AUTHOR=Silveira Antonio , Pereira Antonio 

TITLE=Estimation and Monitoring of COVID-19's Transmissibility From Publicly Available Data

JOURNAL=Frontiers in Applied Mathematics and Statistics

VOLUME=6

YEAR=2020

URL=https://www.frontiersin.org/journals/applied-mathematics-and-statistics/articles/10.3389/fams.2020.565336

DOI=10.3389/fams.2020.565336

ISSN=2297-4687

ABSTRACT=<p>The 2019 coronavirus disease (COVID-19) pandemic began in the city of Wuhan, China, at the end of 2019 and quickly spread worldwide. The disease is caused by contact with the SARS-CoV-2 virus, which probably jumped from an animal host to humans. SARS-CoV-2 infects various tissues in the body, notably the lungs, and patients usually die from respiratory complications. Mathematical models of the disease have been instrumental to guide the implementation of mitigation strategies aimed at slowing the spread of the disease. One of the key parameters of mathematical models is the basic reproduction ratio <italic>R</italic><sub>0</sub>, which measures the degree of infectivity of affected individuals. The goal of mitigation is to reduce <italic>R</italic><sub>0</sub> as close or below 1 as possible, as it means that new infections are in decline. In this work, we use the recursive least-squares algorithm to establish the stochastic variability of a time-varying <italic>R</italic><sub>0</sub>(<italic>t</italic>) from eight different countries: Argentina, Belgium, Brazil, Germany, Italy, New Zealand, Spain, and the United States. The proposed system can be implemented as an online tracking application providing information about the dynamics of the pandemic to health officials and the public at large.</p>