COMMON TRENDS IN THE EPIDEMIC OF COVID-19 DISEASE
The discovery of SARS-CoV-2, the responsible virus for the Covid-19 epidemic, has sparked a global health concern with many countries affected. Developing models that can interpret the epidemic and give common trend parameters are useful for prediction purposes by other countries that are at an earlier phase of the epidemic. We propose a model based on an initial exponential growth coupled with the slowing-down at long term for the total number of COVID-19 cases during the first period of the epidemic, from January to May 2020. The data from countries such as Iran, Turkey, Italy, Spain, France, and the United States are used to develop common trend parameters using this physical model. It is shown that during the fast phase, the number of new infected cases in several countries depends on the total number of cases by a power-law relation with a scaling exponent equal to 0.82. The duplication time together with the so-called confinement parameter that controls the phase change from the fast phase to the slow and plateau phases may be used for data interpretation and for guiding predictions regarding this disease.
M. Radiom* and J.-F. Berret*
Common trends in the epidemic of Covid-19 disease
The European Physical Journal Plus 135, 517 (2020)