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Abstract Background For assessing the HIV epidemic in Kenya, a series of independent HIV indicator household-based surveys of similar design can be used to investigate the trends in key indicators relevant to HIV prevention and control and to describe geographic and sociodemographic disparities, assess the impact of interventions, and develop strategies. We developed methods and tools to facilitate a robust analysis of trends across three national household-based surveys conducted in Kenya in 2007, 2012, and 2018. Methods We used data from the 2007 and 2012 Kenya AIDS Indicator surveys (KAIS 2007 and KAIS 2012) and the 2018 Kenya Population-based HIV Impact Assessment (KENPHIA 2018). To assess the design and other variables of interest from each study, variables were recoded to ensure that they had equivalent meanings across the three surveys. After assessing weighting procedures for comparability, we used the KAIS 2012 nonresponse weighting procedure to revise normalized KENPHIA weights. Analyses were restricted to geographic areas covered by all three surveys. The revised analysis files were then merged into a single file for pooled analysis. We assessed distributions of age, sex, household wealth, and urban/rural status to identify unexpected changes between surveys. To demonstrate how a trend analysis can be carried out, we used continuous, binary, and time-to-event variables as examples. Specifically, temporal trends in age at first sex and having received an HIV test in the last 12 months were used to demonstrate the proposed analytical approach. These were assessed with respondent-specific variables (age, sex, level of education, and marital status) and household variables (place of residence and wealth index). All analyses were conducted in SAS 9.4, but analysis files were created in Stata and R format to support additional analyses. Results This study demonstrates trends in selected indicators to illustrate the approach that can be used in similar settings. The incidence of early sexual debut decreased from 11.63 (95% CI: 10.95–12.34) per 1,000 person-years at risk in 2007 to 10.45 (95% CI: 9.75–11.2) per 1,000 person-years at risk in 2012 and to 9.58 (95% CI: 9.08–10.1) per 1,000 person-years at risk in 2018. HIV-testing rates increased from 12.6% (95% CI: 11.6%–13.6%) in 2007 to 56.1% (95% CI: 54.6%–57.6%) in 2012 but decreased slightly to 55.6% [95% CI: 54.6%–56.6%) in 2018. The decrease in incidence of early sexual debut could be convincingly demonstrated between 2007 and 2012 but not between 2012 and 2018. Similarly, there was virtually no difference between HIV Testing rates in 2012 and 2018. Conclusions Our approach can be used to support trend comparisons for variables in HIV surveys in low-income settings. Independent national household surveys can be assessed for comparability, adjusted as appropriate, and used to estimate trends in key indicators. Analyzing trends over time can not only provide insights into Kenya’s progress toward HIV epidemic control but also identify gaps.

Voluntary medical male circumcision (VMMC) has primarily been promoted for HIV prevention. Evidence also supports that male circumcision offers protection against other sexually transmitted infections. This analysis assessed the effect of circumcision on syphilis, hepatitis B virus (HBV) infection and HIV. Data from the 2015 to 2019 Population-based HIV Impact Assessments (PHIAs) surveys from Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe were used for the analysis. The PHIA surveys are cross-sectional, nationally representative household surveys that include biomarking testing for HIV, syphilis and HBV infection. This is a secondary data analysis using publicly available PHIA data. Univariate and multivariable logistic regression models were created using pooled PHIA data across the five countries to assess the effect of male circumcision on HIV, active and ever syphilis, and HBV infection among sexually active males aged 15-59 years. Circumcised men had lower odds of syphilis infection, ever or active infection, and HIV, compared to uncircumcised men, after adjusting for covariates (active syphilis infection = 0.67 adjusted odds ratio (aOR), 95% confidence interval (CI), 0.52-0.87, ever having had a syphilis infection = 0.85 aOR, 95% CI, 0.73-0.98, and HIV = 0.53 aOR, 95% CI, 0.47-0.61). No difference between circumcised and uncircumcised men was identified for HBV infection (P = 0.75). Circumcised men have a reduced likelihood for syphilis and HIV compared to uncircumcised men. However, we found no statistically significant difference between circumcised and uncircumcised men for HBV infection.

Background We examined the epidemiology and transmission potential of HIV population viral load (VL) in 12 sub-Saharan African countries. Methods We analyzed data from Population-based HIV Impact Assessments (PHIAs), large national household-based surveys conducted between 2015 and 2019 in Cameroon, Cote d’Ivoire, Eswatini, Kenya, Lesotho, Malawi, Namibia, Rwanda, Tanzania, Uganda, Zambia, and Zimbabwe. Blood-based biomarkers included HIV serology, recency of HIV infection, and VL. We estimated the number of people living with HIV (PLHIV) with suppressed viral load (Results The proportion of female PLHIV with viral suppression was higher than that among males in all countries, however, the number of unsuppressed females outnumbered that of unsuppressed males in all countries due to higher overall female HIV prevalence, with ratios ranging from 1.08 to 2.10 (median: 1.43). The spatial distribution of HIV seroprevalence, viremia prevalence, and number of unsuppressed adults often differed substantially within the same countries. The 1% and 5% of PLHIV with the highest VL on average accounted for 34% and 66%, respectively, of countries’ total VL. HIV transmission ratios varied widely across countries and were higher for male-to-female (range: 2.3–28.3/100 PY) than for female-to-male transmission (range: 1.5–10.6/100 PY). In all countries mean log10 VL among unsuppressed males was higher than that among females. Correlations between VL measures and incident HIV varied, were weaker for VL metrics among females compared to males and were strongest for the number of unsuppressed PLHIV per 100 HIV-negative adults (R2 = 0.92). Conclusions Despite higher proportions of viral suppression, female unsuppressed PLHIV outnumbered males in all countries examined. Unsuppressed male PLHIV have consistently higher VL and a higher risk of transmitting HIV than females. Just 5% of PLHIV account for almost two-thirds of countries’ total VL. Population-level VL metrics help monitor the epidemic and highlight key programmatic gaps in these African countries.

BackgroundThe Nigeria AIDS Indicator and Impact Survey (NAIIS), a cross-sectional household survey, was conducted in 2018 with primary objectives to estimate HIV prevalence, HIV-1 incidence, and status of UNAIDS 90-90-90 cascade. We conducted retrospective analysis of the performance of HIV rapid tests and the national HIV testing algorithm used in Nigeria.MethodsThe national algorithm included Determine HIV-1/2 as test 1 (T1), Unigold HIV-1/2 as test 2 (T2), and StatPak HIV-1/2 as the tie-breaker test (T3). Individuals reactive with T1 and either T2 or T3 were considered HIV-positive. HIV-positive specimens from the algorithm were further confirmed for the survey using supplemental test Geenius HIV-1/2. If Geenius did not confirm HIV-positive status, HIV-1 Western blot was performed. We calculated the concordance between tests and positive predictive value (PPV) of the algorithm on unweighted data.ResultsOf 204,930 participants (ages ≥18 months) 5,103 (2.5%) were reactive on T1. Serial testing of T1 reactive specimens with T2 or if needed by tiebreaker T3 identified 2958 (1.44%) persons as HIV-positive. Supplemental testing confirmed 2,800 (95%) as HIV-positive (HIV-1 = 2,767 [98.8%]; HIV-2 = 5 [0.2%]; dual infections = 22 [0.8%]). Concordance between T1 and T2 was 56.6% while PPV of the national algorithm was 94.5%.ConclusionsOur results show high discordant rates and poor PPV of the national algorithm with a false-positive rate of about 5.5% in the NAIIS survey. Considering our findings have major implications for HIV diagnosis in routine HIV testing services, additional evaluation of testing algorithm is warranted in Nigeria.

We analyzed data from the 2018 Kenya Population-Based HIV Impact Assessment (KENPHIA), a cross-sectional, nationally representative survey, to estimate the burden and prevalence of pediatric HIV infection, identify associated factors, and describe the clinical cascade among children aged < 15 years in Kenya. Interviewers collected information from caregivers or guardians on child's demographics, HIV testing, and treatment history. Blood specimens were collected for HIV serology and if HIV-positive, the samples were tested for viral load and antiretrovirals (ARV). For participants

Objective Although geographically specific data can help target HIV prevention and treatment strategies, Nigeria relies on national- and state-level estimates for policymaking and intervention planning. We calculated sub-state estimates along the HIV continuum of care in Nigeria. Design Using data from the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) (July–December 2018), we conducted a geospatial analysis estimating three key programmatic indicators: prevalence of HIV infection among adults (aged 15–64 years); antiretroviral therapy (ART) coverage among adults living with HIV; and viral load suppression (VLS) rate among adults living with HIV. Methods We used an ensemble modeling method called stacked generalization to analyze available covariates and a geostatistical model to incorporate the output from stacking as well as spatial autocorrelation in the modeled outcomes. Separate models were fitted for each indicator. Finally, we produced raster estimates of each indicator on an approximately 5×5-km grid and estimates at the sub-state/local government area (LGA) and state level. Results Estimates for all three indicators varied both within and between states. While state-level HIV prevalence ranged from 0.3% (95% uncertainty interval [UI]: 0.3%–0.5%]) to 4.3% (95% UI: 3.7%–4.9%), LGA prevalence ranged from 0.2% (95% UI: 0.1%–0.5%) to 8.5% (95% UI: 5.8%–12.2%). Although the range in ART coverage did not substantially differ at state level (25.6%–76.9%) and LGA level (21.9%–81.9%), the mean absolute difference in ART coverage between LGAs within states was 16.7 percentage points (range, 3.5–38.5 percentage points). States with large differences in ART coverage between LGAs also showed large differences in VLS—regardless of level of effective treatment coverage—indicating that state-level geographic targeting may be insufficient to address coverage gaps. Conclusion Geospatial analysis across the HIV continuum of care can effectively highlight sub-state variation and identify areas that require further attention in order to achieve epidemic control. By generating local estimates, governments, donors, and other implementing partners will be better positioned to conduct targeted interventions and prioritize resource distribution.

BackgroundData on awareness of HIV status among people living with HIV (PLHIV) are critical to estimating progress toward epidemic control. To ascertain the accuracy of self-reported HIV status and antiretroviral drug (ARV) use in the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), we compared self-reported HIV status with HIV rapid diagnostic test (RDT) results and self-reported ARV use with detectable blood ARV levels.MethodsOn the basis of responses and test results, participants were categorized by HIV status and ARV use. Self-reported HIV status and ARV use performance characteristics were determined by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Proportions and other analyses were weighted to account for complex survey design.ResultsDuring NAIIS, 186,405 participants consented for interview out of which 58,646 reported knowing their HIV status. Of the 959 (weighted, 1.5%) who self-reported being HIV-positive, 849 (92.1%) tested HIV positive and 64 (7.9%) tested HIV negative via RDT and polymerase chain reaction test for discordant positive results. Of the 849 who tested HIV positive, 743 (89.8%) reported using ARV and 72 (10.2%) reported not using ARV. Of 57,687 who self-reported being HIV negative, 686 (1.2%) tested HIV positive via RDT, with ARV biomarkers detected among 195 (25.1%). ARV was detected among 94.5% of those who self-reported using ARV and among 42.0% of those who self-reported not using ARV. Overall, self-reported HIV status had sensitivity of 52.7% (95% confidence interval [CI]: 49.4%-56.0%) with specificity of 99.9% (95% CI: 99.8%-99.9%). Self-reported ARV use had sensitivity of 95.2% (95% CI: 93.6%-96.7%) and specificity of 54.5% (95% CI: 48.8%-70.7%).ConclusionsSelf-reported HIV status and ARV use screening tests were found to be low-validity measures during NAIIS. Laboratory tests to confirm self-reported information may be necessary to determine accurate HIV and clinical status for HIV studies in Nigeria.

Background: The aim of this review was to summarize the data on HIV/AIDS epidemiology and affected populations in Ghana and to describe the United States President’s Emergency Plan for Emergency Relief’s (PEPFAR) response to the epidemic. Design: We conducted a literature review focusing on PEPFAR’s contribution to the HIV response in Ghana. Additionally, we summarized the epidemiology of HIV. We searched both peer-reviewed and grey literature. Setting: Ghana Results: Overall, HIV prevalence in Ghana is 1.6% with regional variation. Key populations (KPs) are disproportionately affected by HIV in the country. FSW and their clients, and MSM, account for 28% of all new infections. PEPFAR provides technical assistance (TA) to Ghana to maximize the quality, coverage and impact of the national HIV/AIDS response. To ensure adequate supply of antiretrovirals (ARVs), in 2016-2017, PEPFAR invested $23.7 million as a onetime supplemental funding to support Ghana’s ARV treatment program. In addition, the National AIDS Control Programme in collaboration with PEPFAR is implementing a scale up of viral load testing. PEPFAR is also implementing a comprehensive package of prevention services in five regions to help reach MSM and FSW and to expand HIV testing services for KPs. Conclusions: Ghana is making changes at both policy and program level in the fight against HIV/AIDS and is working towards achieving the UNAIDS’ 90-90-90 targets. PEPFAR is providing TA to ensure these goals can be achieved. Funding: This manuscript has been supported by the U.S. President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention (CDC). Keywords: HIV, epidemic, Ghana, PEPFAR

BackgroundIneffective linkage to care (LTC) is a known challenge for community HIV testing. To overcome this challenge, a robust linkage to care strategy was adopted by the 2018 Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS). The NAIIS linkage to care strategy was further adapted to improve Nigeria's programmatic efforts to achieve the 1st 90 as part of the Nigeria Antiretroviral Therapy (ART) Surge initiative, which also included targeted community testing. In this paper we provide an overview of the NAIIS LTC strategy and describe the impact of this strategy on both the NAIIS and the Surge initiatives.MethodsThe NAIIS collaborated with community-based organizations (CBOs) and deployed mobile health (mHealth) technology with real-time dashboards to manage and optimize community LTC for people living with HIV (PLHIV) diagnosed during the survey. In NAIIS, CBOs' role was to facilitate linkage of identified PLHIV in community to facility of their choice. For the ART Surge, we modified the NAIIS LTC strategy by empowering both CBOs and mobile community teams as responsible for not only active LTC but also for community testing, ART initiation, and retention in care.ResultsOf the 2,739 PLHIV 15 years and above identified in NAIIS, 1,975 (72.1%) were either unaware of their HIV-positive status (N = 1890) or were aware of their HIV-positive status but not receiving treatment (N = 85). Of these, 1,342 (67.9%) were linked to care, of which 952 (70.9%) were initiated on ART. Among 1,890 newly diagnosed PLHIV, 1,278 (67.6%) were linked to care, 33.7% self-linked and 66.3% were linked by CBOs. Among 85 known PLHIV not on treatment, 64 (75.3%) were linked; 32.8% self-linked and 67.2% were linked by a CBO. In the ART Surge, LTC and treatment initiation rates were 98% and 100%, respectively. Three-month retention for monthly treatment initiation cohorts improved from 76% to 90% over 6 months.ConclusionsActive LTC strategies by local CBOs and mobile community teams improved LTC and ART initiation in the ART Surge initiative. The use of mHealth technology resulted in timely and accurate documentation of results in NAIIS. By deploying mHealth in addition to active LTC, CBOs and mobile community teams could effectively scale up ART with real-time documentation of client-level outcomes.