Abstract—The novel coronavirus (covid-19) was initially identified at the end of 2019 and caused a global health care crisis. The increased transmissibility of the virus, that led to high mortality, raises the interest of scientists worldwide. Thus, various methods and models have been extensively discussed, so to study and control covid-19 transmission. Mathematical modeling constitutes an important tool to estimate key parameters of the transmission and predict the dynamic of the virus. More precisely, in the relevant literature, epidemiology is considered as a classical application area of branching processes, which are stochastic individual-based processes. In this paper, we develop a classical Galton-Watson branching process approach for the covid-19 spread in Greece at the early stage. This approach is structured in two parts, initial and latter transmission stages, so to provide a comprehensive view of the virus spread through basic and effective reproduction numbers respectively, along with the probability of an outbreak. Additionally, the effectiveness of control measures is discussed, based on a simple exponential smoothing model, which is used to build a non-mitigation scenario. Finally, our primary aim is to model all transmission stages through branching processes in order to analyze the first semiannual spread of the ongoing coronavirus pandemic in the region of Greece.
Index Terms—Branching processes, Covid-19, forecasting, mathematical modeling, pandemic.
Ioanna A. Mitrofani and Vasilis P. Koutras are with University of the Aegean, Greece (e-mail: mitrofani.joanna.92@gmail.com)
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Cite: Ioanna A. Mitrofani and Vasilis P. Koutras, "A Branching Process Model for the Novel Coronavirus (Covid-19) Spread in Greece," International Journal of Modeling and Optimization vol. 11, no. 3, pp. 63-69, 2021.
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
(CC BY 4.0).
