Screening, Brief Intervention, and Referral to Treatment (SBIRT) is a cost-effective, preventive strategy for addressing alcohol and substance use in African contexts. While short-term clinical outcomes are well-documented, there is limited understanding of long-term economic, health, and social system impacts. This study develops a stochastic life-course framework to quantify the health, productivity, and social returns of SBIRT across African health systems.

Using a discrete-time stochastic Markov model, individual trajectories of substance use, health status, and labor market participation are simulated under varying SBIRT coverage scenarios. Transition matrices incorporate intervention effects on the probability of moving between low-risk, hazardous, and dependent substance use states, as well as health and labor market outcomes. Monte Carlo simulations (10,000 iterations per scenario) are used to estimate distributions of long-term outcomes, including employment duration, disability incidence, life expectancy, and social protection dependency.

Preliminary results suggest that even moderate increases in SBIRT coverage reduce transitions to dependence, lower disability prevalence, extend productive workforce participation, and decrease reliance on social assistance. By linking early intervention to downstream system-level outcomes, the framework informs evidence-based policy for scaling SBIRT and integrating it into broader health and social protection strategies in Africa.