Quickest Detection and Forecast of Pandemic Outbreaks: Analysis of COVID-19 Waves
Giovanni Soldi, Nicola Forti, Domenico Gaglione, Paolo Braca, Leonardo M. Millefiori, Stefano Maranò, Peter Willett, Krishna R. Pattipati
Abstract
The COVID-19 pandemic, worldwide up to December 2020, caused over 1.7 million deaths, and put the world's most advanced healthcare systems under heavy stress. In many countries, drastic restrictive measures adopted by political authorities, such as national lockdowns, have not prevented the outbreak of the new pandemic's waves. In this article, we propose an integrated detection-estimation-forecasting framework that, using publicly available data, is designed to: learn relevant features of the pandemic (e.g., the infection rate); detect as quickly as possible the onset (or the termination) of an exponential growth of the contagion; and reliably forecast the pandemic evolution. The proposed solution is validated by analyzing the COVID-19 second and third waves in the United States.