From general to specific: moving past the general population in the HIV response across sub-Saharan Africa

Challenges and Opportunities in Big Data Science to Address Health Inequities and Focus the HIV Response

PURPOSE OF REVIEW

Big Data Science can be used to pragmatically guide the allocation of resources within the context of national HIV programs and inform priorities for intervention. In this review, we discuss the importance of grounding Big Data Science in the principles of equity and social justice to optimize the efficiency and effectiveness of the global HIV response.

RECENT FINDINGS

Social, ethical, and legal considerations of Big Data Science have been identified in the context of HIV research. However, efforts to mitigate these challenges have been limited. Consequences include disciplinary silos within the field of HIV, a lack of meaningful engagement and ownership with and by communities, and potential misinterpretation or misappropriation of analyses that could further exacerbate health inequities. Big Data Science can support the HIV response by helping to identify gaps in previously undiscovered or understudied pathways to HIV acquisition and onward transmission, including the consequences for health outcomes and associated comorbidities. However, in the absence of a guiding framework for equity, alongside meaningful collaboration with communities through balanced partnerships, a reliance on big data could continue to reinforce inequities within and across marginalized populations.

Using a Programme Science approach to substantially reduce the risk of HIV transmission and acquisition in sex transactions among female sex workers in Zimbabwe

INTRODUCTION

We used a Programme Science platform, to generate evidence to support the implementation of programmes for sex workers in Africa. Female sex workers are estimated to make up 1.6% (1.3%-1.8%) of the population of women aged 15-49 years in Zimbabwe. We highlight how programme science can be used to help distinguish between when, where and with whom programmes need to be implemented and discuss two case studies that exemplify implementing better (Case study 1 (1 June 2019-30 June 2021) Optimizing implementation of a risk differentiated microplanning intervention) and implementing differently (Case study 2 (1 October 2016-30 September 2022) Reorientating implementation of DREAMS for young women selling sex).

METHODS

Zimbabwe's nationally scaled programme for sex workers was established in 2009 in partnership with sex workers to provide comprehensive services for sex workers and generate evidence for programme design, implementation and scale up. Since inception, comprehensive data have been collected from all sex workers seeking services. As the scope of service provision has expanded so has the scope of data collection and analysis. At enrolment, sex workers are assigned an alphanumeric unique identifier which links consultations within and across programme sites. We conduct descriptive analyses of the Key Population (KP) programme data to guide programme implementation and redesign, embedding programmatic qualitative enquiry as required.

RESULTS

Two case studies describing different approaches to programme optimization are presented. In the first, an optimization exercise was used to strengthen programme implementation ensuring that the KP programme got back on track after SARS-COV-2. In the second, an in-depth review of research and programme data led to a re-orientation of the DREAMS programme to ensure that young women at the highest risk of HIV acquisition were enrolled and had access to DREAMS social support interventions in turn strengthening their uptake of HIV prevention.

CONCLUSIONS

Optimizing and sustaining HIV care and treatment programmes requires effective delivery with sufficient scale and intensity for population impact. Our programme science approach guided the scale up of the KP programme in Zimbabwe, providing evidence to support strategy, implementation and ongoing management, and importantly helping us distinguish between when we needed to just implement, implement better or implement differently.

Impact of family networks on uptake of health interventions: evidence from a community-randomized control trial aimed at increasing HIV testing in South Africa

INTRODUCTION

While it is widely acknowledged that family relationships can influence health outcomes, their impact on the uptake of individual health interventions is unclear. In this study, we quantified how the efficacy of a randomized health intervention is shaped by its pattern of distribution in the family network.

METHODS

The "Home-Based Intervention to Test and Start" (HITS) was a 2×2 factorial community-randomized controlled trial in Umkhanyakude, KwaZulu-Natal, South Africa, embedded in the Africa Health Research Institute's population-based demographic and HIV surveillance platform (ClinicalTrials.gov # NCT03757104). The study investigated the impact of two interventions: a financial micro-incentive and a male-targeted HIV-specific decision support programme. The surveillance area was divided into 45 community clusters. Individuals aged ≥15 years in 16 randomly selected communities were offered a micro-incentive (R50 [$3] food voucher) for rapid HIV testing (intervention arm). Those living in the remaining 29 communities were offered testing only (control arm). Study data were collected between February and November 2018. Using routinely collected data on parents, conjugal partners, and co-residents, a socio-centric family network was constructed among HITS-eligible individuals. Nodes in this network represent individuals and ties represent family relationships. We estimated the effect of offering the incentive to people with and without family members who also received the offer on the uptake of HIV testing. We fitted a linear probability model with robust standard errors, accounting for clustering at the community level.

RESULTS

Overall, 15,675 people participated in the HITS trial. Among those with no family members who received the offer, the incentive's efficacy was a 6.5 percentage point increase (95% CI: 5.3-7.7). The efficacy was higher among those with at least one family member who received the offer (21.1 percentage point increase (95% CI: 19.9-22.3). The difference in efficacy was statistically significant (21.1-6.5 = 14.6%; 95% CI: 9.3-19.9).

CONCLUSIONS

Micro-incentives appear to have synergistic effects when distributed within family networks. These effects support family network-based approaches for the design of health interventions.

Low engagement of key populations in HIV health services in Tanzania: analysis of community, legal and policy factors

Introduction

key populations (KP) often face legal and social challenges that increase their vulnerability to HIV. These experiences include criminalization, higher levels of stigma and discrimination which negatively affect access to HIV services. This study aims to understand legal, community and policy factors affecting engagement of KP in HIV health interventions.

Methods

qualitative research key populations design involving a desk review and stakeholder's engagement. We reviewed program data from NACP on how KP access health services and then conducted three stakeholders' engagement meetings. Factors affecting access to health services by KP were documented. Data were organized using socio-ecological model (SEM).

Results

program data showed only 49% of the estimated KP accessed health services. Barriers to accessing health services at the interpersonal level included lack of social support and high-risk networks linked with risk behaviours. At the community, stigma and discrimination, limited engagement of influential leaders were noted. In health facilities, lack of trained staff to provide KP friendly services affected utilization of health services. At structural level, despite improvements, still various laws negated engagement of KP such criminalizing drug use, same sex, and sex work. Harassments and arrests further marginalize KP and makes access to health intervention harder.

Conclusion

engagement of key population into HIV health interventions was limited at multiple levels. The study recommends building capacity on KP friendly services for communities, law enforcement and health care providers, further engagement of communities including religious leaders on KP issues and implementing differentiated service delivery models for KP.

A Systematic Review of Linkage-to-Care and Antiretroviral Initiation Implementation Strategies in Low- and Middle-Income Countries Across Sub-Saharan Africa

Linkage to care (LTC) and initiation of antiretroviral therapy (ART) are key components in the longitudinal care cascade for people living with HIV. Many strategies to optimize these stages of HIV care have been implemented, though there is a paucity of analyses comparing the outcomes of these efforts in low- and middle-income countries. We conducted a systematic review of studies assessing interventions along all stages of the HIV care continuum published between 2008 and 2020. A comprehensive search strategy reviewed five electronic databases to capture studies assessing HIV testing, LTC, ART initiation, ART adherence, and viral suppression. Of the 388 articles that met the inclusion criteria, 78 described interventions for improving LTC/ART initiation. Efforts focused on empowering patients through integrative approaches generally yielded more substantive results compared to provider-initiated non-adaptive LTC interventions or cash incentives. Specifically, tailoring care and incorporating ART initiation into existing infrastructures, such as maternal clinics, had a high impact across settings. Moreover, strategies such as home-based HIV counseling and testing (HBHCT) appear to be most effective when implemented in tandem with other approaches including motivational counseling and point-of-care CD4 testing.

Quantifying rates of HIV-1 flow between risk groups and geographic locations in Kenya: A country-wide phylogenetic study

In Kenya, HIV-1 key populations including men having sex with men (MSM), people who inject drugs (PWID) and female sex workers (FSW) are thought to significantly contribute to HIV-1 transmission in the wider, mostly heterosexual (HET) HIV-1 transmission network. However, clear data on HIV-1 transmission dynamics within and between these groups are limited. We aimed to empirically quantify rates of HIV-1 flow between key populations and the HET population, as well as between different geographic regions to determine HIV-1 'hotspots' and their contribution to HIV-1 transmission in Kenya. We used maximum-likelihood phylogenetic and Bayesian inference to analyse 4058 HIV-1 pol sequences (representing 0.3 per cent of the epidemic in Kenya) sampled 1986-2019 from individuals of different risk groups and regions in Kenya. We found 89 per cent within-risk group transmission and 11 per cent mixing between risk groups, cyclic HIV-1 exchange between adjoining geographic provinces and strong evidence of HIV-1 dissemination from (i) West-to-East (i.e. higher-to-lower HIV-1 prevalence regions), and (ii) heterosexual-to-key populations. Low HIV-1 prevalence regions and key populations are sinks rather than major sources of HIV-1 transmission in Kenya. Targeting key populations in Kenya needs to occur concurrently with strengthening interventions in the general epidemic.

Estimating the epidemic consequences of HIV prevention gaps among key populations

INTRODUCTION

HIV epidemic appraisals are used to characterize heterogeneity and inequities in the context of the HIV pandemic and the response. However, classic measures used in appraisals have been shown to underestimate disproportionate risks of onward transmission, particularly among key populations. In response, a growing number of modelling studies have quantified the consequences of unmet prevention and treatment needs (prevention gaps) among key populations as a transmission population attributable fraction over time (tPAFt ). To aid its interpretation and use by programme implementers and policy makers, we outline and discuss a conceptual framework for understanding and estimating the tPAFt via transmission modelling as a measure of onward transmission risk from HIV prevention gaps; and discuss properties of the tPAFt .

DISCUSSION

The distribution of onward transmission risks may be defined by who is at disproportionate risk of onward transmission, and under which conditions. The latter reflects prevention gaps, including secondary prevention via treatment: the epidemic consequences of which may be quantified by the tPAFt . Steps to estimating the tPAFt include parameterizing the acquisition and onward transmission risks experienced by the subgroup of interest, defining the most relevant counterfactual scenario, and articulating the time-horizon of analyses and population among whom to estimate the relative difference in cumulative transmissions; such steps could reflect programme-relevant questions about onward transmission risks. Key properties of the tPAFt include larger onward transmission risks over longer time-horizons; seemingly mutually exclusive tPAFt measures summing to greater than 100%; an opportunity to quantify the magnitude of disproportionate onward transmission risks with a per-capita tPAFt ; and that estimates are conditional on what has been achieved so far in reducing prevention gaps and maintaining those conditions moving forward as the status quo.

CONCLUSIONS

The next generation of HIV epidemic appraisals has the potential to support a more specific HIV response by characterizing heterogeneity in disproportionate risks of onward transmission which are defined and conditioned on the past, current and future prevention gaps across subsets of the population.

Bringing HIV services to key populations and their communities in Tanzania: from pilot to scale

INTRODUCTION

Despite the global scale-up of HIV testing, prevention and treatment, these services remain inaccessible to groups most vulnerable to HIV. Globally, most new HIV infections are concentrated among members of key populations (KP), including female sex workers, men who have sex with men, transgender people, people who inject drugs and their sexual partners. These populations lag in access to HIV prevention and antiretroviral therapy (ART) and have less favourable HIV outcomes compared to the general population. Intersecting behavioural and structural factors contribute to these gaps in service access for at-risk KP and those living with HIV; corresponding comprehensive approaches to improving service delivery for KP are urgently needed. Differentiated service delivery (DSD) models tailor HIV programmes to the needs and preferences of specific groups but are rarely implemented at scale for KP. We describe the FIKIA Project, which implemented innovative approaches to scaling up DSD models to reach and engage KP in Tanzania.

METHODS

The FIKIA Project worked with diverse KP communities in Tanzania to tailor HIV services to their needs and to pair healthcare workers with trained peer educators and expert client counsellors to expand uptake of community-based HIV testing and ART services. We analysed routine aggregate project data from 2016 to 2020 to describe project implementation, outcomes and best practices.

RESULTS AND DISCUSSION

The FIKIA Project conducted 1,831,441 HIV tests in community settings; of the 98,349 (5.4%) individuals with new HIV diagnoses, 89,640 (91.1%) initiated ART. The project reached substantial numbers of KP: 203,233 received HIV tests, 28,830 (14.2%) received a new HIV diagnosis and 25,170 KP (87.3%) initiated ART at the point of diagnosis. Over time, HIV testing increased by 1.6 times overall (2.3 times among KP), HIV diagnoses increased by 8.7 times (10.9 times among KP) and ART initiation at the point of diagnosis increased from 80.0% to 95.9% overall (from 69.6% to 94.9% among KP).

CONCLUSIONS

Over four years, the FIKIA Project scaled up HIV testing, diagnosis and treatment by using DSD principles to design services that meet the needs of KP and their communities.

Reductions in HIV incidence are likely to increase the importance of key population programmes for HIV control in sub-Saharan Africa

INTRODUCTION

An efficient HIV response requires that resources be focussed on effective interventions for those most at risk of acquiring and transmitting infection. As HIV epidemics evolve the distribution of HIV across key and other populations will change. Here, the epidemiological concepts underpinning these changes are described and the importance of appropriate allocation of effective interventions is discussed.

DISCUSSION

In many sub-Saharan African countries HIV epidemics have been categorized as "generalized," and HIV testing, treatment and prevention interventions have focussed on the "general" population. As HIV epidemics are better controlled the relative importance of "key" populations will increase, dominating the ongoing burden of disease and providing the potential for repeated outbreaks of HIV if interventions are relaxed. The basic reproductive number (R0 ) describes the potential for an infectious disease to spread at the boundary of invasion or elimination, whereas the effective reproduction number (Rt ) describes the current potential for spread. Heterogeneity in risk means that while Rt is temporarily below one and prevalence declining, the R0 can remain above one, preventing eventual elimination. Patterns of HIV acquisition are often used to guide interventions but inadequately capture the transmission dynamics of the virus and the most efficient approach to controlling HIV. Risks for HIV acquisition are not identical to risks for HIV transmission and will change depending on the epidemiological context. In addition to the challenges in measuring HIV transmission dynamics, there is a tension between using epidemiology to drive the HIV response and the social and political realities constraining how programmes and providers can practically and appropriately focus on key populations and maintain political support. In addition to being well focussed, interventions need to be effective and cost-effective, which requires a better understanding of packages of interventions rather than specific tools.

CONCLUSIONS

Continued control of HIV will increasingly rely on resources, programmes and interventions supporting key populations. Current epidemiological and programmatic approaches for key populations in sub-Saharan Africa are insufficient with a need for an improved understanding of local epidemiology and the effectiveness of interventions.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.