Understanding how public health decisions shape epidemic outcomes is essential for futureoutbreak preparedness. In this study, we develop and apply an age-structured model of infectionand immunity to investigate how diff erent combinations of non-pharmaceutical measures andvaccination pathways infl uence COVID-19 dynamics across several regions. Using jurisdiction-specifi c calibration to observed epidemiological data, we construct hypothetical scenarios thatmodify intervention timing, policy intensity, primary vaccine rollout, and booster administrationThe analysis reveals that epidemic severity is strongly shaped by the interplay between existingimmunity levels and behavioral response to public health measures. In particular, non-schoolinterventions have the biggest impact in reducing infections. Additionally, booster delivery has apronounced eff ect on reducing hospitalizations and other severe outcomes, even when uptake isnot universal. By enabling harmonized comparison across regions, this modelling approachprovides a practical tool for evaluating alternative response strategies and informing futurepandemic policy.