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.

Quantifying and Predicting Ongoing Human Immunodeficiency Virus Type 1 Transmission Dynamics in Switzerland Using a Distance-Based Clustering Approach.

BACKGROUND: Despite effective prevention approaches, ongoing human immunodeficiency virus 1 (HIV-1) transmission remains a public health concern indicating a need for identifying its drivers. METHODS: We combined a network-based clustering method using evolutionary distances between viral sequences with statistical learning approaches to investigate the dynamics of HIV transmission in the Swiss HIV Cohort Study and to predict the drivers of ongoing transmission. RESULTS: We found that only a minority of clusters and patients acquired links to new infections between 2007 and 2020. While the growth of clusters and the probability of individual patients acquiring new links in the transmission network was associated with epidemiological, behavioral, and virological predictors, the strength of these associations decreased substantially when adjusting for network characteristics. Thus, these network characteristics can capture major heterogeneities beyond classical epidemiological parameters. When modeling the probability of a newly diagnosed patient being linked with future infections, we found that the best predictive performance (median area under the curve receiver operating characteristic AUCROC = 0.77) was achieved by models including characteristics of the network as predictors and that models excluding them performed substantially worse (median AUCROC = 0.54). CONCLUSIONS: These results highlight the utility of molecular epidemiology-based network approaches for analyzing and predicting ongoing HIV transmission dynamics. This approach may serve for real-time prospective assessment of HIV transmission.

Increasing sero-discordancy among young HIV infected pregnant women from India: a likely pointer of changing transmission dynamics.

The flat-lining of HIV incidence in India has raised concerns about the presence of emerging risk groups. As HIV prevalence among pregnant women is reflective of the situation in general population, its closer scrutiny provides valuable insights about the evolving epidemic. The present study assesses temporal trends of sero-discordance (where woman is HIV infected and husband is uninfected), among pregnant women living with HIV (pWLHIV) from India. Data of program for prevention of parent to child transmission of HIV was analyzed. Statistical analysis was done using Cochrane-Armitage trend test and logistic regression. Of the 1209 currently married pWLHIV, 302 (25%) were sero-discordant. The proportion increased from 16% in 2007 to 36% in 2016-17 (p = 0.000). The likelihood of sero-discordance was higher for women aged 18-20 (OR: 2.68, CI: 1.30-5.83) and 21-23 (OR: 1.98, CI: 1.01-4.15) years compared to 36-40 years; and for primi-parous women (OR: 1.84, CI: 1.31-2.58) compared to women pregnant for second/third time. The findings are indicative of changing HIV transmission dynamics. Steeper rise in sero-discordance in younger women implies an increasing risk of HIV in unmarried women population. A better understanding of HIV specific vulnerabilities of young women, married and unmarried, is warranted.

Ethical issues associated with HIV phylogenetics in HIV transmission dynamics research: A review of the literature using the Emanuel Framework.

The reduced costs of DNA sequencing and the use of such data for HIV-1 clinical management and phylogenetic analysis have led to a massive increase of HIV-1 sequences in the last few years. Phylogenetic analysis has shed light on the origin, spread and characteristics of HIV-1 epidemics and outbreaks. Phylogenetic analysis is now also being used to advance our knowledge of the drivers of HIV-1 transmission in order to design effective interventions. However, HIV phylogenetic analysis presents unique ethical challenges, which have not been fully explored. This review presents an analysis of what appear to be key ethical issues in HIV phylogenetics in the hope of stimulating further conceptual and empirical work in this rapidly emerging area. We structure the review using the Emanuel Framework, a systematic, holistic framework, which has been adapted for use in developing countries, which bear the brunt of the HIV-1 pandemic.

Effective strategies to promote HIV self-testing for men who have sex with men: Evidence from a mathematical model.

BACKGROUND: HIV testing is the gateway to HIV treatment and prevention. HIV self-testing (HIVST) has potential to increase testing; however, the potential population-level impact of HIVST on the HIV epidemic and the best strategies for promoting HIVST are unknown. Our aim is to inform public health approaches for promoting HIVST as part of a comprehensive strategy to reduce HIV incidence. METHODS: Stochastic network-based HIV transmission models were used to estimate how different HIVST strategies would affect HIV incidence in Seattle and Atlanta over 10 years. We included four types of HIV testers and implemented nine replacement and eleven supplementation strategies for HIVST. RESULTS: Replacement of clinic-based tests with HIVST increased HIV incidence in Seattle and Atlanta. The benefits of supplementary strategies depended on the tester type using HIVST. Targeting non-testers averted the highest number of cases per test. In Seattle 2.2 (95%SI=-77, 100.4) and 4.7 (95%SI=-35.7, 60.1) infections were averted per 1000 HIVST when non-testers used HIVST once or twice per year respectively. In Atlanta the comparable rates were 8.0 (95%SI=-60.3 to 77.7) and 6.7 (95%SI=-37.7, 41.0). Paradoxically, increasing testing among risk-based testers using HIVST increased incidence. CONCLUSIONS: The population-level impact of HIVST depends on who is reached with HIVST, how kits are used, and by characteristics of the underlying epidemic and HIV care infrastructure. Targeted HIVST can be an effective component of a comprehensive HIV testing strategy. More work is needed to understand how to identify and target non-testers for self-testing implementation.