A Predictive Model for R0 (SARS-COV2)

Abstract

Due to the rapid spread of the COVID-19, scientists are constantly monitoring the evolution of the number of infections in a region. In particular, the basic reproductive number (R0) is studied, because it indicates if the number of cases will increase and the infection will last, or if it will decrease and stability will be reached. The present contribution is focused on forecasting this ratio, based on the extreme gradient boosting tree approach. Gradient reinforcement trees are used. Using public data of the COVID-19 outbreak in the Caribbean and some countries, this value is computed.