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

Descrizione del progetto

Uno strumento scalabile per ridurre le disuguaglianze legate alla tubercolosi

La protezione sociale può ridurre la povertà e promuovere l’equità in materia di salute, ma permangono importanti lacune nella copertura, soprattutto nei paesi a basso e medio reddito. La tubercolosi (TB) è tuttora un grave problema di salute globale, con 10,8 milioni di casi e 1,25 milioni di decessi nel 2023. Sebbene la tutela sociale possa migliorare la prevenzione, la cura e il trattamento di questa malattia, le prove del suo impatto a lungo termine rimangono limitate, soprattutto in contesti di crisi e vulnerabilità. Grazie al sostegno del programma di azioni Marie Skłodowska-Curie, SIMPACT-TB combinerà diverse fonti di dati e simulerà l’impatto delle politiche di tutela sociale sulla tubercolosi in Brasile, un paese con un’incidenza elevata della malattia e disuguaglianze marcate. Il modello verrà quindi adattato a paesi selezionati per esaminare gli effetti sugli esiti della tubercolosi fino al 2030 e al 2040.

Obiettivo

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.