Prediction of the effective reproduction number of COVID-19 in Greece. A machine learning approach using Google mobility data

This paper demonstrates how a short-term prediction of the effective reproduction number (R _t ) of COVID-19 in regions of Greece is achieved based on online mobility data. Various machine learning methods are applied to predict R _t and attribute importance analysis is performed to reveal the most important variables that affect the accurate prediction of R _t . Our results are based on an ensemble of diverse R _t methodologies to provide non-precautious and non-indulgent predictions. The model demonstrates robust results and the methodology overall represents a promising approach towards COVID-19 outbreak prediction. This paper can help health related authorities when deciding non-nosocomial interventions to prevent the spread of COVID-19.