Forecast of Omicron Wave Time Evolution

Abstract

The temporal evolution of the omicron wave in different countries is predicted, upon adopting an early doubling time of three days for the rate of new infections with this mutant. The forecast is based on the susceptible–infectious–recovered/removed (SIR) epidemic compartment model with a constant stationary ratio k=μ(t)/a(t) between the infection (a(t)) and recovery (μ(t)) rates. The assumed fixed early doubling time then uniquely relates the initial infection rate a0 to the ratio k; this way the full temporal evolution of the omicron wave is determined here. Three scenarios (optimistic, pessimistic, intermediate) and the resulting pandemic parameters are considered for 12 different countries. Parameters include the total number of infected persons, the maximum rate of new infections, the peak time and the maximum 7-day incidence per 100,000 persons. The monitored data from Great Britain underwent a clear maximum SDI of 1865 on 7 January 2022. This maximum is a factor 5.0 smaller than our predicted value in the optimistic case and may indicate a dark number of omicron infections of 5.0 in Great Britain. For Germany we predict peak times of the omicron wave ranging from 32 to 38 and 45 days after the start of the omicron wave in the optimistic, intermediate and pessimistic scenario, respectively, with corresponding maximum SDI values of 7090, 13,263 and 28,911. Adopting 1 January 2022 as the starting date our predictions imply the maximum of the omicron wave to be reached between 1 February and 15 February 2022. Rather similar values are predicted for Switzerland. Due to an order of magnitude smaller omicron hospitalization rate, in concert with a high percentage of vaccinated and boosted population, the German health system can cope with a maximum omicron SDI value of 2800 which is about a factor 2.5 smaller than the corresponding value 7090 for the optimistic case. By either reducing the duration of intensive care during peak time, and/or by making use of the nonuniform spread of the omicron wave across Germany, it seems that the German health system can barely cope with the omicron wave and thus avoid triage decisions. The reduced omicron hospitalization rate also causes significantly smaller mortality rates compared to the earlier mutants in Germany. Within the optimistic scenario, we predict 7445 fatalities and a maximum number of 418 deaths/day due to omicron. These numbers range in order of magnitude below the ones known from the beta mutant.

Mathematics of Epidemics: On the General Solution of SIRVD, SIRV, SIRD and SIR Compartment Models

“…with constants q 0 , q 1 and G. The fatality rate (168) starts from the constant value q 0 and decreases with the typical time scale G −1 to its final constant value q 1 . Such a behavior accounts well for the COVID-19 omicron which had a much smaller (about an order of magnitude) fatality rate than the earlier mutants [22] occurring about a year earlier. Such a slow gradual decrease is well captured by the adopted fatality rate (168) in the case G b 0 < 1, allowing us the linear approximation…”

“…The main difference between the SIRVD and the SIRV model is the discrimination between recovered and deceased persons by introducing two different compartments. This is necessary as the omicron mutant the COVID-19 has a much smaller (about an order of magnitude) fatality rate than earlier mutants [22]. This gradually changing fatality rate is not accompanied by a corresponding change in the time dependence of the recovery rate.…”

The Omicron variant of concern: The genomics, diagnostics, and clinical characteristics in children

“…The projected mortality was between 60% of the Delta wave, while hospitalization was projected to be comparable to the situation in January 2021 to 4–5 times higher in the most pessimistic scenario ( 13 ). On the basis of these observations, the Omicron variant was projected to peak in approximately 32–45 days, ( 14 ) therefore, reaching a peak by the end February in Indonesia.…”

Quantitative evaluation of the role of Fangcang shelter hospitals in the control of Omicron transmission: A case study of the outbreak in Shanghai, China in 2022

“…Among them, Cai et al [ 24 ] reported that the cancellation of the dynamic zero-COVID policy would trigger a wave of infections in Omicron, causing about 1.55 million deaths. Schlickeiser et al [ 25 ] predicted deaths in the UK, Switzerland and Germany using the SIR epidemic compartment model. Muniyappan et al [ 26 ] dealt with the mathematical modeling of the second wave of COVID-19 and verified the current Omicron variant pandemic data in India.…”