Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Forecast for the second Covid-19 wave based on the improved SIR model with a constant ratio of recovery to infection rate

Version 1 : Received: 21 January 2021 / Approved: 22 January 2021 / Online: 22 January 2021 (14:00:51 CET)

How to cite: Kröger, M.; Schlickeiser, R. Forecast for the second Covid-19 wave based on the improved SIR model with a constant ratio of recovery to infection rate. Preprints 2021, 2021010449 (doi: 10.20944/preprints202101.0449.v1). Kröger, M.; Schlickeiser, R. Forecast for the second Covid-19 wave based on the improved SIR model with a constant ratio of recovery to infection rate. Preprints 2021, 2021010449 (doi: 10.20944/preprints202101.0449.v1).

Abstract

We start out by deriving simple analytic expressions for all measurable amounts of cases and fatalities during a pandemic evolution exhibiting multiple waves, described by the semi-time SIR model. The approximant shares all relevant features with the exact solution, including time and position of the peak of daily new infections, as well as the asymptotic behaviors at small and large times. We derive exact analytic expressions for the early doubling time, late half decay time, and a half-early peak law, characterizing the dynamical evolution. We show, in particular, how the asymmetry of the first epidemic wave and its exponential tails are affected by the initial conditions; a feature that has no analogue in the all-time SIR model. We apply the approach to available data from different continents. Our analysis reveals that the immunity is very strongly increasing during the 2nd wave, while it was still at a very moderate level of a few percent in several countries at the end of the first wave. The wave-specific SIR parameters describing the infection and recovery rates we find to behave in a similar fashion, while their ratio k was decreasing only by a about 5% for most countries. Still, an apparently moderate change of k can have significant consequences for the relevant numbers like the final amount of infected or deceased population. As we show, the probability for an additional wave is however low in several countries due to the fraction of immune inhabitants at the end of the 2nd wave, irrespective the currently ongoing vaccination efforts. We compare with alternate approaches.

Supplementary and Associated Material

https://www.complexfluids.ethz.ch/covid19-waveII: Real-time analysis of the 2nd wave for various countries

Keywords

coronavirus; statistical analysis; extrapolation; parameter estimation; pandemic spreading

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