attendance at screening sessions (screening coverage) and diagnostic inaccuracy. We developed a model-based approach to estimate the true prevalence and the fraction of cases detected during mass screening, based on observed prevalence, and adjusting for incomplete screening coverage and inaccuracy of diagnostic algorithms for screening, confirmation and HAT stage classification. We applied the model to data from three Médecins Sans Frontières projects in Uganda (Adjumani, Arua-Yumbe) and Southern Sudan (Kiri). We analysed 604 screening sessions, targeting about 710,000 people. Cases were about twice as likely to attend screening as non-cases, with no apparent difference by stage. Past incidence, population size and repeat screening rounds were strongly associated with observed prevalence. The estimated true prevalence was 0.46% to 0.90% in Kiri depending on the analysis approach, compared to an observed prevalence of 0.45%; 0.59% to 0.87% in Adjumani, compared to 0.92%; and 0.18% to 0.24% in Arua-Yumbe, compared to 0.21%. The true ratio of stage 1 to stage 2 cases was around two-three times higher than that observed, due to stage misclassification. The estimated detected fraction was between 42.2% and 84.0% in Kiri, 52.5% to 79.9% in Adjumani and 59.3% to 88.0% in Arua-Yumbe. In these well-resourced projects, a moderate to high fraction of cases appeared to be detected through mass screening. True prevalence differed little from observed prevalence for monitoring purposes. We discuss some limitations to our model that illustrate several difficulties of estimating the unseen burden of neglected tropical diseases.
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