Geographical analysis of the morbidity of COVID-19 in Costa Rica, 2020-2021
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Keywords
COVID-19, morbility, spatial models, Costa Rica
Abstract
Objective: Identify the COVID-19 morbidity geographic clusters in Costa Rica during the first year of the pandemic. Methods: COVID-19 morbidity cases between March 06, 2020 and March 06, 2021 were analyzed. The morbidity rate is the ratio of cases (cumulative) and population and multiplying by one thousand inhabitants. The geographical distribution was mapped for the 82 cantons of Costa Rica. Assuming the Poisson distribution, a space scan was performed to detect COVID-19 clusters among the cantons of Costa Rica. Results: The space scan identified 10 clusters with high COVID-19 morbidity rates: San Jose and Alajuelita (RR = 1.84, p = 0.00), Central Limon (RR = 1.51, p = 0.00), Heredia and Alajuela (RR = 1.14, p = 0.00), Corredores (RR = 1.49, p = 0.00), Siquirres (RR = 1.34, p = 0.00), Garabito (RR = 1.45, p = 0.00), Alfaro Ruiz (RR = 1.35, p = 0.00), Cartago (RR = 1.04, p = 0.00), San Carlos (RR = 1.05, p = 0.00) and Montes de Oro (RR = 1.19, p = 0.00). Conclusion: During the first year of the COVID-19 pandemic in Costa Rica, the cases were not distributed homogeneously in the country since high morbidity clusters rates were detected. The geographic disparity of COVID-19 cases should alert public health organizations to implement measures in those geographic clusters and raise awareness in the population to avoid community transmission of COVID-19.
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