Progress towards onchocerciasis elimination in the participating countries of the African Programme for Onchocerciasis Control: epidemiological evaluation results

• Published in: Infectious diseases of poverty 2016-06, Vol.5 (1), p.66-66, Article 66
• Main Authors: Tekle, Afework H, Zouré, Honorath G M, Noma, Mounkaila, Boussinesq, Michel, Coffeng, Luc E, Stolk, Wilma A, Remme, Jan H F
• Format: Article
• Language: English
• Subjects: Africa South of the Sahara - epidemiology; Animals; Bayes Theorem; Community Health Services; Epidemiology; Evaluation; Filaricides - pharmacology; Filaricides - therapeutic use; Health promotion; Infection control; Infectious diseases; Ivermectin - pharmacology; Ivermectin - therapeutic use; Methods; Microfilariae - drug effects; Monte Carlo Method; Onchocerca volvulus - drug effects; Onchocerciasis; Onchocerciasis - drug therapy; Onchocerciasis - epidemiology; Onchocerciasis - parasitology; Onchocerciasis - prevention & control; Prevalence; Prevention
• ISSN: 2049-9957; 2095-5162; 2049-9957
• DOI: 10.1186/s40249-016-0160-7

The African Programme for Onchocerciasis Control (APOC) was created in 1995 to establish community-directed treatment with ivermectin (CDTi) in order to control onchocerciasis as a public health problem in 20 African countries that had 80 % of the global disease burden. When research showed that CDTi may ultimately eliminate onchocerciasis infection, APOC was given in 2008 the additional objective to determine when and where treatment can be safely stopped. We report the results of epidemiological evaluations undertaken from 2008 to 2014 to assess progress towards elimination in CDTi areas with ≥6 years treatment. Skin snip surveys were undertaken in samples of first-line villages to determine the prevalence of O. volvulus microfilariae. There were two evaluation phases. The decline in prevalence was evaluated in phase 1A. Observed and model-predicted prevalences were compared after correcting for endemicity level and treatment coverage. Bayesian statistics and Monte Carlo simulation were used to classify the decline in prevalence as faster than predicted, on track or delayed. Where the prevalence approached elimination levels, phase 1B was launched to determine if treatment could be safely stopped. Village sampling was extended to the whole CDTi area. Survey data were analysed within a Bayesian framework to determine if stopping criteria (overall prevalence