Where Are the Newly Diagnosed HIV Positives in Kenya? Time to Consider Geo-Spatially Guided Targeting at a Finer Scale to Reach the "First 90"

Cofactors of Partner HIV Self-testing and Oral PrEP Acceptance Among Pregnant Women at High Risk of HIV in Kenya

BACKGROUND

Oral pre-exposure prophylaxis (PrEP) and male partner HIV self-testing (HIVST) is being scaled up within antenatal clinics. Few data are available on how co-distribution influences acceptance of both interventions.

METHODS

We used data from the PrEP Implementation of Mothers in Antenatal Care (NCT03070600) trial in Kenya. Women included in this analysis were determined to be at high risk of HIV and offered oral PrEP and partner HIVST. Characteristics were compared between women who chose: (1) PrEP and HIVST, (2) HIVST-alone, (3) PrEP-alone, or (4) declined both (reference), excluding women who had partners known to be living with HIV.

RESULTS

Among 911 women, median age was 24 years, 87.3% were married, 43.9% perceived themselves to be at high risk of HIV and 13.0% had history of intimate partner violence (IPV). Overall, 68.9% accepted HIVST and 18.4% accepted PrEP, with 54.7% accepting HIVST-alone, 4.2% PrEP-alone, and 14.3% both HIVST and PrEP. Of women accepting HIVST, partner HIV testing increased from 20% to 82% and awareness of partner HIV status increased from 4.7% to 82.0% between pregnancy and 9 months postpartum (P < 0.001). Compared with women who accepted neither, choosing: (1) HIVST-alone was associated with being married, higher level of education, and residing with partner; (2) PrEP-alone was associated with lower social support, IPV, not residing with partner, longer time living with partner, and suspicion of other partners; and (3) PrEP and HIVST was associated with being married, IPV, and suspicion that partner had other partners.

CONCLUSIONS

Understanding factors associated with accepting HIVST and PrEP can inform HIV prevention programs for pregnant women.

CLINICAL TRIAL NUMBER

NCT03070600.

Use of unsupervised machine learning to characterise HIV predictors in sub-Saharan Africa

INTRODUCTION

Significant regional variations in the HIV epidemic hurt effective common interventions in sub-Saharan Africa. It is crucial to analyze HIV positivity distributions within clusters and assess the homogeneity of countries. We aim at identifying clusters of countries based on socio-behavioural predictors of HIV for screening.

METHOD

We used an agglomerative hierarchical, unsupervised machine learning, approach for clustering to analyse data for 146,733 male and 155,622 female respondents from 13 sub-Saharan African countries with 20 and 26 features, respectively, using Population-based HIV Impact Assessment (PHIA) data from the survey years 2015-2019. We employed agglomerative hierarchical clustering and optimal silhouette index criterion to identify clusters of countries based on the similarity of socio-behavioural characteristics. We analyse the distribution of HIV positivity with socio-behavioural predictors of HIV within each cluster.

RESULTS

Two principal components were obtained, with the first describing 62.3% and 70.1% and the second explaining 18.3% and 20.6% variance of the total socio-behavioural variation in females and males, respectively. Two clusters per sex were identified, and the most predictor features in both sexes were: relationship with family head, enrolled in school, circumcision status for males, delayed pregnancy, work for payment in last 12 months, Urban area indicator, known HIV status and delayed pregnancy. The HIV positivity distribution with these variables was significant within each cluster.

CONCLUSIONS /FINDINGS

The findings provide a potential use of unsupervised machine learning approaches for substantially identifying clustered countries based on the underlying socio-behavioural characteristics.

Cost-effectiveness of the dual prevention pill for contraception and HIV pre-exposure prophylaxis

Introduction

Women in sub-Saharan Africa (SSA) experience the world's highest rates of both HIV infection and unintended pregnancy. The Dual Prevention Pill (DPP) is a novel multipurpose prevention technology (MPT) that co-formulates HIV pre-exposure prophylaxis (PrEP) and combined hormonal oral contraception into a single daily pill. As a dual indication product, the DPP may be preferred by women facing these overlapping health risks. However, most SSA countries face severe healthcare resource constraints. Research is needed to assess whether, in what populations, and in what use cases the DPP would be cost-effective.

Methods

We augmented an agent-based SSA HIV model with maternal health parameters including unintended pregnancy, abortion, and maternal mortality. Based on a previous market analysis, we assumed a primary DPP user population of current oral contraceptive users ages 25-49, and alternative user populations in different risk groups (age 15-24, sex workers, HIV-serodiscordant couples) and baseline product use profiles (unmet need for contraception, oral PrEP use, condom use). In three geographies (western Kenya, Zimbabwe, South Africa), we estimated HIV infections averted, pregnancies averted, disability-adjusted life-years (DALYs) averted, and the incremental cost-effectiveness ratio (ICER) over a 30-year time horizon, assuming equivalent adherence to the DPP as to oral contraceptives, higher adherence, or lower adherence.

Results

The DPP is likely to be a cost-effective alternative to oral PrEP among users in need of contraception. Among women not already using PrEP, the DPP is likely to be cost-saving in sex workers and serodiscordant couples. The DPP is unlikely to be cost-effective in oral contraceptive users in the general population. Switching from oral contraception to the DPP could be net harmful in some settings and populations if it were to substantially reduces adherence to oral contraception. Results were robust to a range of time horizons or discount rates.

Conclusion

The DPP has the potential to be cost-effective and cost-saving in populations at substantial HIV risk. Outcomes are sensitive to adherence, implying that effective counseling and decision-making tools for users considering the DPP will be essential. More research is needed to understand real-life adherence patterns and ensure health benefits achieved from contraception alone are not lost.

Mapping geographic clusters of new HIV diagnoses to inform granular-level interventions for HIV epidemic control in western Kenya

BACKGROUND

As countries make progress towards HIV epidemic control, there is increasing need to identify finer geographic areas to target HIV interventions. We mapped geographic clusters of new HIV diagnoses, and described factors associated with HIV-positive diagnosis, in order to inform targeting of HIV interventions to finer geographic areas and sub-populations.

METHODS

We analyzed data for clients aged > 15 years who received home-based HIV testing as part of a routine public health program between May 2016 and July 2017 in Siaya County, western Kenya. Geospatial analysis using Kulldorff's spatial scan statistic was used to detect geographic clusters (radius < 5 kilometers) of new HIV diagnoses. Factors associated with new HIV diagnosis were assessed in a spatially-integrated Bayesian hierarchical model.

RESULTS

Of 268,153 clients with HIV test results, 2906 (1.1%) were diagnosed HIV-positive. We found spatial variation in the distribution of new HIV diagnoses, and identified nine clusters in which the number of new HIV diagnoses was significantly (1.56 to 2.64 times) higher than expected. Sub-populations with significantly higher HIV-positive yield identified in the multivariable spatially-integrated Bayesian model included: clients aged 20-24 years [adjusted relative risk (aRR) 3.45, 95% Bayesian Credible Intervals (CI) 2.85-4.20], 25-35 years (aRR 4.76, 95% CI 3.92-5.81) and > 35 years (aRR 2.44, 95% CI 1.99-3.00); those in polygamous marriage (aRR 1.84, 95% CI 1.55-2.16), or separated/divorced (aRR 3.36, 95% CI 2.72-4.08); and clients who reported having never been tested for HIV (aRR 2.35, 95% CI 2.02-2.72), or having been tested > 12 months ago (aRR 1.53, 95% CI 1.41-1.66).

CONCLUSION

Our study used routine public health program data to identify granular geographic clusters of higher new HIV diagnoses, and sub-populations with higher HIV-positive yield in the setting of a generalized HIV epidemic. In order to target HIV testing and prevention interventions to finer granular geographic areas for maximal epidemiologic impact, integrating geospatial analysis into routine public health programs can be useful.