Statistical mechanics study of the introduction of a vaccine against COVID-19 disease
Hilla De-Leon, Francesco Pederiva

TL;DR
This study uses statistical physics to determine the vaccination rate needed to control COVID-19, highlighting that high vaccination rates combined with restrictions are essential due to re-infection risks.
Contribution
It introduces a novel application of statistical physics tools to model vaccination strategies and pandemic control considering re-infection and temporal restrictions.
Findings
A vaccination rate of at least 0.3% of the population daily is needed for control.
Restrictions should accompany vaccination until herd immunity is achieved.
Re-infection can lead to additional outbreaks if vaccination rates are insufficient.
Abstract
By the end of 2020, a year since the first cases of infection by the Covid-19 virus have been reported, there is a light at the end of the tunnel. Several pharmaceutical companies made significant progress in developing effective vaccines against the Covid-19 virus that has claimed the lives of more than a million people over the world. On the other hand, there is growing evidence of re-infection by the virus, which can cause further outbreaks. In this paper, we apply statistical physics tools to examine the vaccination rate required to control the pandemic for three different vaccine efficiency scenarios. Also, we study the effect of temporal restrictions/reliefs on the pandemic's outbreak, assuming that re-infection is possible. When examining the efficiency of the vaccination rate of the general population in preventing an additional outbreak of the disease, we find that a high…
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