AUTHOR=Medina-Ortiz David , Contreras Sebastián , Barrera-Saavedra Yasna , Cabas-Mora Gabriel , Olivera-Nappa Álvaro 

TITLE=Country-Wise Forecast Model for the Effective Reproduction Number Rt of Coronavirus Disease

JOURNAL=Frontiers in Physics

VOLUME=8

YEAR=2020

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2020.00304

DOI=10.3389/fphy.2020.00304

ISSN=2296-424X

ABSTRACT=<p>Due to the particularities of SARS-CoV-2, public health policies have played a crucial role in the control of the COVID-19 pandemic. Epidemiological parameters for assessing the stage of the outbreak, such as the Effective Reproduction Number (<italic>R</italic><sub><italic>t</italic></sub>), are not always straightforward to calculate, raising barriers between the scientific community and non-scientific decision-making actors. The combination of estimators of <italic>R</italic><sub><italic>t</italic></sub> with elaborated Machine Learning-based forecasting techniques provides a way to support decision-making when assessing governmental plans of action. In this work, we develop forecast models applying logistic growth strategies and auto-regression techniques based on Auto-Regressive Integrated Moving Average (ARIMA) models for each country that records information about the COVID-19 outbreak. Using the forecast for the main variables of the outbreak, namely the number of infected (I), recovered (R), and dead (D) individuals, we provide a real-time estimation of <italic>R</italic><sub><italic>t</italic></sub> and its temporal evolution within a timeframe. With such models, we evaluate <italic>R</italic><sub><italic>t</italic></sub> trends at the continental and country levels, providing a clear picture of the effect governmental actions have had on the spread. We expect this methodology of combining forecast models for raw data to calculate <italic>R</italic><sub><italic>t</italic></sub> to serve as valuable input to support decision-making related to controlling the spread of SARS-CoV-2.</p>