During population-based HIV impact assessments (PHIAs), some participants who self-reported testing HIV-positive (PSRP) tested negative in one or more subsequent survey HIV tests. These unexpected discrepancies between their self-reported results and the survey results draw into question the validity of either the self-reported status or the test results. We analyzed PSRP with negative test results aged 15-59 years old using data collected from 2015 to 2021 in 13 countries, assessing prevalence, self-report status, survey HIV status, viral load, rapid tests and confirmatory tests, and answers to follow-up questions (such as years on treatment). Across these surveys, 19,026 participants were PSRP, and 256 (1.3%) of these were concluded to be HIV-negative after additional survey-based testing and review. PSRP determined to be HIV-negative trended higher in countries with a higher HIV prevalence, but their number was small enough that accepting self-reported HIV-positive status without testing would not have significantly affected the prevalence estimates for HIV or viral load suppression. Additionally, using more detailed information for Uganda, we examined 107 PSRP with any negative test results and found no significant correlation with years on treatment or age. Using these details, we examined support for the possible reasons for these discrepancies beyond misdiagnosis and false reporting. These findings suggest that those conducting surveys would benefit from a nuanced understanding of HIV testing among PSRP to conduct surveys ethically and produce high-quality results.

Population-based HIV Impact Assessments (PHIAs) are national household (HH) surveys that provide HIV diagnosis and CD4 testing with an immediate return of results. Accurate CD4 results improve HIV-positive participants' clinical care and inform the effectiveness of HIV programs. Here, we present CD4 results from the PHIA surveys that were conducted in 11 countries in sub-Saharan Africa between 2015 and 2018. All of the HIV-positive participants and 2 to 5% of the HIV-negative participants were offered Pima CD4 (Abbott, IL, USA) point-of-care (POC) tests. The quality of the CD4 test was ensured by conducting instrument verification, comprehensive training, quality control, a review of testing errors and an analysis of unweighted CD4 data by HIV status, age, gender, and antiretroviral (ARV) treatment status. Overall, CD4 testing was completed for 23,085 (99.5%) of the 23,209 HIV-positive and 7,329 (2.7%) of the 270,741 negative participants in 11 surveys. The instrument error rate was 11.3% (range, 4.4% to 15.7%). The median CD4 values among HIV-positive and HIV-negative participants (aged 15+) were 468 cells/mm(3) (interquartile range [IQR], 307 to 654) and 811 cells/mm(3) (IQR, 647 to 1,013), respectively (P < 0.0001). Among the HIV-positive participants (aged 15+), those with detectable ARVs had higher CD4 values (508 cells/mm(3)) than those with undetectable ARVs (385.5 cells/mm(3)). Among the HIV-positive participants (aged 15+), 11.4% (2,528/22,253) had a CD4 value of less than 200 cells/mm(3), and approximately half of them (1,225/2,528 = 48.5%) had detectable ARVs, whereas 51.5% (1,303/2,528) had no detectable ARVs. We successfully implemented high quality POC CD4 testing using Pima instruments. Our data come from nationally representative surveys in 11 countries and provide unique insights regarding the CD4 distribution among HIV-positive individuals as well as the baseline CD4 values among HIV-negative individuals. IMPORTANCE The manuscript describes CD4 levels among HIV-positive individuals and baseline CD4 levels among HIV-negative individuals from 11 sub-Saharan countries, thereby highlighting the importance of CD4 markers in the context of the HIV epidemic. Despite increased ARV access in each country, advanced HIV disease (CD4 < 200 cells/mm(3)) persists among approximately 11% of HIV-positive individuals. Therefore, it is important that our findings are shared with the scientific community to assist with similar implementations of point-of-care testing and to conduct a review of HIV programmatic gaps.

BACKGROUND: HIV-1 incidence calculation currently includes recency classification by HIV-1 incidence assay and unsuppressed viral load (VL ≥ 1000 copies/mL) in a recent infection testing algorithm (RITA). However, persons with recent classification not virally suppressed and taking antiretroviral (ARV) medication may be misclassified. SETTING: We used data from 13 African household surveys to describe the impact of an ARV-adjusted RITA on HIV-1 incidence estimates. METHODS: HIV-seropositive samples were tested for recency using the HIV-1 Limiting Antigen (LAg)-Avidity enzyme immunoassay, HIV-1 viral load, ARVs used in each country, and ARV drug resistance. LAg-recent result was defined as normalized optical density values ≤1.5. We compared HIV-1 incidence estimates using 2 RITA: RITA1: LAg-recent + VL ≥ 1000 copies/mL and RITA2: RITA1 + undetectable ARV. We explored RITA2 with self-reported ARV use and with clinical history. RESULTS: Overall, 357 adult HIV-positive participants were classified as having recent infection with RITA1. RITA2 reclassified 55 (15.4%) persons with detectable ARV as having long-term infection. Those with detectable ARV were significantly more likely to be aware of their HIV-positive status (84% vs. 10%) and had higher levels of drug resistance (74% vs. 26%) than those without detectable ARV. RITA2 incidence was lower than RITA1 incidence (range, 0%-30% decrease), resulting in decreased estimated new infections from 390,000 to 341,000 across the 13 countries. Incidence estimates were similar using detectable or self-reported ARV (R2 > 0.995). CONCLUSIONS: Including ARV in RITA2 improved the accuracy of HIV-1 incidence estimates by removing participants with likely long-term HIV infection.