Quantifying the Impact of National Crises on Life Expectancy in Sri Lanka

This study investigates the impact of major national crises on life expectancy trends in Sri Lanka from 2000 to 2023 using a Bayesian generalized additive modeling (GAM) framework combined with interrupted time series analysis. The model incorporates key socio-economic and environmental covariates—including infant mortality and GDP per capita—along with event indicators to capture the immediate and post-event effects of significant crises: the 2004 Indian Ocean tsunami, the prolonged civil conflict culminating in 2009, and the COVID-19 pandemic. Model evaluation based on the Leave-One-Out Information Criterion (LOOIC) identified a spline dimension of 8 as optimal for capturing nonlinear temporal trends. Results indicate significant immediate negative impacts on life expectancy due to the 2004 tsunami and the 2009 war. The nonlinear temporal trend, captured by the spline term, showed a strong positive effect indicating overall improvements over time. Estimated effects for infant mortality and GDP per capita were inconclusive, with wide credible intervals overlapping zero, suggesting minimal or uncertain direct associations after accounting for crises and temporal trends. Posterior predictive checks confirmed the model’s strong predictive accuracy. Forecasting for 2024 was performed using a second-order Taylor series expansion on posterior fitted draws, providing a robust and computationally efficient approach to project life expectancy beyond observed data while accounting for nonlinear trends and uncertainty. The forecast indicates a continued upward trend, though with increasing uncertainty. These findings highlight the resilience of the Sri Lankan health system and underscore the importance of targeted interventions during crises to sustain population health improvements. The proposed modeling framework provides policymakers a valuable tool for ongoing health monitoring, crisis impact assessment, and strategic planning in Sri Lanka and similar settings.