Population Viral Load, Viremia, and Recent HIV-1 Infections: Findings From Population-Based HIV Impact Assessments (PHIAs) in Zimbabwe, Malawi, and Zambia.
Journal
Journal of acquired immune deficiency syndromes (1999)
ISSN: 1944-7884
Titre abrégé: J Acquir Immune Defic Syndr
Pays: United States
ID NLM: 100892005
Informations de publication
Date de publication:
01 08 2021
01 08 2021
Historique:
pubmed:
10
2
2021
medline:
6
11
2021
entrez:
9
2
2021
Statut:
ppublish
Résumé
HIV population viral load (PVL) can reflect antiretroviral therapy program effectiveness and transmission potential in a community. Using nationally representative data from household surveys conducted in Zimbabwe, Malawi, and Zambia in 2015-16, we examined the association between various VL measures and the probability of at least one recent HIV-1 infection in the community. We used limiting-antigen avidity enzyme immunoassay, viral load suppression (VLS) (HIV RNA <1000 copies/mL), and antiretrovirals in the blood to identify recent HIV-1 cases. Among 1510 enumeration areas (EAs) across the 3 surveys, 52,036 adults aged 15-59 years resided in 1363 (90.3%) EAs with at least one HIV-positive adult consenting to interview and blood draw and whose VL was tested. Mean HIV prevalence across these EAs was 13.1% [95% confidence intervals (CI) 12.7 to 13.5]. Mean VLS prevalence across these EAs was 58.7% (95% CI: 57.3 to 60.0). In multivariable analysis, PVL was associated with a recent HIV-1 case in that EA (adjusted odds ratio: 1.4, 95% CI: 1.2 to 1.6, P = 0.001). VLS prevalence was inversely correlated with recent infections (adjusted odds ratio: 0.3, 95% CI: 0.1 to 0.6, P = 0.004). The 90-90-90 indicators, namely, the prevalence of HIV diagnosis, antiretroviral therapy coverage, and VLS at the EA level, were inversely correlated with HIV recency at the EA level. We found a strong association between PVL and VLS prevalence and recent HIV-1 infection at the EA level across 3 southern African countries with generalized HIV epidemics. These results suggest that population-based measures of VLS in communities may serve as a proxy for epidemic control.
Sections du résumé
BACKGROUND
HIV population viral load (PVL) can reflect antiretroviral therapy program effectiveness and transmission potential in a community. Using nationally representative data from household surveys conducted in Zimbabwe, Malawi, and Zambia in 2015-16, we examined the association between various VL measures and the probability of at least one recent HIV-1 infection in the community.
METHODS
We used limiting-antigen avidity enzyme immunoassay, viral load suppression (VLS) (HIV RNA <1000 copies/mL), and antiretrovirals in the blood to identify recent HIV-1 cases.
RESULTS
Among 1510 enumeration areas (EAs) across the 3 surveys, 52,036 adults aged 15-59 years resided in 1363 (90.3%) EAs with at least one HIV-positive adult consenting to interview and blood draw and whose VL was tested. Mean HIV prevalence across these EAs was 13.1% [95% confidence intervals (CI) 12.7 to 13.5]. Mean VLS prevalence across these EAs was 58.7% (95% CI: 57.3 to 60.0). In multivariable analysis, PVL was associated with a recent HIV-1 case in that EA (adjusted odds ratio: 1.4, 95% CI: 1.2 to 1.6, P = 0.001). VLS prevalence was inversely correlated with recent infections (adjusted odds ratio: 0.3, 95% CI: 0.1 to 0.6, P = 0.004). The 90-90-90 indicators, namely, the prevalence of HIV diagnosis, antiretroviral therapy coverage, and VLS at the EA level, were inversely correlated with HIV recency at the EA level.
CONCLUSIONS
We found a strong association between PVL and VLS prevalence and recent HIV-1 infection at the EA level across 3 southern African countries with generalized HIV epidemics. These results suggest that population-based measures of VLS in communities may serve as a proxy for epidemic control.
Identifiants
pubmed: 33560041
doi: 10.1097/QAI.0000000000002637
pii: 00126334-202108011-00014
doi:
Types de publication
Journal Article
Research Support, U.S. Gov't, P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
S81-S88Subventions
Organisme : PEPFAR
Pays : United States
Organisme : CGH CDC HHS
ID : U2G GH001226
Pays : United States
Informations de copyright
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
Déclaration de conflit d'intérêts
The authors have no conflicts of interest to disclose.
Références
UNAIDS. 90-90-90: An Ambitious Treatment Target to Help End the AIDS Epidemic. Geneva, Switzerland: UNAIDS; 2014.
Quinn TC, Wawer MJ, Sewankambo N, et al. Viral load and heterosexual transmission of human immunodeficiency virus type 1. Rakai Project Study Group. New Engl J Med. 2000;342:921–929.
Justman JE, Mugurungi O, El-Sadr WM. HIV population surveys—bringing precision to the global response. New Engl J Med. 2018;378:1859–1861.
PHIA Project. 2018. Available at: https://phia.icap.columbia.edu/countries-overview/ . Accessed October 20, 2018.
CIPHIA team. CIPHIA Summary Sheet. 2018. Available at: https://phia.icap.columbia.edu/wp-content/uploads/2018/08/CIPHIA_Cote-DIvoire-SS_FINAL.pdf . Accessed January 19, 2019.
SHIMS2 team. SHIMS2 Summary Sheet. 2017. Available at: https://phia.icap.columbia.edu/wp-content/uploads/2017/11/Swaziland_new.v8.pdf . Accessed January 19, 2019.
Montaner JS, Lima VD, Barrios R, et al. Association of highly active antiretroviral therapy coverage, population viral load, and yearly new HIV diagnoses in British Columbia, Canada: a population-based study. The Lancet. 2010;376:532–539.
Wood E. Longitudinal community plasma HIV-1 RNA concentrations and incidence of HIV-1 among injecting drug users: a prospective cohort study. BMJ. 2009;338:b1649.
Das M, Chu PL, Santos GM, et al. Decreases in community viral load are accompanied by reductions in new HIV infections in san francisco. PLoS One. 2010;5:e11068.
Centers for Disease Control and Prevention (CDC). Guidance on Community Viral Load: A Family of Measures, Definitions, and Methods for Calculation. Atlanta, GA: Centers for Disease Control and Prevention (CDC); 2011.
Castel AD, Befus M, Willis S, et al. Use of the community viral load as a population-based biomarker of HIV burden. AIDS. 2012;26:345–353.
Miller WC, Powers KA, Smith MK, et al. Community viral load as a measure for the assessment of HIV treatment as prevention. Lancet Infect Dis. 2013;13:459–464.
Tanser F, Vandormael A, Cuadros D, et al. Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community. Sci translational Med. 2017;9:eaam8012.
Latkin CA, German D, Vlahov D, et al. Neighborhoods, and HIV: a social-ecological approach to prevention and care. Am Psychol. 2013;68:210–224.
ICF International. Demographic and Health Survey Sampling and Household Listing Manual. Calverton, MD: MEASURE DHS, ICF International; 2012.
Solomon SS, Mehta SH, McFall AM, et al. Community viral load, antiretroviral therapy coverage, and HIV incidence in India: a cross-sectional, comparative study. Lancet HIV. 2016;3:e183–e190.
Boerma JT, Weir SS. Integrating demographic and epidemiological approaches to research on HIV/AIDS: the proximate-determinants framework. J Infect Dis. 2005;191(supp 1):S61–S67.
Hardin JW, Schmiediche H, Carroll RJ. The simulation extrapolation method for fitting generalized linear models with additive measurement error. Stata J. 2003;3:1–13.
Burns PA, Snow RC. The built environment and the impact of neighborhood characteristics on youth sexual risk behavior in Cape Town, South Africa. Health Place. 2012;18:1088–1100.
Fendrich M, Avci O, Johnson TP, et al. Depression, substance use, and HIV risk in a probability sample of men who have sex with men. Addict Behav. 2013;38:1715–1718.
Carlson M, Brennan RT, Earls F. Enhancing adolescent self-efficacy and collective efficacy through public engagement around HIV/AIDS competence: a multilevel, cluster randomized controlled trial. Soc Sci Med. 2012;75:1078–1087.
Tanser F, Bärnighausen T, Grapsa E, et al. High coverage of ART associated with decline in risk of HIV acquisition in rural KwaZulu-natal, South Africa. Science. 2013;339:966–971.
(UNAIDS) JUNPoHA. Location, Location: Connecting People Faster to HIV Services. Geneva, Switzerland: UNAIDS; 2013.
President's Emergency Plan for AIDS Relief (PEPFAR). PEPFAR 3.0: Controlling the Epidemic: Delivering on the Promise of an AIDS-Free Generation. Washington, DC: PEPFAR; 2014.
Morgenstern H. Ecologic studies in epidemiology: concepts, principles, and methods. Annu Rev Public Health. 1995;16:61–81.
Kassanjee R, Pilcher CD, Busch MP, et al. Viral load criteria and threshold optimization to improve HIV incidence assay characteristics-a CEPHIA analysis. AIDS. 2016;30:2361.