Determination of a Key Pandemic Parameter of the SIR-Epidemic Model from Past COVID-19 Mutant Waves and Its Variation for the Validity of the Gaussian Evolution

Abstract

Monitored differential infection rates of past corona waves are used to infer, a posteriori, the real time variation of the ratio of recovery to infection rate as a key parameter of the SIR (susceptible-infected-recovered/removed) epidemic model. From monitored corona waves in five different countries, it is found that this ratio exhibits a linear increase at early times below the first maximum of the differential infection rate, before the ratios approach a nearly constant value close to unity at the time of the first maximum with small amplitude oscillations at later times. The observed time dependencies at early times and at times near the first maximum agree favorably well with the behavior of the calculated ratio for the Gaussian temporal evolution of the rate of new infections, although the predicted linear increase of the Gaussian ratio at late times is not observed.