COVID-19 Pandemic: a novel theoretical approach to epidemics

The coronavirus pan-demic 2019 (COVID-19) has completed numerous global spreading waves. Several models categorized as compart-mental, growth, and distributional have been derived and are intended to determine the spread dynamics of the pandemic and behavioral patterns. However, it seems that a more generalized theoretical approach to this phenomenon can be derived via distributional models, especially the Gaussian distribution. For this reason, we aim to approach the problem as a stochastic phenomenon, considering that the spread and the related outcomes of the epidemic occur randomly and exhibit stochastic behavior. In this way, we can predict the course of the pandemic by detecting the spreading wave patterns using stochastic instruments and methods. The purpose of our study is to present a phenomenological model that helps us understand the general outbreak behaviors that determine the characteristic parameters of the pandemic and behavioral patterns in spreading waves. To achieve the goal, we have developed a theoretical approach that obtains a stochastic differential equation or a master equation called the Fokker-Planck equation by starting with a stochastic difference equation or a random walk model. Thus, as a solution to this master equation, we get a time-dependent Gaussian distribution with a shifted center, which is a good instrument to determine the characteristic spreading parameters of COVID-19 and the general behavior patterns for all pandemic diseases. The model uncovers thoughts on preventative mechanisms and sheds light on most criticisms about the importance of individual isolation, recovery treatments, remedies, and vaccine development.