Gestión e impacto de las medidas de intervención para la reducción de casos por COVID-19 en Costa Rica

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.