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In more than two years since the COVID-19 virus was first detected in China,hundreds of millions of individuals have been infected, and millions have died.Aside from the immediate need for medical solutions (such as vaccines andmedications) to treat the epidemic, the Corona pandemic has strengthened thedemand for mathematical models that can predict the spread of the pandemic inan ever-changing reality. Here, we present a novel, dynamic particle modelbased on the basic principles of statistical physics that enables theprediction of the spreading of Covid-19 in the presence of effective vaccines.This particle model enables us to accurately examine the effects of the vaccineon different subgroups of the vaccinated population and the entire populationand to identify the vaccine waning. Furthermore, a particle model can predictthe prevalence of two competing variants over time and their associatedmorbidity.

Using a physical model and aggregate data to estimate the spreading of Covid-19 in Israel in the presence of waning immunity and competing variants