Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Mar 22;17(3):e0265253.
doi: 10.1371/journal.pone.0265253. eCollection 2022.

Evaluating the impact of social determinants, conditional cash transfers and primary health care on HIV/AIDS: Study protocol of a retrospective and forecasting approach based on the data integration with a cohort of 100 million Brazilians

Affiliations

Evaluating the impact of social determinants, conditional cash transfers and primary health care on HIV/AIDS: Study protocol of a retrospective and forecasting approach based on the data integration with a cohort of 100 million Brazilians

Davide Rasella et al. PLoS One. .

Abstract

Background: Despite the great progress made over the last decades, stronger structural interventions are needed to end the HIV/AIDS pandemic in Low and Middle-Income Countries (LMIC). Brazil is one of the largest and data-richest LMIC, with rapidly changing socioeconomic characteristics and an important HIV/AIDS burden. Over the last two decades Brazil has also implemented the world's largest Conditional Cash Transfer programs, the Bolsa Familia Program (BFP), and one of the most consolidated Primary Health Care (PHC) interventions, the Family Health Strategy (FHS).

Objective: We will evaluate the effects of socioeconomic determinants, BFP exposure and FHS coverage on HIV/AIDS incidence, treatment adherence, hospitalizations, case fatality, and mortality using unprecedently large aggregate and individual-level longitudinal data. Moreover, we will integrate the retrospective datasets and estimated parameters with comprehensive forecasting models to project HIV/AIDS incidence, prevalence and mortality scenarios up to 2030 according to future socioeconomic conditions and alternative policy implementations.

Methods and analysis: We will combine individual-level data from all national HIV/AIDS registries with large-scale databases, including the "100 Million Brazilian Cohort", over a 19-year period (2000-2018). Several approaches will be used for the retrospective quasi-experimental impact evaluations, such as Regression Discontinuity Design (RDD), Random Administrative Delays (RAD) and Propensity Score Matching (PSM), combined with multivariable Poisson regressions for cohort analyses. Moreover, we will explore in depth lagged and long-term effects of changes in living conditions and in exposures to BFP and FHS. We will also investigate the effects of the interventions in a wide range of subpopulations. Finally, we will integrate such retrospective analyses with microsimulation, compartmental and agent-based models to forecast future HIV/AIDS scenarios.

Conclusion: The unprecedented datasets, analyzed through state-of-the-art quasi-experimental methods and innovative mathematical models will provide essential evidences to the understanding and control of HIV/AIDS epidemic in LMICs such as Brazil.

PubMed Disclaimer

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Conceptual framework of selected structural determinants of HIV/AIDS incidence and mortality, and of the hypothesized effects of cash transfer and PHC on this process.
*Note: Pre-Exposure Prophalaxis (PrEP) is not yet widespread in Brazil and cannot yet be assessed in this study.
Fig 2
Fig 2. Datasets for linkage and subsequent study cohorts.
Fig 3
Fig 3. Integrated microsimulation, compartmental and agent-based model.

Similar articles

Cited by

References

    1. UNAIDS leads the world’s most extensive data collection on HIV epidemiology, programme coverage and finance | UNAIDS. [cited 1 Feb 2022]. https://www.unaids.org/en/topic/data
    1. Dean HD, Fenton KA. Addressing social determinants of health in the prevention and control of HIV/AIDS, viral hepatitis, sexually transmitted infections, and tuberculosis. Public Health Rep Wash DC 1974. 2010;125 Suppl 4: 1–5. doi: 10.1177/00333549101250S401 - DOI - PMC - PubMed
    1. McMahan LD, Lombe M, Evans CBR, Enelamah NV, Chu Y, Simms S, et al.. Getting to zero HIV/AIDS in sub-Saharan Africa: Understanding perceptions of locals using the social determinants of health framework. Health Soc Care Community. 2021. doi: 10.1111/hsc.13444 - DOI - PubMed
    1. Rudgard WE, Carter DJ, Scuffell J, Cluver LD, Fraser-Hurt N, Boccia D. Cash transfers to enhance TB control: lessons from the HIV response. BMC Public Health. 2018;18: 1052. doi: 10.1186/s12889-018-5962-z - DOI - PMC - PubMed
    1. Pettifor A, MacPhail C, Nguyen N, Rosenberg M. Can money prevent the spread of HIV? A review of cash payments for HIV prevention. AIDS Behav. 2012;16: 1729–1738. doi: 10.1007/s10461-012-0240-z - DOI - PMC - PubMed

Publication types