Investing in Optimized HIV Prevention Among Young Men Who Have Sex With Men in Brazil: Insights From Fiscal Health Modeling
Author(s)
Natalya Danchenko, PhD1, Straus Tanaka, BS2, George Bray, MSc3, Matthew Napier, MSc3, Frederick McElwee, MSc4, Hania El Banhawi, MSc3, Simon Brassel, MS3, Lotte Steuten, PhD, MSc3, Sarah-Jane Anderson, PhD5, Ian Jacob, MSc6;
1GSK / ViiV, Global Health Outcomes, Rueil-Malmaison, France, 2GSK, Rio de Janeiro, Brazil, 3Office of Health Economics, London, United Kingdom, 4Office of Health Economics, London, United Kingdom; Health Economics Research Centre, University of Oxford, Oxford, United Kingdom, 5GSK, London, United Kingdom, 6ViiV Healthcare, London, United Kingdom
1GSK / ViiV, Global Health Outcomes, Rueil-Malmaison, France, 2GSK, Rio de Janeiro, Brazil, 3Office of Health Economics, London, United Kingdom, 4Office of Health Economics, London, United Kingdom; Health Economics Research Centre, University of Oxford, Oxford, United Kingdom, 5GSK, London, United Kingdom, 6ViiV Healthcare, London, United Kingdom
Presentation Documents
OBJECTIVES: Despite public availability of daily oral pre-exposure prophylaxis (PrEP) since 2018, HIV diagnoses have increased in Brazil, suggesting suboptimal PrEP uptake and adherence. To assess the fiscal impact of optimizing HIV prevention among young men who have sex with men (aged 15-29), we developed a fiscal health model (FHM) that evaluates its return on investment from a governmental perspective in Brazil.
METHODS: The FHM links individual health states of a multicohort Markov model to 4 fiscal states (formally employed, informally employed, unemployed, retired). The model compares the status quo, reflecting current provision of HIV prevention, with optimized prevention, which includes availability of long-acting PrEP and outreach programs to increase PrEP uptake and adherence. Outcomes are presented as an average fiscal benefit-cost ratio across all age cohorts’ lifetimes and the corresponding aggregated fiscal net benefit discounted at 5%. Scenario analyses were conducted over the cohorts’ total lifetime and productive lifetime (excluding retirement phase) using either conservative estimates for viral suppression in people treated for HIV (80%) and employment reduction among individuals with CD4+ cell count <200 cells/mm3 (36.5%) or assumptions that likely better reflect real-world values (viral suppression, 47.75%; employment reduction, 50%).
RESULTS: In all scenarios, optimizing HIV prevention averts ~70,000 HIV diagnoses. With conservative estimates, optimizing HIV prevention recoups 97% of the investment over the cohorts’ total lifetimes and generates a 7% return over their productive lifetimes, representing a loss of R$0.3 billion and return of R$0.8 billion, respectively. With real-world estimates, optimizing HIV prevention generates a return of 10% and 22% over the total lifetimes and productive lifetimes, respectively.
CONCLUSIONS: Optimizing HIV prevention in young men who have sex with men shows a positive return on investment. Decision-makers should consider long-term perspectives to ensure opportunities to improve population health and contribute to a stronger economy are realized.
METHODS: The FHM links individual health states of a multicohort Markov model to 4 fiscal states (formally employed, informally employed, unemployed, retired). The model compares the status quo, reflecting current provision of HIV prevention, with optimized prevention, which includes availability of long-acting PrEP and outreach programs to increase PrEP uptake and adherence. Outcomes are presented as an average fiscal benefit-cost ratio across all age cohorts’ lifetimes and the corresponding aggregated fiscal net benefit discounted at 5%. Scenario analyses were conducted over the cohorts’ total lifetime and productive lifetime (excluding retirement phase) using either conservative estimates for viral suppression in people treated for HIV (80%) and employment reduction among individuals with CD4+ cell count <200 cells/mm3 (36.5%) or assumptions that likely better reflect real-world values (viral suppression, 47.75%; employment reduction, 50%).
RESULTS: In all scenarios, optimizing HIV prevention averts ~70,000 HIV diagnoses. With conservative estimates, optimizing HIV prevention recoups 97% of the investment over the cohorts’ total lifetimes and generates a 7% return over their productive lifetimes, representing a loss of R$0.3 billion and return of R$0.8 billion, respectively. With real-world estimates, optimizing HIV prevention generates a return of 10% and 22% over the total lifetimes and productive lifetimes, respectively.
CONCLUSIONS: Optimizing HIV prevention in young men who have sex with men shows a positive return on investment. Decision-makers should consider long-term perspectives to ensure opportunities to improve population health and contribute to a stronger economy are realized.
Conference/Value in Health Info
2025-05, ISPOR 2025, Montréal, Quebec, CA
Value in Health, Volume 28, Issue S1
Code
EE391
Topic
Economic Evaluation
Topic Subcategory
Novel & Social Elements of Value
Disease
SDC: Infectious Disease (non-vaccine)