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.

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.

Effect of a conditional cash transfer programme on AIDS incidence, hospitalisations, and mortality in Brazil: a longitudinal ecological study.

BACKGROUND: One of the biggest challenges of the response to the AIDS epidemic is to reach the poorest people. In 2004, Brazil implemented one of the world's largest conditional cash transfer programmes, the Bolsa Família Programme (BFP). We aimed to evaluate the effect of BFP coverage on AIDS incidence, hospitalisations, and mortality in Brazil. METHODS: In this longitudinal ecological study, we developed a conceptual framework linking key mechanisms of BFP effects on AIDS indicators and used ecological panel data from 5507 Brazilian municipalities over the period of 2004-18. We used government sources to calculate municipal-level AIDS incidence, hospitalisation, and mortality rates, and used multivariable regressions analyses of panel data with fixed-effects negative binomial models to estimate the effect of BFP coverage, which was classified as low (0-29%), intermediate (30-69%), and high (≥70%), on AIDS indicators, while adjusting for all relevant demographic, socioeconomic, and health-care covariates at the municipal level. FINDINGS: Between 2004 and 2018, in the municipalities under study, 601 977 new cases of AIDS were notified, of which 376 772 (62·6%) were in males older than 14 years, 212 465 (35·3%) were in females older than 14 years, and 12 740 (2·1%) were in children aged 14 years or younger. 533 624 HIV/AIDS-related hospitalisations, and 176 868 AIDS-related deaths had been notified. High BFP coverage was associated with reductions in incidence rate ratios of 5·1% (95% CI 0·9-9·1) for AIDS incidence, 14·3% (7·7-20·5) for HIV/AIDS hospitalisations, and 12·0% (5·2-18·4) for AIDS mortality. The effect of the BFP on AIDS indicators was more pronounced in municipalities with higher AIDS endemicity levels, with reductions in incidence rate ratios of 12·7% (95% CI 5·4-19·4) for AIDS incidence, 21·1% (10·7-30·2) for HIV/AIDS hospitalisations, and 14·7% (3·2-24·9) for AIDS-related mortality, and reductions in AIDS incidence of 14·6% (5·9-22·5) in females older than 14 years, 9·7% (1·4-17·3) in males older than 14 years, and 24·5% (0·5-42·7) in children aged 14 years or younger. INTERPRETATION: The effect of BFP coverage on AIDS indicators in Brazil could be explained by the reduction of households' poverty and by BFP health-related conditionalities. The protection of the most vulnerable populations through conditional cash transfers could contribute to the reduction of AIDS burden in low-income and middle-income countries. FUNDING: US National Institute of Allergy and Infectious Diseases, National Institutes of Health. TRANSLATION: For the Portugese translation of the abstract see Supplementary Materials section.