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Meta-Analysis
. 2021 Dec;25(12):3858-3870.
doi: 10.1007/s10461-021-03310-z. Epub 2021 May 28.

Under-Reporting of Known HIV-Positive Status Among People Living with HIV: A Systematic Review and Meta-analysis

Nirali Soni  1   2 , Katia Giguère  3   4 , Marie-Claude Boily  1   2 , Jessica M Fogel  5 , Mathieu Maheu-Giroux  3 , Dobromir Dimitrov  6 , Susan H Eshleman  5 , Kate M Mitchell  7   8   9
Affiliations
Meta-Analysis

Under-Reporting of Known HIV-Positive Status Among People Living with HIV: A Systematic Review and Meta-analysis

Nirali Soni et al. AIDS Behav. 2021 Dec.

Abstract

Monitoring progress towards the UNAIDS 'first 90' target requires accurate estimates of levels of diagnosis among people living with HIV (PLHIV), which is often estimated using self-report. We conducted a systematic review and meta-analysis quantifying under-reporting of known HIV-positive status using objective knowledge proxies. Databases were searched for studies providing self-reported and biological/clinical markers of prior knowledge of HIV-positive status among PLHIV. Random-effects models were used to derive pooled estimates of levels of under-reporting. Thirty-two estimates from 26 studies were included (41,465 PLHIV). The pooled proportion under-reporting known HIV-positive status was 20% (95% confidence interval 13-26%, I2 = 99%). In sub-group analysis, under-reporting was higher among men who have sex with men (32%, number of estimates [Ne] = 10) compared to the general population (9%, Ne = 10) and among Black (18%, Ne = 5) than non-Black (3%, Ne = 3) individuals. Supplementing self-reported data with biological/clinical proxies may improve the validity of the 'first 90' estimates.

Keywords: Bias; HIV status; Knowledge; Proxy; Under-report.

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Conflict of interest statement

KMM has received an honorarium from Gilead for speaking, outside of the submitted work. KG has worked as a consultant for UNAIDS. All other authors have no conflicts to declare.

Figures

Fig. 1
Fig. 1
PRISMA flowchart showing the screening and selection process. DHS demographic and health survey, IAS International AIDS society, Ne number of estimates, Ns number of studies, PHIA population-based impact assessment
Fig. 2
Fig. 2
Forest plot showing proportion of people living with HIV under-reporting known HIV-positive status by population type. White squares identify estimates that were excluded from the pooled estimates to avoid counting same population twice. ARV antiretroviral, DHS demographic and health survey, FSW female sex workers, MPHIA Malawi population-based HIV impact assessment, MSM men who have sex with men, PLHIV people living with HIV, PWID people who inject drugs, RE random effects, SHIMS2 Swaziland HIV incidence measurement survey 2, THIS Tanzania HIV impact survey, TGW transgender women, USA United States of America, VLS viral load suppression, ZAMPHIA Zambia population-based HIV impact assessment. Viral suppression considered as < 1000 copies/mL for all but one study which was defined as < 893 copies/mL
Fig. 3
Fig. 3
Forest plot showing all sub-group analysis pooled estimates of people living with HIV under-reporting of known HIV-positive status. Sex sub-group only contains studies in the general population. MSM men who have sex with men, PWID people who inject drugs, FSW female sex workers, TGW transgender women, LGBT lesbian, gay, bisexual, and transgender, RDS respondent driven sampling
See this image and copyright information in PMC

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