Evidence map›Paper›PMID 40730419›Full record

ArticleBMJ global health2025

Improving social determinants of health significantly reduces AIDS incidence: a modelling study of 1.17 million individuals in Brazil.

Rodrigo Volmir Rezende Anderle, Felipe Alves Rubio, Priscila Scaff, Ana Paula Santin Bertoni, José Alejandro Ordoñez, Iracema Lua, Gonzalo Barreix, Megan Naidoo, James Macinko, Luis Eugenio de Souza and 2 more

Abstract read
In one paragraph

Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Rodrigo Volmir Rezende AnderleInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil rodrigoanderle@yahoo.com.br.ORCID http://orcid.org/0000-0002-2618-5926
Felipe Alves RubioInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Priscila ScaffInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Ana Paula Santin BertoniInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
José Alejandro OrdoñezInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Iracema LuaInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Gonzalo BarreixBarcelona Institute for Global Health, Barcelona, Spain.
Megan NaidooBarcelona Institute for Global Health, Barcelona, Spain.
James MacinkoDepartment of Health Policy and Management, University of California, Los Angeles, California, USA.
Luis Eugenio de SouzaInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Maria Ines Costa DouradoInstitute of Collective Health, Federal University of Bahia (ISC/UFBA), Salvador, Brazil.
Davide RasellaBarcelona Institute for Global Health, Barcelona, Spain.ORCID http://orcid.org/0000-0002-7260-4386

Funding

The impact of social determinants, conditional cash transfers and primary health care on HIV/AIDS: an integrated retrospective and forecasting approach based on a cohort of 100 million BraziliansR01AI152938 · NIAID · FEDERAL UNIVERSITY OF BAHIA · PI RASELLA, DAVIDE · 2020 to 2024
$2.0M
NIAID NIH HHS R01 AI152938
6 · The paper itself

Abstract

Despite progress in addressing HIV/AIDS, the burden remains uneven, especially in low- and middle-income countries (LMICs). Social determinants of health (SDH) significantly influence HIV/AIDS. We studied the impact of SDH inequalities on AIDS incidence in Brazil, a large and diverse LMIC. We used an agent-based model (ABM) to introduce the SDH inequalities of income, education, sex and race in an HIV/AIDS model of 1 172 721 residents in 10 Brazilian state capitals. We simulated the poorest half of the population using the Cadastro Único database and calibrated our baseline models for each city with AIDS incidence from 2012 to 2019. We compared them with an alternative scenario where the effect of inequalities in SDH was removed. The difference between scenarios and subpopulations was measured in terms of cumulative rate ratios (RR) and avoidable cases over the study period. If there were no inequality in income, education, sex and race, there would be 38.8% lower AIDS incidence (95% CI 33% to 44.4%) compared with the baseline scenario. Furthermore, AIDS incidence was lower among individuals with low income (44.9%, 95% CI 34.7% to 61%), lower education (39.8%, 95% CI 34.6% to 46.5%) and people of Brown or Black race (39.3%, 95% CI 33.5% to 47.3%), in the alternative scenario compared with the baseline scenario. Furthermore, addressing inequality in the selected SDH had a positive spillover effect in reducing AIDS incidence in high income (31%, 95% CI 23.3% to 48.8%), highly educated (13.7%, 95% CI 8.4% to 27.8%) and white or Asian (35.4%, 95% CI 27.5% to 46.6%) populations, indicating a strong benefit to the whole of society. Our results suggest that addressing social inequalities in key SDH could reduce the number of AIDS cases among Brazil's poorest population by at least a third from 2012 to 2019. This effect is particularly significant in subpopulations with higher vulnerabilities. Implementing social protection policies to tackle these inequalities has the potential to help control the HIV/AIDS epidemic and advance the AIDS-related Social Development Goals.

Indexed as

Acquired Immunodeficiency SyndromeSocial Determinants of HealthAdolescentAdultBrazilFemaleHumansIncidenceMaleMiddle AgedSocioeconomic FactorsYoung AdultAIDSBrazilHIVMathematical modellingPublic Health

Identifiers

PMID40730419
PMCPMC12306475

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.