Risk scores for predicting HIV incidence among adult heterosexual populations in sub-Saharan Africa: a systematic review and meta-analysis

Predictors of maternal HIV acquisition during pregnancy and lactation in sub-Saharan Africa: A systematic review and narrative synthesis

OBJECTIVES

To eliminate vertical transmission of HIV, global institutions recommend using a risk-guided approach for HIV prevention services in antenatal and postnatal settings. Identifying predictors of maternal HIV acquisition can inform the development of risk-guided approaches, but individual studies of predictors can have limited power and generalizability.

METHODS

We conducted a systematic review and narrative synthesis to identify common predictors of maternal HIV acquisition in sub-Saharan Africa (SSA). We searched four databases for full-text articles that estimated associations between at least one predictor and risk of HIV acquisition among pregnant and/or lactating women (PLW) in SSA. We restricted our synthesis to predictors assessed in at least four study populations. For these predictors, we summarized how each predictor was defined and used vote counting and descriptive statistics to characterize overall trends.

RESULTS

We identified 26 eligible publications that summarized results from 24 unique studies. Studies were implemented in 12 countries between 1988 and 2021 and enrolled a total of 164,480 PLW at risk of acquiring HIV. Of the 66 predictors evaluated, 16 met our inclusion criteria. Estimated associations tended to be imprecise and variability in how predictors were measured precluded meta-analyses. We observed trends towards a higher risk of maternal HIV acquisition among young women and women who reported early coital debut, multiple partnerships, sexually transmitted infections, being unaware of partner HIV status, or having a partner living with HIV. In most studies, PLW in stable, monogamous relationships experienced a lower risk of acquiring HIV than those who were single, separated, or in a polygynous marriage. HIV risk perception, condom use, and vaginal drying were also commonly associated with HIV acquisition risk.

CONCLUSIONS

In our systematic review and narrative synthesis, we identified several easily measured characteristics that were associated with HIV acquisition among PLW in multiple study populations across SSA. Such findings can support the development and refinement of risk-guided approaches for HIV prevention in the region.

A Human Immunodeficiency Virus Type 1 Risk Assessment Tool for Women Aged 15-49 Years in African Countries: A Pooled Analysis Across 15 Nationally Representative Surveys

BACKGROUND

Women in Africa disproportionately acquire human immunodeficiency virus type 1 (HIV-1). Understanding which women are most likely to acquire HIV-1 can guide focused prevention with preexposure prophylaxis (PrEP). Our objective was to identify women at the highest risk of HIV-1 and estimate PrEP efficiency at different sensitivity levels.

METHODS

Nationally representative data were collected from 2015 through 2019 from 15 population-based household surveys. This analysis included women aged 15-49 who tested HIV-1 seronegative or had recent HIV-1. Least absolute shrinkage and selection operator regression models were fit with 28 variables to predict recent HIV-1. Models were trained on the full population and internally cross-validated. Performance was evaluated using area under the receiver operating characteristic curve (AUC), sensitivity, and number needed to treat (NNT) with PrEP to avert 1 infection.

RESULTS

Among 209 012 participants, 248 had recent HIV-1 infection, representing 118 million women and 402 000 (95% confidence interval [CI], 309 000-495 000) annual infections. Two variables were retained: living in a subnational area with high HIV-1 viremia and having a sexual partner living outside the home. The full-population AUC was 0.80 (95% CI, .76-.84); cross-validated AUC was 0.79 (95% CI, .75-.84). At 33% sensitivity, 130 000 cases could be averted if 7.9 million women were perfectly adherent to PrEP; NNT would be 61. At 67% sensitivity, 260 000 cases could be averted if 25.1 million women were perfectly adherent; NNT would be 96.

CONCLUSIONS

This risk assessment tool was generalizable, predictive, and parsimonious with trade-offs between reach and efficiency.

Dynamic HIV risk differentiation among youth: Validation of a tool for prioritization of prevention in East Zimbabwe

Background

Differentiating risk for HIV infection is important for providing focussed prevention options to individuals. We conducted a longitudinal study to validate a risk-differentiation tool for predicting HIV or HSV-2 acquisition among HIV-negative youth.

Setting

Population-based household survey in east Zimbabwe.

Methods

HIV and HSV-2 status and HIV behavioural risk factors were assessed in two surveys conducted 12 months apart among young people. Associations between risk-behaviours and combined HIV/HSV-2 incident infection were estimated using proportional hazards models. We calculated the sensitivity and specificity of risk-differentiation questions in predicting HIV/HSV-2 acquisition and quantified changes between surveys among low, medium, and high-risk categories.

Results

In total, 44 HIV/HSV-2 seroconversions were observed in 1812 person-years of follow up (2.43/100PY, 95%CI: 1.71-3.15); 50% of incident cases reported never having had sex at baseline. Risk of HIV/HSV-2 acquisition was higher for those reporting non-regular partners (women: HR=2.71, 95% CI:1.12-6.54, men: HR=1.37, 95%CI: 0.29-6.38) and those reporting having a partner with a sexually transmitted infection (STI) (HR=7.62 (1.22-47.51). Adding a question on non-regular partnerships increased tool sensitivity from 18.2% to 38.6%, and further to 77.3% when restricted to those who had ever had sex. Individual risk category increased for 28% of men and 17% of women over 12-months.

Conclusion

The refined risk differentiation tool identified a high proportion of youth at risk of HIV acquisition. Despite this, half of incident infections were among individuals who reported no prior sexual activity. The shifting patterns of risk behaviours underscore the need for dynamic prevention engagement strategies in high HIV prevalence or incidence settings.

Predicting the individualized risk of human immunodeficiency virus infection among sexually active women in Ethiopia using a nomogram: prediction model development and validation

Introduction

Women are more vulnerable to HIV infection due to biological and socioeconomic reasons. Developing a predictive model for these vulnerable populations to estimate individualized risk for HIV infection is relevant for targeted preventive interventions. The objective of the study was to develop and validate a risk prediction model that allows easy estimations of HIV infection risk among sexually active women in Ethiopia.

Methods

Data from the 2016 Ethiopian Demographic and Health Survey, which comprised 10,253 representative sexually active women, were used for model development. Variables were selected using the least absolute shrinkage and selection operator (LASSO). Variables selected by LASSO were incorporated into the multivariable mixed-effect logistic regression model. Based on the multivariable model, an easy-to-use nomogram was developed to facilitate its applicability. The performance of the nomogram was evaluated using discrimination and calibration abilities, Brier score, sensitivity, and specificity. Internal validation was carried out using the bootstrapping method.

Results

The model selected seven predictors of HIV infection, namely, age, education, marital status, sex of the household head, age at first sex, multiple sexual partners during their lifetime, and residence. The nomogram had a discriminatory power of 89.7% (95% CI: 88.0, 91.5) and a calibration p-value of 0.536. In addition, the sensitivity and specificity of the nomogram were 74.1% (95% CI: 68.4, 79.2) and 80.9% (95% CI: 80.2, 81.7), respectively. The internally validated model had a discriminatory ability of 89.4% (95% CI: 87.7, 91.1) and a calibration p-value of 0.195. Sensitivity and specificity after validation were 72.9% (95% CI: 67.2, 78.2) and 80.1% (95% CI: 79.3, 80.9), respectively.

Conclusion

A new prediction model that quantifies the individualized risk of HIV infection has been developed in the form of a nomogram and internally validated. It has very good discriminatory power and good calibration ability. This model can facilitate the identification of sexually active women at high risk of HIV infection for targeted preventive measures.

Enhancing HIV positivity yield in southern Mozambique: The effect of a Ministry of Health training module in targeted provider-initiated testing and counselling

In Mozambique, targeted provider-initiated HIV testing and counselling (PITC) is recommended where universal PITC is not feasible, but its effectiveness depends on healthcare providers' training. This study aimed to evaluate the effect of a Ministry of Health training module in targeted PITC on the HIV positivity yield, and identify factors associated with a positive HIV test. We conducted a single-group pre-post study between November 2018 and November 2019 in the triage and emergency departments of four healthcare facilities in Manhiça District, a resource-constrained semi-rural area. It consisted of two two-month phases split by a one-week targeted PITC training module ("observation phases"). The HIV positivity yield of targeted PITC was estimated as the proportion of HIV-positive individuals among those recommended for HIV testing by the provider. Additionally, we extracted aggregated health information system data over the four months preceding and following the observation phases to compare yield in real-world conditions ("routine phases"). Logistic regression analysis from observation phase data was conducted to identify factors associated with a positive HIV test. Among the 7,102 participants in the pre- and post-training observation phases (58.5% and 41.5% respectively), 68% were women, and 96% were recruited at triage. In the routine phases with 33,261 individuals (45.8% pre, 54.2% post), 64% were women, and 84% were seen at triage. While HIV positivity yield between pre- and post-training observation phases was similar (10.9% (269/2470) and 11.1% (207/1865), respectively), we observed an increase in yield in the post-training routine phase for women in triage, rising from 4.8% (74/1553) to 7.3% (61/831) (Yield ratio = 1.54; 95%CI: 1.11-2.14). Age (25-49 years) (OR = 2.43; 95%CI: 1.37-4.33), working in industry/mining (OR = 4.94; 95%CI: 2.17-11.23), unawareness of partner's HIV status (OR = 2.50; 95%CI: 1.91-3.27), and visiting a healer (OR = 1.74; 95%CI: 1.03-2.93) were factors associated with a positive HIV test. Including these factors in the targeted PITC algorithm could have increased new HIV diagnoses by 2.6%. In conclusion, providing refresher training and adapting the current targeted PITC algorithm through further research can help reach undiagnosed PLHIV, treat all, and ultimately eliminate HIV, especially in resource-limited rural areas.

Rates of sexual partner acquisition from nationally representative surveys: variation between countries and by age, sex, wealth, partner and HIV status

BACKGROUND

Knowing levels and determinants of partnership acquisition will help inform interventions that try to reduce transmission of sexually transmitted infections (STIs) including HIV.

METHODS

We used population-based, cross-sectional data from 47 Demographic and Health Surveys to calculate rates of partner acquisition among men and women (15-49years), and identified socio-demographic correlates for partner acquisition. Partner acquisition rates were estimated as the total number of acquisitions divided by the person-time in the period covered by the survey. For each survey and by sex, we estimated age-specific partner acquisition rates and used age-adjusted piecewise exponential survival models to explore whether there was any association between wealth, HIV status and partner status with partner acquisition rates.

RESULTS

Across countries, the median partner acquisition rates were 30/100 person-years for men (interquartile range 21-45) and 13/100 person-years for women (interquartile range 6-18). There were substantial variations in partner acquisition rates by age. Associations between wealth and partner acquisition rates varied across countries. People with a cohabiting partner were less likely to acquire a new one, and this effect was stronger for women than men and varied substantially between countries. Women living with HIV had higher partner acquisition rates than HIV-negative women but this association was less apparent for men. At a population level, partner acquisition rates were correlated with HIV incidence.

CONCLUSIONS

Partner acquisition rates are variable and are associated with important correlates of STIs and thus could be used to identify groups at high risk of STIs.

Risk Factors for Recent HIV Infections among Adults in 14 Countries in Africa Identified by Population-Based HIV Impact Assessment Surveys, 2015-2019

Identifying persons who have newly acquired HIV infections is critical for characterizing the HIV epidemic direction. We analyzed pooled data from nationally representative Population-Based HIV Impact Assessment surveys conducted across 14 countries in Africa for recent infection risk factors. We included adults 15-49 years of age who had sex during the previous year and used a recent infection testing algorithm to distinguish recent from long-term infections. We collected risk factor information via participant interviews and assessed correlates of recent infection using multinomial logistic regression, incorporating each survey's complex sampling design. Compared with HIV-negative persons, persons with higher odds of recent HIV infection were women, were divorced/separated/widowed, had multiple recent sex partners, had a recent HIV-positive sex partner or one with unknown status, and lived in communities with higher HIV viremia prevalence. Prevention programs focusing on persons at higher risk for HIV and their sexual partners will contribute to reducing HIV incidence.

Developing HIV risk prediction tools in four African settings

OBJECTIVE

HIV risk prediction tools are a critical component of efforts to end the HIV pandemic. We aimed to create and validate tools for identifying individuals at highest risk of prevalent and incident HIV in an African setting.

METHODS

We used Logistic regression and Poisson regression to determine risk factors for HIV prevalence and incidence in a multi-country HIV vaccine trial preparedness cohort study among individuals at high risk of HIV, and used the identified factors to create and validate tools that predict HIV risk. We also assessed the performance of the VOICE risk score in predicting HIV incidence among women in the cohort.

RESULTS

The prevalent HIV prediction tool created had good predictive ability [area under the curve (AUC) = 0.70, 95% CI 0.66-0.74]. It included the following participant variables: age, sex, recreational drug use, unprotected male-to-male anal sex, a sexual partner who had other partners, transactional sex and having a partner who was a long-distance truck driver/miner. It was not possible to create a valid HIV incidence prediction tool. Participants with high VOICE risk scores (≥7) had slightly higher HIV incidence but this tool performed poorly within our study (AUC = 0.58, 95% CI 0.51-0.64: Harrell's concordance index = 0.59).

CONCLUSION

We created a prevalent HIV prediction tool that could be used to increase efficiency in diagnosis of HIV and linkage to care in sub-Saharan Africa. Existing incident HIV prediction tools may need modification to include context-specific predictors such as calendar period, participant occupation, study site, before adoption in settings different from those in which they were developed.

Spatio-temporal estimates of HIV risk group proportions for adolescent girls and young women across 13 priority countries in sub-Saharan Africa

The Global AIDS Strategy 2021-2026 identifies adolescent girls and young women (AGYW) as a priority population for HIV prevention, and recommends differentiating intervention portfolios geographically based on local HIV incidence and individual risk behaviours. We estimated prevalence of HIV risk behaviours and associated HIV incidence at health district level among AGYW living in 13 countries in sub-Saharan Africa. We analysed 46 geospatially-referenced national household surveys conducted between 1999-2018 across 13 high HIV burden countries in sub-Saharan Africa. Female survey respondents aged 15-29 years were classified into four risk groups (not sexually active, cohabiting, non-regular or multiple partner[s] and female sex workers [FSW]) based on reported sexual behaviour. We used a Bayesian spatio-temporal multinomial regression model to estimate the proportion of AGYW in each risk group stratified by district, year, and five-year age group. Using subnational estimates of HIV prevalence and incidence produced by countries with support from UNAIDS, we estimated new HIV infections in each risk group by district and age group. We then assessed the efficiency of prioritising interventions according to risk group. Data consisted of 274,970 female survey respondents aged 15-29. Among women aged 20-29, cohabiting (63.1%) was more common in eastern Africa than non-regular or multiple partner(s) (21.3%), while in southern countries non-regular or multiple partner(s) (58.9%) were more common than cohabiting (23.4%). Risk group proportions varied substantially across age groups (65.9% of total variation explained), countries (20.9%), and between districts within each country (11.3%), but changed little over time (0.9%). Prioritisation based on behavioural risk, in combination with location- and age-based prioritisation, reduced the proportion of population required to be reached in order to find half of all expected new infections from 19.4% to 10.6%. FSW were 1.3% of the population but 10.6% of all expected new infections. Our risk group estimates provide data for HIV programmes to set targets and implement differentiated prevention strategies outlined in the Global AIDS Strategy. Successfully implementing this approach would result in more efficiently reaching substantially more of those at risk for infections.

Adult HIV-1 incidence across 15 high-burden countries in sub-Saharan Africa from 2015 to 2019: a pooled analysis of nationally representative data

BACKGROUND

Harmonised population-based surveys with recent HIV-1 infection testing algorithms permit pooled cross-sectional estimation of HIV incidence across multiple countries. We aimed to estimate adult HIV-1 incidence rates and number of new infections by sex, age, and subregion in sub-Saharan Africa.

METHODS

We analysed data from 13 Population-Based HIV Impact Assessment (PHIA) surveys and two additional population-based surveys done between 2015 and 2019 in 15 sub-Saharan African countries. HIV-seropositive samples from adults aged 15-59 years were tested for recent HIV-1 infection by use of an algorithm consisting of the HIV-1 limiting antigen avidity enzyme immunoassay, HIV-1 viral load, and qualitative detection of antiretroviral agents. Data were pooled across countries; sampling weights were incorporated to represent all adults in the 15 national populations. Analyses accounted for the complex sample designs. HIV incidence rates, incidence rate differences, and number of new annual infections were estimated.

FINDINGS

Among 445 979 adults sampled, 382 had recent HIV-1 infection. The estimated HIV-1 incidence rate was 3·3 per 1000 person-years (95% CI 2·6-4·0) among women and 2·0 per 1000 person-years (1·2-2·7) among men (incidence rate difference 1·3 per 1000 person-years, 95% CI 0·3-2·3). Among adults aged 15-24 years, the incidence rate was higher for women (3·5 per 1000 person-years) than men (1·2 per 1000 person-years; difference 2·3, 95% CI 0·8-3·8), but infection rates were similar between sexes in all other age groups. The HIV-1 incidence rate was 7·4 per 1000 person-years (95% CI 5·0-9·7) in southern sub-Saharan Africa, 2·3 per 1000 person-years (1·7-2·9) in the eastern subregion, and 0·9 per 1000 person-years (0·6-1·2) in the western and central subregion. 689 000 (95% CI 546 000-833 000) new HIV cases were estimated annually among the 265 million susceptible adults (61·6% in women).

INTERPRETATION

HIV-1 incidence and number of new infections differed by age, sex, and subregion. Approaches for risk stratification are needed to guide comprehensive HIV-1 prevention.

FUNDING

National Institutes of Health.