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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

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 and medications) to treat the epidemic, the Corona pandemic has strengthened the demand for mathematical models that can predict the spread of the pandemic in an ever-changing reality. Here, we present a novel, dynamic particle model based on the basic principles of statistical physics that enables the prediction of the spreading of Covid-19 in the presence of effective vaccines. This particle model enables us to accurately examine the effects of the vaccine on different subgroups of the vaccinated population and the entire population and to identify the vaccine waning. Furthermore, a particle model can predict the prevalence of two competing variants over time and their associated morbidity.

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