Statistical Modeling for the Management of the Initial Stateof Emergency: First Three Months of COVID-19 in Costa Rica
DOI:
https://doi.org/10.32719/25506641.2021.10.3Keywords:
coronavirus, COVID-19, logistic, exponential, reproducibilityAbstract
The role of statistical modeling in emergency management is essential to shape or sup-port decisions regarding the care of events. In 2020 with coronavirus pandemic, countries quickly braced themselves for attention to contagious behavior and the impact it would have on public health. In Costa Rica, a team of specialists prepared studies on the behavior of the contagion curve and its effect on the occupation of hospital beds during the first three months of the epidemic. The studies were based on statistical model estimation of exponential and logistic growth, which provided forecasts of the daily and accumulated case numbers. The prediction of cases allowed feeding a simulation model for the projection of demand for hospital beds by patients with COVID-19. The analysis were based on data provided by the Ministry of Health regarding confirmed cases of coronavirus since the appearance of the first case in Costa Rica. Four models were estimated: logistic, Richards, Gompertz and Exponential, which generated daily case predictions. The reproducibility number was also estimated using Bayesian statistics to quantify the virus transmissibility. The results made it possible to anticipate the initial behavior of the virus in Costa Rica and the potential effect of the containment measures adopted after the declaration of national emergency.
JEL: C15 Statistical simulation methods: general.
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