Current and Projected Mortality and Hospitalization Rates Associated With Conditional Cash Transfer, Social Pension, and Primary Health Care Programs in Brazil, 2000-2030.

Importance: The health outcomes of increased poverty and inequalities in low- and middle-income countries (LMICs) have been substantially amplified as a consequence of converging multiple crises. Brazil has some of the world's largest conditional cash transfer (Programa Bolsa Família [PBF]), social pension (Beneficio de Prestacão Continuada [BPC]), and primary health care (Estratégia de Saúde da Família [ESF]) programs that could act as mitigating interventions during the current polycrisis era of increasing poverty, slow or contracting economic growth, and conflicts. Objective: To evaluate the combined association of the Brazilian conditional cash transfer, social pension, and primary health care programs with the reduction of morbidity and mortality over the last 2 decades and forecast their potential mitigation of the current global polycrisis and beyond. Design, Setting, and Participants: This cohort study used a longitudinal ecological design with multivariable negative binomial regression models (adjusted for relevant socioeconomic, demographic, and health care variables) integrating the retrospective analysis from 2000 to 2019, with dynamic microsimulation models to forecast potential child mortality scenarios up to 2030. Participants included a cohort of 2548 Brazilian municipalities from 2004 to 2019, projected from 2020 to 2030. Data analysis was performed from September 2022 to February 2023. Exposure: PBF coverage of the target population (those who were poorest) was categorized into 4 levels: low (0%-29.9%), intermediate (30.0%-69.9%), high (70.0%-99.9%), and consolidated (≥100%). ESF coverage was categorized as null (0), low (0.1%-29.9%), intermediate (30.0%-69.9%), and consolidated (70.0%-100%). BPC coverage was categorized by terciles. Main outcomes and measures: Age-standardized, all-cause mortality and hospitalization rates calculated for the entire population and by age group (<5 years, 5-29 years, 30-69 years, and ≥70 years). Results: Among the 2548 Brazilian municipalities studied from 2004 to 2019, the mean (SD) age-standardized mortality rate decreased by 16.64% (from 6.73 [1.14] to 5.61 [0.94] deaths per 1000 population). Consolidated coverages of social welfare programs studied were all associated with reductions in overall mortality rates (PBF: rate ratio [RR], 0.95 [95% CI, 0.94-0.96]; ESF: RR, 0.93 [95% CI, 0.93-0.94]; BPC: RR, 0.91 [95% CI, 0.91-0.92]), having all together prevented an estimated 1 462 626 (95% CI, 1 332 128-1 596 924) deaths over the period 2004 to 2019. The results were higher on mortality for the group younger than age 5 years (PBF: RR, 0.87 [95% CI, 0.85-0.90]; ESF: RR, 0.89 [95% CI, 0.87-0.93]; BPC: RR, 0.84 [95% CI, 0.82-0.86]), on mortality for the group aged 70 years and older, and on hospitalizations. Considering a shorter scenario of economic crisis, a mitigation strategy that will increase the coverage of PBF, BPC, and ESF to proportionally cover the newly poor and at-risk individuals was projected to avert 1 305 359 (95% CI, 1 163 659-1 449 256) deaths and 6 593 224 (95% CI, 5 534 591-7 651 327) hospitalizations up to 2030, compared with fiscal austerity scenarios that would reduce the coverage of these interventions. Conclusions and relevance: This cohort study's results suggest that combined expansion of conditional cash transfers, social pensions, and primary health care should be considered a viable strategy to mitigate the adverse health outcomes of the current global polycrisis in LMICs, whereas the implementation of fiscal austerity measures could result in large numbers of preventable deaths.

A Mathematical Model for the Impact of 3HP and Social Programme Implementation on the Incidence and Mortality of Tuberculosis: Study in Brazil.

In this paper, we presented a mathematical model for tuberculosis with treatment for latent tuberculosis cases and incorporated social implementations based on the impact they will have on tuberculosis incidence, cure, and recovery. We incorporated two variables containing the accumulated deaths and active cases into the model in order to study the incidence and mortality rate per year with the data reported by the model. Our objective is to study the impact of social program implementations and therapies on latent tuberculosis in particular the use of once-weekly isoniazid-rifapentine for 12 weeks (3HP). The computational experimentation was performed with data from Brazil and for model calibration, we used the Markov Chain Monte Carlo method (MCMC) with a Bayesian approach. We studied the effect of increasing the coverage of social programs, the Bolsa Familia Programme (BFP) and the Family Health Strategy (FHS) and the implementation of the 3HP as a substitution therapy for two rates of diagnosis and treatment of latent at 1% and 5%. Based of the data obtained by the model in the period 2023-2035, the FHS reported better results than BFP in the case of social implementations and 3HP with a higher rate of diagnosis and treatment of latent in the reduction of incidence and mortality rate and in cases and deaths avoided. With the objective of linking the social and biomedical implementations, we constructed two different scenarios with the rate of diagnosis and treatment. We verified with results reported by the model that with the social implementations studied and the 3HP with the highest rate of diagnosis and treatment of latent, the best results were obtained in comparison with the other independent and joint implementations. A reduction of the incidence by 36.54% with respect to the model with the current strategies and coverage was achieved, and a greater number of cases and deaths from tuberculosis was avoided.

Incorporating social vulnerability in infectious disease mathematical modelling: a scoping review.

BACKGROUND: Highlighted by the rise of COVID-19, climate change, and conflict, socially vulnerable populations are least resilient to disaster. In infectious disease management, mathematical models are a commonly used tool. Researchers should include social vulnerability in models to strengthen their utility in reflecting real-world dynamics. We conducted a scoping review to evaluate how researchers have incorporated social vulnerability into infectious disease mathematical models. METHODS: The methodology followed the Joanna Briggs Institute and updated Arksey and O'Malley frameworks, verified by the PRISMA-ScR checklist. PubMed, Clarivate Web of Science, Scopus, EBSCO Africa Wide Information, and Cochrane Library were systematically searched for peer-reviewed published articles. Screening and extracting data were done by two independent researchers. RESULTS: Of 4075 results, 89 articles were identified. Two-thirds of articles used a compartmental model (n = 58, 65.2%), with a quarter using agent-based models (n = 24, 27.0%). Overall, routine indicators, namely age and sex, were among the most frequently used measures (n = 42, 12.3%; n = 22, 6.4%, respectively). Only one measure related to culture and social behaviour (0.3%). For compartmental models, researchers commonly constructed distinct models for each level of a social vulnerability measure and included new parameters or influenced standard parameters in model equations (n = 30, 51.7%). For all agent-based models, characteristics were assigned to hosts (n = 24, 100.0%), with most models including age, contact behaviour, and/or sex (n = 18, 75.0%; n = 14, 53.3%; n = 10, 41.7%, respectively). CONCLUSIONS: Given the importance of equitable and effective infectious disease management, there is potential to further the field. Our findings demonstrate that social vulnerability is not considered holistically. There is a focus on incorporating routine demographic indicators but important cultural and social behaviours that impact health outcomes are excluded. It is crucial to develop models that foreground social vulnerability to not only design more equitable interventions, but also to develop more effective infectious disease control and elimination strategies. Furthermore, this study revealed the lack of transparency around data sources, inconsistent reporting, lack of collaboration with local experts, and limited studies focused on modelling cultural indicators. These challenges are priorities for future research.

Income determines the impact of cash transfers on HIV/AIDS: cohort study of 22.7 million Brazilians.

Living with extremely low-income is an important risk factor for HIV/AIDS and can be mitigated by conditional cash transfers. Using a cohort of 22.7 million low-income individuals during 9 years, we evaluated the effects of the world's largest conditional cash transfer, the Programa Bolsa Família, on HIV/AIDS-related outcomes. Exposure to Programa Bolsa Família was associated with reduced AIDS incidence by 41% (RR:0.59; 95%CI:0.57-0.61), mortality by 39% (RR:0.61; 95%CI:0.57-0.64), and case fatality rates by 25% (RR:0.75; 95%CI:0.66-0.85) in the cohort, and Programa Bolsa Família effects were considerably stronger among individuals of extremely low-income [reduction of 55% for incidence (RR:0.45, 95% CI:0.42-0.47), 54% mortality (RR:0.46, 95% CI:0.42-0.49), and 37% case-fatality (RR:0.63, 95% CI:0.51 -0.76)], decreasing gradually until having no effect in individuals with higher incomes. Similar effects were observed on HIV notification. Programa Bolsa Família impact was also stronger among women and adolescents. Several sensitivity and triangulation analyses demonstrated the robustness of the results. Conditional cash transfers can significantly reduce AIDS morbidity and mortality in extremely vulnerable populations and should be considered an essential intervention to achieve AIDS-related sustainable development goals by 2030.

Modelling HIV/AIDS epidemiological complexity: A scoping review of Agent-Based Models and their application.

OBJECTIVE: To end the AIDS epidemic by 2030, despite the increasing poverty and inequalities, policies should be designed to deal with population heterogeneity and environmental changes. Bottom-up designs, such as the Agent-Based Model (ABM), can model these features, dealing with such complexity. HIV/AIDS has a complex dynamic of structural factors, risk behaviors, biomedical characteristics and interventions. All embedded in unequal, stigmatized and heterogeneous social structure. To understand how ABMs can model this complexity, we performed a scoping review of HIV applications, highlighting their potentialities. METHODS: We searched on PubMed, Web of Science, and Scopus repositories following the PRISMA extension for scoping reviews. Our inclusion criteria were HIV/AIDS studies with an ABM application. We identified the main articles using a local co-citation analysis and categorized the overall literature aims, (sub)populations, regions, and if the papers declared the use of ODD protocol and limitations. RESULTS: We found 154 articles. We identified eleven main papers, and discussed them using the overall category results. Most studies model Transmission Dynamics (37/154), about Men who have sex with Men (MSM) (41/154), or individuals living in the US or South Africa (84/154). Recent studies applied ABM to model PrEP interventions (17/154) and Racial Disparities (12/154). Only six papers declared the use of ODD Protocol (6/154), and 34/154 didn't mention the study limitations. CONCLUSIONS: While ABM is among the most sophisticated techniques available to model HIV/AIDS complexity. Their applications are still restricted to some realities. However, researchers are challenged to think about social structure due model characteristics, the inclusion of these features is still restricted to case-specific. Data and computational power availability can enhance this feature providing insightful results.

Incidence and risk factors of tuberculosis among 420 854 household contacts of patients with tuberculosis in the 100 Million Brazilian Cohort (2004-18): a cohort study.

BACKGROUND: Although household contacts of patients with tuberculosis are known to be particularly vulnerable to tuberculosis, the published evidence focused on this group at high risk within the low-income and middle-income country context remains sparse. Using nationwide data from Brazil, we aimed to estimate the incidence and investigate the socioeconomic and clinical determinants of tuberculosis in a cohort of contacts of tuberculosis patients. METHODS: In this cohort study, we linked individual socioeconomic and demographic data from the 100 Million Brazilian Cohort to mortality data and tuberculosis registries, identified contacts of tuberculosis index patients diagnosed from Jan 1, 2004 to Dec 31, 2018, and followed up the contacts until the contact's subsequent tuberculosis diagnosis, the contact's death, or Dec 31, 2018. We investigated factors associated with active tuberculosis using multilevel Poisson regressions, allowing for municipality-level and household-level random effects. FINDINGS: We studied 420 854 household contacts of 137 131 tuberculosis index patients. During the 15 years of follow-up (median 4·4 years [IQR 1·9-7·6]), we detected 8953 contacts with tuberculosis. The tuberculosis incidence among contacts was 427·8 per 100 000 person-years at risk (95% CI 419·1-436·8), 16-times higher than the incidence in the general population (26·2 [26·1-26·3]) and the risk was prolonged. Tuberculosis incidence was associated with the index patient being preschool aged (<5 years; adjusted risk ratio 4·15 [95% CI 3·26-5·28]) or having pulmonary tuberculosis (2·84 [2·55-3·17]). INTERPRETATION: The high and sustained risk of tuberculosis among contacts reinforces the need to systematically expand and strengthen contact tracing and preventive treatment policies in Brazil in order to achieve national and international targets for tuberculosis elimination. FUNDING: Wellcome Trust and Brazilian Ministry of Health.

Racial inequalities in mental healthcare use and mortality: a cross-sectional analysis of 1.2 million low-income individuals in Rio de Janeiro, Brazil 2010-2016.

INTRODUCTION: Mental health inequalities across racial and ethnic groups are large and unjust in many countries, yet these inequalities remain under-researched, particularly in low-income and middle-income countries such as Brazil. This study investigates racial and socioeconomic inequalities in primary healthcare usage, hospitalisation and mortality for mental health disorders in Rio de Janeiro, Brazil. METHODS: A cohort of 1.2 million low-income adults from Rio de Janeiro, Brazil with linked socioeconomic, demographic, healthcare use and mortality records was cross-sectionally analysed. Poisson regression models were used to investigate associations between self-defined race/colour and primary healthcare (PHC) usage, hospitalisation and mortality due to mental disorders, adjusting for socioeconomic factors. Interactions between race/colour and socioeconomic characteristics (sex, education level, income) explored if black and pardo (mixed race) individuals faced compounded risk of adverse mental health outcomes. RESULTS: There were 272 532 PHC consultations, 10 970 hospitalisations and 259 deaths due to mental disorders between 2010 and 2016. After adjusting for a wide range of socioeconomic factors, the lowest PHC usage rates were observed in black (adjusted rate ratio (ARR): 0.64; 95% CI 0.60 to 0.68; compared with white) and pardo individuals (ARR: 0.87; 95% CI 0.83 to 0.92). Black individuals were more likely to die from mental disorders (ARR: 1.68; 95% CI 1.19 to 2.37; compared with white), as were those with lower educational attainment and household income. In interaction models, being black or pardo conferred additional disadvantage across mental health outcomes. The highest educated black (ARR: 0.56; 95% CI 0.47 to 0.66) and pardo (ARR: 0.75; 95% CI 0.66 to 0.87) individuals had lower rates of PHC usage for mental disorders compared with the least educated white individuals. Black individuals were 3.7 times (ARR: 3.67; 95% CI 1.29 to 10.42) more likely to die from mental disorders compared with white individuals with the same education level. CONCLUSION: In low-income individuals in Rio de Janeiro, racial/colour inequalities in mental health outcomes were large and not fully explainable by socioeconomic status. Black and pardo Brazilians were consistently negatively affected, with lower PHC usage and worse mental health outcomes.

The combined effect of social pensions and cash transfers on child mortality: evaluating the last two decades in Brazil and projecting their mitigating effect during the global economic crisis.

Background: The world is currently experiencing multiple economic crises due to the COVID-19 pandemic, war in Ukraine, and inflation surge, which disproportionately affect children, especially in low- and middle-income countries (LMICs). We evaluated if the expansion of Social Assistance, represented by Social Pensions (SP) and Conditional Cash Transfers (CCT), could reduce infant and child mortality, and mitigate excess deaths among children in Brazil, one of the LMICs most affected by these economic crises. Methods: We conducted a retrospective impact evaluation in a cohort of Brazilian municipalities from 2004 to 2019 using multivariable fixed-effects negative binomial models, adjusted for relevant demographic, social, and economic factors, to estimate the effects of the SP and CCT on infant and child mortality. To verify the robustness of the results, we conducted several sensitivity and triangulation analyses, including difference-in-difference with propensity-score matching. These results were incorporated into dynamic microsimulation models to generate projections to 2030 of various economic crises and Social Assistance scenarios. Findings: Consolidated coverage of SP was associated with significant reductions in infant and child mortality rates, with a rate ratio (RR) of 0.843 (95% CI: 0.826-0.861) and 0.840 (95% CI: 0.824-0.856), respectively. Similarly, CCT consolidated coverages showed RRs of 0.868 (95% CI: 0.842-0.849) and 0.874 (95% CI: 0.850-0.899) for infant and child mortality, respectively. The higher the degree of poverty in the municipalities, the stronger the impact of CCT on reducing child mortality. Given the current economic crisis, a mitigation strategy that will increase the coverage of SP and CCT could avert 148,736 (95% CI: 127,148-170,706) child deaths up to 2030, compared with fiscal austerity measures. Interpretation: SP and CCT programs could strongly reduce child mortality in LMICs, and their expansion should be considered as an effective strategy to mitigate the impact of the current multiple global economic crises. Funding: Bill & Melinda Gates Foundation, Grant_Number:INV-027961. Medical Research Council(MRC-UKRI),Grant_Number:MC_PC_MR/T023678/1.

Understanding the social determinants of child mortality in Latin America over the last two decades: a machine learning approach.

The reduction of child mortality rates remains a significant global public health challenge, particularly in regions with high levels of inequality such as Latin America. We used machine learning (ML) algorithms to explore the relationship between social determinants and child under-5 mortality rates (U5MR) in Brazil, Ecuador, and Mexico over two decades. We created a municipal-level cohort from 2000 to 2019 and trained a random forest model (RF) to estimate the relative importance of social determinants in predicting U5MR. We conducted a sensitivity analysis training two more ML models and presenting the mean square error, root mean square error, and median absolute deviation. Our findings indicate that poverty, illiteracy, and the Gini index were the most important variables for predicting U5MR according to the RF. Furthermore, non-linear relationships were found mainly for Gini index and U5MR. Our study suggests that long-term public policies to reduce U5MR in Latin America should focus on reducing poverty, illiteracy, and socioeconomic inequalities. This research provides important insights into the relationships between social determinants and child mortality rates in Latin America. The use of ML algorithms, combined with large longitudinal data, allowed us to evaluate the effects of social determinants on health more carefully than traditional models.

The effect of primary health care on AIDS incidence and mortality: a cohort study of 3.4 million Brazilians.

Background: Primary Health Care (PHC) is essential for the health and wellbeing of people living with HIV/AIDS. This study evaluated the effects of one of the largest community-based PHC programs in the world, the Brazilian Family Health Strategy (FHS), on AIDS incidence and mortality. Methods: A retrospective cohort study carried out in Brazil, from January 1 2007 to December 31 2015. We conducted a quasi-experimental effect evaluation using a cohort of 3,435,068 ≥13 years low-income individuals who were members of the 100 Million Brazilians Cohort, linked to AIDS diagnoses and deaths registries. We evaluated the effect of FHS on AIDS incidence and mortality and comparing outcomes between residents of municipalities with no FHS coverage with those in municipalities with full FHS coverage. We used multivariable Poisson regressions adjusted for all relevant municipal and individual-level demographic, socioeconomic, and contextual variables, and weighted with inverse probability of treatment weighting (IPTW). We also estimated FHS effect by sex and age, and performed a wide range of sensitivity and triangulation analyses. Findings: FHS coverage was associated with lower AIDS incidence (rate ratio [RR]:0.76, 95%CI:0.68-0.84) and mortality (RR:0.68,95%CI:0.56-0.82). FHS effect was similar between men and women, but was larger in people aged ≥35 years old both for incidence (RR 0.62, 95%CI:0.53-0.72) and mortality (RR 0.56, 95%CI:0.43-0.72). Conclusions: AIDS should be an avoidable outcome for most people living with HIV today, and our study shows that FHS coverage could significantly reduce AIDS incidence and mortality among low-income populations in Brazil. Universal access to comprehensive healthcare through community-based PHC programs should be promoted to achieve the Sustainable Development Goals of ending AIDS by 2030.

Model Choice for Quantitative Health Impact Assessment and Modelling: An Expert Consultation and Narrative Literature Review.

BACKGROUND: Health impact assessment (HIA) is a widely used process that aims to identify the health impacts, positive or negative, of a policy or intervention that is not necessarily placed in the health sector. Most HIAs are done prospectively and aim to forecast expected health impacts under assumed policy implementation. HIAs may quantitatively and/ or qualitatively assess health impacts, with this study focusing on the former. A variety of quantitative modelling methods exist that are used for forecasting health impacts, however, they differ in application area, data requirements, assumptions, risk modelling, complexities, limitations, strengths, and comprehensibility. We reviewed relevant models, so as to provide public health researchers with considerations for HIA model choice. METHODS: Based on an HIA expert consultation, combined with a narrative literature review, we identified the most relevant models that can be used for health impact forecasting. We narratively and comparatively reviewed the models, according to their fields of application, their configuration and purposes, counterfactual scenarios, underlying assumptions, health risk modelling, limitations and strengths. RESULTS: Seven relevant models for health impacts forecasting were identified, consisting of (i) comparative risk assessment (CRA), (ii) time series analysis (TSA), (iii) compartmental models (CMs), (iv) structural models (SMs), (v) agent-based models (ABMs), (vi) microsimulations (MS), and (vii) artificial intelligence (AI)/machine learning (ML). These models represent a variety in approaches and vary in the fields of HIA application, complexity and comprehensibility. We provide a set of criteria for HIA model choice. Researchers must consider that model input assumptions match the available data and parameter structures, the available resources, and that model outputs match the research question, meet expectations and are comprehensible to end-users. CONCLUSION: The reviewed models have specific characteristics, related to available data and parameter structures, computational implementation, interpretation and comprehensibility, which the researcher should critically consider before HIA model choice.

Evaluation and Forecasting Analysis of the Association of Conditional Cash Transfer With Child Mortality in Latin America, 2000-2030.

Importance: Latin America has implemented the world's largest and most consolidated conditional cash transfer (CCT) programs during the last 2 decades. As a consequence of the COVID-19 pandemic, poverty rates have markedly increased, and a large number of newly low-income individuals, especially children, have been left unprotected. Objective: To evaluate the association of CCT programs with child health in Latin American countries during the last 2 decades and forecast child mortality trends up to 2030 according to CCT alternative implementation options. Design, Setting, and Participants: This cohort study used a multicountry, longitudinal, ecological design with multivariable negative binomial regression models, which were adjusted for all relevant demographic, socioeconomic, and health care variables, integrating the retrospective impact evaluations from January 1, 2000, to December 31, 2019, with dynamic microsimulation models to forecast potential child mortality scenarios up to 2030. The study cohort included 4882 municipalities from Brazil, Ecuador, and Mexico with adequate quality of civil registration and vital statistics according to a validated multidimensional criterion. Data analysis was performed from September 2022 to February 2023. Exposure: Conditional cash transfer coverage of the target (lowest-income) population categorized into 4 levels: low (0%-29.9%), intermediate (30.0%-69.9%), high (70.0%-99.9%), and consolidated (≥100%). Main Outcomes and Measures: The main outcomes were mortality rates for those younger than 5 years and hospitalization rates (per 1000 live births), overall and by poverty-related causes (diarrheal, malnutrition, tuberculosis, malaria, lower respiratory tract infections, and HIV/AIDS), and the mortality rates for those younger than 5 years by age groups, namely, neonatal (0-28 days), postneonatal (28 days to 1 year), infant (<1 year), and toddler (1-4 years). Results: The retrospective analysis included 4882 municipalities. During the study period of January 1, 2000, to December 31, 2019, mortality in Brazil, Ecuador, and Mexico decreased by 7.8% in children and 6.5% in infants, and an increase in coverage of CCT programs of 76.8% was observed in these Latin American countries. Conditional cash transfer programs were associated with significant reductions of mortality rates in those younger than 5 years (rate ratio [RR], 0.76; 95% CI, 0.75-0.76), having prevented 738 919 (95% CI, 695 641-782 104) child deaths during this period. The association of highest coverage of CCT programs was stronger with poverty-related diseases, such as malnutrition (RR, 0.33; 95% CI, 0.31-0.35), diarrhea (RR, 0.41; 95% CI, 0.40-0.43), lower respiratory tract infections (RR, 0.66, 95% CI, 0.65-0.68), malaria (RR, 0.76; 95% CI, 0.63-0.93), tuberculosis (RR, 0.62; 95% CI, 0.48-0.79), and HIV/AIDS (RR, 0.32; 95% CI, 0.28-0.37). Several sensitivity and triangulation analyses confirmed the robustness of the results. Considering a scenario of moderate economic crisis, a mitigation strategy that will increase the coverage of CCTs to protect those newly in poverty could reduce the mortality rate for those younger than 5 years by up to 17% (RR, 0.83; 95% CI, 0.80-0.85) and prevent 153 601 (95% CI, 127 441-180 600) child deaths by 2030 in Brazil, Ecuador, and Mexico. Conclusions and Relevance: The results of this cohort study suggest that the expansion of CCT programs could strongly reduce childhood hospitalization and mortality in Latin America and should be considered an effective strategy to mitigate the health impact of the current global economic crisis in low- and middle-income countries.

The effects of social determinants of health on acquired immune deficiency syndrome in a low-income population of Brazil: a retrospective cohort study of 28.3 million individuals.

Background: Social determinants of health (SDH) include factors such as income, education, and race, that could significantly affect the human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDS). Studies on the effects of SDH on HIV/AIDS are limited, and do not yet provide a systematic understanding of how the various SDH act on important indicators of HIV/AIDS progression. We aimed to evaluate the effects of SDH on AIDS morbidity and mortality. Methods: A retrospective cohort of 28.3 million individuals was evaluated over a 9-year period (from 2007 to 2015). Multivariable Poisson regression, with a hierarchical approach, was used to estimate the effects of SDH-at the individual and familial level-on AIDS incidence, mortality, and case-fatality rates. Findings: A total of 28,318,532 individuals, representing the low-income Brazilian population, were assessed, who had a mean age of 36.18 (SD: 16.96) years, 52.69% (14,920,049) were female, 57.52% (15,360,569) were pardos, 34.13% (9,113,222) were white/Asian, 7.77% (2,075,977) were black, and 0.58% (154,146) were indigenous. Specific socioeconomic, household, and geographic factors were significantly associated with AIDS-related outcomes. Less wealth was strongly associated with a higher AIDS incidence (rate ratios-RR: 1.55; 95% confidence interval-CI: 1.43-1.68) and mortality (RR: 1.99; 95% CI: 1.70-2.34). Lower educational attainment was also greatly associated with higher AIDS incidence (RR: 1.46; 95% CI: 1.26-1.68), mortality (RR: 2.76; 95% CI: 1.99-3.82) and case-fatality rates (RR: 2.30; 95% CI: 1.31-4.01). Being black was associated with a higher AIDS incidence (RR: 1.53; 95% CI: 1.45-1.61), mortality (RR: 1.69; 95% CI: 1.57-1.83) and case-fatality rates (RR: 1.16; 95% CI: 1.03-1.32). Overall, also considering the other SDH, individuals experiencing greater levels of socioeconomic deprivation were, by far, more likely to acquire AIDS, and to die from it. Interpretation: In the population studied, SDH related to poverty and social vulnerability are strongly associated with a higher burden of HIV/AIDS, most notably less wealth, illiteracy, and being black. In the absence of relevant social protection policies, the current worldwide increase in poverty and inequalities-due to the consequences of the COVID-19 pandemic, and the effects of war in the Ukraine-could reverse progress made in the fight against HIV/AIDS in low- and middle-income countries (LMIC). Funding: National Institute of Allergy and Infectious Diseases (NAIDS), National Institutes of Health (NIH), US Grant Number: 1R01AI152938.

Associations between primary healthcare and infant health outcomes: a cohort analysis of low-income mothers in Rio de Janeiro, Brazil.

Background: Expanding primary healthcare to urban poor populations is a priority in many low-and middle-income countries and is essential to achieve universal health coverage (UHC). Between 2008 and 2016 the city of Rio de Janeiro undertook an ambitious programme to rapidly expand primary care to low-income areas through the family health strategy (FHS). Infant health impacts of this roll out are unknown. This study examines associations between maternal FHS utilisation and birth outcomes, neonatal and infant mortality. Methods: A cohort of 75,339 live births (January 2009-December 2014) to low-income mothers in Rio de Janeiro was linked to primary care, birth, hospital and death records. The relationship between maternal FHS use and infant health outcomes was assessed through logistic regression with inverse probability treatment weighting and regression adjustment. Socioeconomic inequalities in the associations between FHS use and outcomes were explored through interactions. Primary outcomes were neonatal and infant death. Thirteen secondary outcomes were also examined to explore other important health outcomes and potential mechanisms. Results: A total of 9002 (12.0%) infants were born to mothers in the cohort who used FHS services either before pregnancy or in the first two trimesters. There was a total of 527 neonatal and 893 infant deaths. Maternal FHS usage during the first two trimesters was associated with substantial reductions in neonatal [adjusted odds ratio (aOR): 0.527, 95% confidence interval (95% CI): 0.345; 0.806] and infant mortality (aOR: 0.672, 95% CI: 0.48; 0.924). Infants born to lower-income mothers and those without formal employment had larger reductions in neonatal and infant mortality associated with FHS use. Maternal FHS in the first two trimesters use was also associated with more antenatal care consultations and a lower risk of low birth weight and preterm birth. Interpretation: Expanding primary care to low-income populations in Rio de Janeiro was associated with improved infant health and health equity benefits. Funding: DFID/MRC/Wellcome Trust/ESRC.

The effects of cash transfer programmes on HIV/AIDS prevention and care outcomes: a systematic review and meta-analysis of intervention studies.

BACKGROUND: Poverty and social inequality are risk factors for poor health outcomes in patients with HIV/AIDS. In addition to eligibility, cash transfer programmes can be divided into two categories: those with specific requirements (conditional cash transfers [CCTs]) and those without specific requirements (unconditional cash transfers). Common CCT requirements include health care (eg, undergoing an HIV test) and education (eg, children attending school). Trials assessing the effect of cash transfer programmes on HIV/AIDS outcomes have yielded divergent findings. This review aimed to summarise evidence to evaluate the effects of cash transfer programmes on HIV/AIDS prevention and care outcomes. METHODS: For this systematic review and meta-analysis, we searched PubMed, EMBASE, Cochrane Library, LILACS, WHO IRIS, PAHO-IRIS, BDENF, Secretaria Estadual de Saúde SP, Localizador de Informação em Saúde, Coleciona SUS, BINACIS, IBECS, CUMED, SciELO, and Web of Science up to Nov 28, 2022. We included randomised controlled trials (RCTs) that evaluated the effects of cash transfer programmes on HIV incidence, HIV testing, retention in HIV care, and antiretroviral therapy adherence, and conducted risk of bias and quality of evidence assessments using the Cochrane Risk of Bias tool and the Grading of Recommendations, Assessment, Development, and Evaluations approach. A random-effects meta-analysis model was used to combine studies and calculate risk ratios (RRs). Subgroup analyses were performed using conditionality types (ie, school attendance or health care). The protocol was registered with PROSPERO, CRD42021274452. FINDINGS: 16 RCTs, which included 5241 individuals, fulfilled the inclusion criteria. Of these, 13 studies included conditionalities for receiving cash transfer programmes. The results showed that receiving a cash transfer was associated with lowered HIV incidence among individuals who had to meet health-care conditionalities (RR 0·74, 95% CI 0·56-0·98) and with increased retention in HIV care for pregnant women (1·14, 95% CI 1·03-1·27). No significant effect was observed for HIV testing (RR 0·45, 95% CI 0·18-1·12) or antiretroviral therapy adherence (1·13, 0·73-1·75). Lower risk of bias was observed for HIV incidence and having an HIV test. The strength of available evidence can be classified as moderate. INTERPRETATION: Cash transfer programmes have a positive effect on mitigating HIV incidence for individuals who have to meet health-care conditionalities and on increasing retention in HIV care for pregnant women. These results show the potential of cash transfer programmes for HIV prevention and care, especially among people in extreme poverty, and highlight that cash transfer programmes must be considered when developing policies for HIV/AIDS control, as indicated by the UNAIDS 95-95-95 target of the HIV care continuum. FUNDING: National Institute of Allergy and Infectious Diseases, National Institutes of Health, USA.

Association of Conditional Cash Transfers With Maternal Mortality Using the 100 Million Brazilian Cohort.

Importance: Conditional cash transfers (CCTs) have been consistently associated with improvements to the determinants of maternal health, but there have been insufficient investigations regarding their effects on maternal mortality. Objective: To evaluate the association between being a Bolsa Família program (BFP) beneficiary and maternal mortality and to examine how this association differs by duration of BFP receipt, maternal race, living in rural or urban areas, the Municipal Human Development Index (MHDI), and municipal primary health care coverage. Design, Setting, and Participants: This cross-sectional analysis was nested within the 100 Million Brazilian Cohort. Girls and women aged 10 to 49 years (hereinafter referred to as women) who had at least 1 live birth were included, using data from Brazilian national health databases linked to the 100 Million Brazilian Cohort (January 1, 2004, to December 31, 2015). Propensity score kernel weighting was applied to control for sociodemographic and economic confounders in the association between BFP receipt and maternal mortality, overall and stratified by different subgroups (race, urban or rural area, and MHDI), and duration of BFP receipt. Data were analyzed from July 12, 2019, to December 31, 2022. Main Outcome(s) and Measures: Maternal death. Results: A total of 6 677 273 women aged 10 to 49 years were included in the analysis, 4056 of whom had died from pregnancy-related causes. The risk of maternal death was 18% lower in women who received BFP (weighted odds ratio [OR], 0.82 [95% CI, 0.71-0.93]). A longer duration receiving BFP was associated with an increased reduction in maternal mortality (OR for 1-4 years, 0.85 [95% CI, 0.75-0.97]; OR for 5-8 years, 0.70 [95% CI, 0.60-0.82]; OR for ≥9 years, 0.69 [95% CI, 0.53-0.88]). Receiving BFP was also associated with substantial increases in the number of prenatal appointments and interbirth intervals. The reduction was more pronounced in the most vulnerable groups. Conclusions and Relevance: This cross-sectional analysis nested within the 100 Million Brazilian Cohort found an association between BFP receipt and maternal mortality. This association was of greater magnitude in women with longer exposure to BFP and in the most vulnerable groups. These findings reinforce evidence that programs such as BFP, which have already proven effective in poverty reduction, have great potential to improve maternal survival.

Incorporating social determinants of health into the mathematical modeling of HIV/AIDS.

Currently, it is estimated that 37.6 million people are living with the HIV/AIDS virus worldwide, placing HIV/AIDS among the ten leading causes of death, mostly among low- and lower-middle-income countries. Despite the effective intervention in the prevention and treatment, this reduction did not occur equally among populations, subpopulations and geographic regions. This difference in the occurrence of the disease is associated with the social determinants of health (SDH), which could affect the transmission and maintenance of HIV. With the recognition of the importance of SDH in HIV transmission, the development of mathematical models that incorporate these determinants could increase the accuracy and robustness of the modeling. This article aims to propose a theoretical and conceptual way of including SDH in the mathematical modeling of HIV/AIDS. The theoretical mathematical model with the Social Determinants of Health has been developed in stages. For the selection of SDH that were incorporated into the model, a narrative literature review was conducted. Secondly, we proposed an extended model in which the population (N) is divided into Susceptible (S), HIV-positive (I), Individual with AIDS (A) and individual under treatment (T). Each SDH had a different approach to embedding in the model. We performed a calibration and validation of the model. A total of 31 SDH were obtained in the review, divided into four groups: Individual Factors, Socioeconomic Factors, Social Participation, and Health Services. In the end, four determinants were selected for incorporation into the model: Education, Poverty, Use of Drugs and Alcohol abuse, and Condoms Use. the section "Numerical simulation" to simulate the influence of the poverty rate on the AIDS incidence and mortality rates. We used a Brazilian dataset of new AIDS cases and deaths, which is publicly available. We calibrated the model using a multiobjective genetic algorithm for the years 2003 to 2019. To forecast from 2020 to 2035, we assumed two lines of poverty rate representing (i) a scenario of increasing and (ii) a scenario of decreasing. To avoid overfitting, we fixed some parameters and estimated the remaining. The equations presented with the chosen SDH exemplify some approaches that we can adopt when thinking about modeling social effects on the occurrence of HIV. The model was able to capture the influence of the employment/poverty on the HIV/AIDS incidence and mortality rates, evidencing the importance of SDOH in the occurrence of diseases. The recognition of the importance of including the SDH in the modeling and studies on HIV/AIDS is evident, due to its complexity and multicausality. Models that do not take into account in their structure, will probably miss a great part of the real trends, especially in periods, as the current on, of economic crisis and strong socioeconomic changes.

The impact of social drivers, conditional cash transfers and their mechanisms on the mental health of the young; an integrated retrospective and forecasting approach using the 100 million Brazilian Cohort: A study protocol.

BACKGROUND: Physical, emotional, and social changes, including exposure to poverty, abuse, or violence, increases youth vulnerability to mental illness. These factors interfere with development, limit opportunities, and hamper achievement of a fulfilling life as adults. Addressing these issues can lead to improved outcomes at the population level and better cost-effectiveness for health services. Cash transfer programs have been a promising way to address social drivers for poor mental health. However, it is still unclear which pathways and mechanisms explain the association between socioeconomic support and lower mental illness among youth. Therefore, we will evaluate the effect of social drivers on youth mental health-related hospitalizations and suicide, test mechanisms and pathways of a countrywide socioeconomic intervention, and examine the timing of the intervention during the life course. METHODS: We will combine individual-level data from youth national hospitalization, mental health disorders and attempted suicide, suicide registries and notifications of violence, with large-scale databases, including "The 100 Million Brazilian Cohort", over an 18-year period (2001-2018). Several approaches will be used for the retrospective quasi-experimental impact evaluations, such as Regression Discontinuity Designs, Propensity Score Matching and difference-in-differences, combined with multivariable regressions for cohort analyses. We will run multivariate regressions based on hierarchical analysis approach to evaluate the association between important social drivers (mental health care, demographic and economic aspects) on mental health-related hospitalizations and suicide among youth. Furthermore, we will perform microsimulations to generate projections regarding how mental health-related hospitalizations and suicide trends will be in the future based on the current state, and how BFP implementation scenarios will affect these trends. DISCUSSION: The results of this project will be of vital importance to guide policies and programs to improve mental health and reduce mental health-related hospitalizations and suicide in youth. It will provide information to improve the effectiveness of these programs worldwide. If cash transfers can decrease mental health problems among youth and reduce suicide.