Blaizot S., Kim A. A., Zeh C., Riche B., Maman D., De Cock K. M., Etard Jean-François, Ecochard R. (2017). Estimating HIV incidence using a cross-sectional survey : comparison of three approaches in a hyperendemic setting, Ndhiwa subcounty, Kenya, 2012. Aids Research and Human Retroviruses, 33 (5), p. 472-481. ISSN 0889-2229.
Titre du document
Estimating HIV incidence using a cross-sectional survey : comparison of three approaches in a hyperendemic setting, Ndhiwa subcounty, Kenya, 2012
Blaizot S., Kim A. A., Zeh C., Riche B., Maman D., De Cock K. M., Etard Jean-François, Ecochard R.
Source
Aids Research and Human Retroviruses, 2017,
33 (5), p. 472-481 ISSN 0889-2229
Objectives: Estimating HIV incidence is critical for identifying groups at risk for HIV infection, planning and targeting interventions, and evaluating these interventions over time. The use of reliable estimation methods for HIV incidence is thus of high importance. The aim of this study was to compare methods for estimating HIV incidence in a population-based cross-sectional survey. Design/Methods: The incidence estimation methods evaluated included assay-derived methods, a testing history-derived method, and a probability-based method applied to data from the Ndhiwa HIV Impact in Population Survey (NHIPS). Incidence rates by sex and age and cumulative incidence as a function of age were presented. Results: HIV incidence ranged from 1.38 [95% confidence interval (CI) 0.67-2.09] to 3.30 [95% CI 2.78-3.82] per 100 person-years overall; 0.59 [95% CI 0.00-1.34] to 2.89 [95% CI 0.86-6.45] in men; and 1.62 [95% CI 0.16-6.04] to 4.03 [95% CI 3.30-4.77] per 100 person-years in women. Women had higher incidence rates than men for all methods. Incidence rates were highest among women aged 15-24 and 25-34 years and highest among men aged 25-34 years. Conclusion: Comparison of different methods showed variations in incidence estimates, but they were in agreement to identify most-at-risk groups. The use and comparison of several distinct approaches for estimating incidence are important to provide the best-supported estimate of HIV incidence in the population.
