Parametrization Model Motivated from Physical Processes for Studying the Spread of COVID-19 Epidemic (2004.05992v2)

Abstract: The outbreak of the new virus COVID-19, beyond the human health risks and loss, has caused also very serious problems in a wide range of human activities, including the basic and applied scientific research, mainly that concern world wide collaborations. It is desirable to all of us to have the prospect of quickly predicting a turning point in the daily cases curve of the disease. In this work we face the problem of COVID-19 virus disease spreading by aiming mostly to create a reliable mathematical model describing this mechanism for an isolated society, for cities or even for a whole country. Drawing upon similar mechanisms appearing in the particle detector Physics, we concentrated to the so called, semi-gaussian function of n-degree. This approach can provide some very useful advantages in the data analysis of the daily reported cases of the infected people. Applying this model and fitting to the data, reported until the submission of this work, we have determined, among others, the mean infection time for a citizen in the society under study. We also applied and adopted this model to the reported cases in other countries and we have performed useful comparisons and conclusions.