Stéphanie Blaizot1,2,3,4, Andrea A Kim5, Clement Zeh6, Benjamin Riche1,2,3,4, David Maman7, Kevin M De Cock5, Jean-François Etard7,8, René Ecochard1,2,3,4. 1. 1 Hospices Civils de Lyon, Service de Biostatistique , Lyon, France . 2. 2 Université de Lyon , Lyon, France . 3. 3 Université Lyon 1 , Villeurbanne, France . 4. 4 CNRS UMR 5558, Laboratoire de Biométrie et Biologie Evolutive, Equipe Biostatistique-Santé , Villeurbanne, France . 5. 5 Division of Global HIV/AIDS, U.S. Centers for Disease Control and Prevention , Nairobi, Kenya . 6. 6 Division of HIV/AIDS Prevention, U.S. Centers for Disease Control and Prevention , Kisumu, Kenya . 7. 7 Epicentre , Paris, France . 8. 8 UMI 233 TransVIHMI, Institut de Recherche pour le Développement, INSERM U1175, Université de Montpellier , Montpellier, France .
Abstract
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.
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.
Authors: Michael P Busch; Christopher D Pilcher; Timothy D Mastro; John Kaldor; Gaby Vercauteren; William Rodriguez; Christine Rousseau; Thomas M Rehle; Alex Welte; Megan D Averill; Jesus M Garcia Calleja Journal: AIDS Date: 2010-11-27 Impact factor: 4.177
Authors: Reshma Kassanjee; Christopher D Pilcher; Sheila M Keating; Shelley N Facente; Elaine McKinney; Matthew A Price; Jeffrey N Martin; Susan Little; Frederick M Hecht; Esper G Kallas; Alex Welte; Michael P Busch; Gary Murphy Journal: AIDS Date: 2014-10-23 Impact factor: 4.177
Authors: Isolde Birdthistle; Clare Tanton; Andrew Tomita; Kristen de Graaf; Susan B Schaffnit; Frank Tanser; Emma Slaymaker Journal: Lancet Glob Health Date: 2019-11 Impact factor: 26.763
Authors: Sheila M Keating; Wes Rountree; Eduard Grebe; Andrea L Pappas; Mars Stone; Dylan Hampton; Christopher A Todd; Marek S Poniewierski; Ana Sanchez; Cassandra G Porth; Thomas N Denny; Michael P Busch Journal: PLoS One Date: 2019-09-16 Impact factor: 3.240