Modeling COVID-19: Forecasting and analyzing the dynamics of the
outbreak in Hubei and Turkey
As the pandemic of Coronavirus Disease 2019 (COVID-19) rages throughout
the world, accurate modeling of the dynamics thereof is essential.
However, since the availability and quality of data varies dramatically
from region to region, accurate modeling directly from a global
perspective is difficult, if not altogether impossible. Nevertheless,
via local data collected by certain regions, it is possible to develop
accurate local prediction tools, which may be coupled to develop global
models. In this study, we analyze the dynamics of local outbreaks of
COVID-19 via a coupled system of ordinary differential equations (ODEs).
Utilizing the large amount of data available from the ebbing outbreak in
Hubei, China as a testbed, we estimate the basic reproductive number, R0
of COVID-19 and predict the total cases, total deaths, and other
features of the Hubei outbreak with a high level of accuracy. Through
numerical experiments, we observe the effects of quarantine, social
distancing, and COVID-19 testing on the dynamics of the outbreak. Using
knowledge gleaned from the Hubei outbreak, we apply our model to analyze
the dynamics of outbreak in Turkey. We provide forecasts for the peak of
the outbreak and the total number of cases/deaths in Turkey, for varying
levels of social distancing, quarantine, and COVID-19 testing.