An equity microsimulation approach to forecast the impact of social protection on diseases of poverty in low- and middle-income countries: the case of tuberculosis

Description du projet

Un outil évolutif pour réduire les inégalités liées à la tuberculose

La protection sociale peut réduire la pauvreté et promouvoir l’équité dans le domaine de la santé, mais d’importantes lacunes subsistent en matière de couverture, notamment dans les pays à revenu faible et intermédiaire. La tuberculose (TB) demeure un problème de santé publique majeur à l’échelle mondiale, avec 10,8 millions de cas et 1,25 million de décès en 2023. Bien que la protection sociale puisse améliorer la prévention, les soins et les résultats du traitement de la tuberculose, les preuves de son impact à long terme restent limitées, en particulier dans les contextes de crise et de vulnérabilité. Soutenu par le programme Actions Marie Skłodowska-Curie, SIMPACT-TB combinera plusieurs sources de données et simulera l’impact des politiques de protection sociale sur la tuberculose au Brésil, un pays où sa prévalence est élevée et où les inégalités sont marquées. Le modèle sera ensuite adapté à certains pays afin d’examiner ses effets sur l’évolution de la maladie jusqu’en 2030 et 2040.

Objectif

Social protection is a proven mechanism to reduce poverty, prevent income shocks, and promote social and health equity. Expanding its coverage is a global health priority, yet 53% of the population remain without protection and low- and middle-income countries (LMICs) face major funding shortfalls. In this context, tuberculosis (TB) is an emblematic disease of poverty and social exclusion: it remains the leading cause of death from an infectious disease, with 10.8 million cases and 1.25 million deaths in 2023, disproportionately affecting LMICs. While social protection is seen as a key solution to improve TB outcomes, evidence of its performance under overlapping crises (recessions, pandemics, or climate shocks) remains scarce. SIMPACT-TB addresses this gap by integrating epidemiological, social, and administrative datasets with dynamic microsimulation forecasting. Brazil will serve as the pilot case, given its high TB burden, sharp inequalities, and unique longitudinal databases. The model will simulate individual TB care trajectories, incorporating income, gender, geography, and access to social protection. In a second stage, the framework will be extended to selected LMICs using harmonized datasets. The project has four objectives: (1) to build an integrated, policy-relevant database; (2) to design and implement SIMPACT-TB to forecast the impact of social protection on TB outcomes through 2030 and up to 2040; (3) to apply the model across LMICs to identify the most effective and equitable interventions; and (4) to advance my career through high-level training. By deepening understanding of how social protection influences TB and health equity, SIMPACT-TB will fill a critical evidence gap and deliver a scalable tool for global use. While TB serves as an emblematic disease of poverty, the methodology is transferable to other socially determined diseases, generating scientific, societal, and economic impact, supporting more resilient and equitable health policies.