Associated organisationsAlliance for Public Health · Imperial College London · Johns Hopkins University School of Medicine · London School of Hygiene & Tropical Medicine · McGill University · Pac-Ci · University of BristolEurope PMC affiliations are not treated as award recipients or mapped locations.
Funding£5.1M
PeriodJul 2023 — Jun 2031
In plain English
AI plain-English summary
HIV infections are still rising among sex workers, people who inject drugs, and other key populations, even where effective treatments exist. The problem is not just medical. Laws that criminalise these groups, police harassment, and social stigma all block access to prevention and care. But no one has systematically measured how much these structural factors actually drive transmission, or whether changing them would be cost-effective. This project will fill that gap. The researchers will combine global longitudinal datasets with new mathematical models that explicitly include these causal pathways. They will estimate how much structural factors contribute to new infections, and then model the impact and cost-effectiveness of specific societal enablers—such as decriminalisation, anti-discrimination laws, or peer-led services—across different countries and populations. If successful, the work will give national and global policymakers the quantitative evidence they need to include societal enablers in HIV elimination plans. That could shift funding and strategy away from purely biomedical interventions toward structural reforms, making the 2030 elimination target more realistic for the people currently being left behind.
View original technical description
Despite international efforts to eliminate HIV/AIDS, infection levels remain high among key populations (KPs). Although effective interventions exist, evolving evidence suggests structural factors limit their impact and increase HIV transmission among KPs. Initiatives to reduce these factors (societal enablers) are a focus of new global HIV elimination strategies, but little evidence exists on the contribution of structural factors to HIV transmission or the potential impact of societal enablers. The proposed research will develop a novel evidence-based statistical and modelling framework to improve this evidence base. We will conduct epidemiological analyses to improve our quantitative understanding of the causal pathways between structural factors and HIV-risk, utilising global longitudinal datasets. We will then develop new mathematical models that include these causal pathways to robustly estimate the contribution of structural factors to HIV transmission and evaluate the impact and cost-effectiveness of societal enablers across diverse KPs and countries. The project will transform the evidence and methodologies used to evaluate the effect of structural factors and interventions to mitigate their effects. It will result in a step change through enabling evidence-based planning for including societal enablers in HIV programming for KPs, with insights being crucial for national/global policymakers aiming to eliminate HIV/AIDS by 2030.
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