Abstract
OBJECTIVE: Assess the impact of interventions introduced in Costa Rica during 2020 and 2021 to control the COVID-19 pandemic. METHODS: A Bayesian Poisson regression model was used, incorporating control or intervention measures as independent variables in the changes in reported case numbers per epidemiological week. RESULTS: The results showed the relative and combined impact of containment policies and measures on the reduction of cases: mainly vehicular traffic restrictions, use of masks, and implementation of health guidelines and protocols. Evidence of impact was optimized and made available for decision-making by the country's health and emergency authorities. Several iterations were generated for constant monitoring of variations in impact at four different moments in the pandemic's spread. CONCLUSION: The simultaneous implementation of different mitigation measures in Costa Rica has been a driving force in reducing the number of COVID-19 cases.