Modelos de predicción del impacto y evolución del COVID-19 en República Dominicana

After its discovery in China, in December 2019, the SARS-CoV-2 virus causing the COVID-19 disease began to spread through countries around the world, causing a significant number of infected and dead. This situation has put high pressure on the health systems and governments of the different countries, which in many cases did not have the resources and infrastructure to face a pandemic caused by the virus, as was the case in the Dominican Republic. Using the public data of the advance of the pandemic in the Dominican Republic, from March 1 to April 30, the possible evolution of COVID-19 in this country was modeled and predicted, using three mathematical models SIR, SEIR-Extended, and log-linear. These models made it possible to project the different scenarios of infection and disease evolution, in addition to calculating the peak and decrease in the case curve. According to the results obtained, the country presented an exponential growth process of infections, with the peak of infections being projected to occur between the second half of May and the first half of June, with an estimated infected between 100,000 and 200,000 individuals. The results obtained in this study allow us to get an idea of what COVID-19 could have in human and social impact in the Dominican Republic.