Forecasting the temporal evolution of Omicron infections

In a recent study posted to the medRxiv* pre-print server, a team of researchers predicted the rate of new infections due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant in different countries with the help of an early doubling time (t2) of three days.

Study: Forecast of omicron wave time evolution. Image Credit: Dmitry Demidovich/ShutterstockStudy: Forecast of omicron wave time evolution. Image Credit: Dmitry Demidovich/Shutterstock

After several coronavirus disease 2019 (COVID-19) outbursts caused by SARS-CoV-2 Alpha (α), Beta (β), Gamma (γ), and Delta (δ) variants, the recently identified Omicron variant is threatening to wreak havoc across several countries across the world.

Therefore, it is of utmost importance to predict the temporal evolution of the Omicron variant under realistic scenarios, in particular, to estimate the maximum and the total number of Omicron infections to compare with the available medical capacities in different countries.

About the study

In the present study, the researchers estimated the rate of Omicron infections by modeling temporal evolution of the Omicron wave, using 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)) rate. Herein, the fixed early t2 uniquely relates the initial Omicron infection rate (a0) to the ratio k, which determines the full temporal evolution of the Omicron waves.

For the study analysis, the researchers adopted 1 January 2022 as the starting date to predict the peak of the Omicron wave in different countries. For each country, pandemic parameters were calculated for three scenarios of Omicron infection rate - optimistic, pessimistic, and intermediate. These parameters included the total number of infected persons, the maximum rate of new infections (jmax), the peak time, and the maximum 7-day incidence per 100,000 persons (SDI).

Findings

Among the European countries, Denmark had the shortest peak time of the Omicron wave, ranging from 16 to 22, and 27 days in the optimistic, pessimistic, intermediate scenarios, respectively. The corresponding SDI values for these scenarios were 2424, 4462, and 7148, respectively. Notably, as of 10 January 2022, the SDI for Denmark saturated at a maximum value of 2478, thus indicating that the predicted values of the study were accurate.

In the case of Germany, SIR analysis predicted peak times of the Omicron wave, ranging from 32 to 38 and 45 days during the optimistic, intermediate, and pessimistic scenarios, respectively. The maximum SDI values corresponding to three scenarios were 7090, 13263, and 28911, respectively. Again considering 1 January 2022, as the starting date, in Germany, the Omicron wave would have reached its peak between 1 February and 15 February 2022. Subsequently, in the optimistic case, the total cumulative number of Omicron infections would have been 0.180, which would have gone up to 0.812 in the pessimistic case.

The predicted values were almost similar for Switzerland, with the peak times of the Omicron wave ranging from 30 to 36 and 42 days after the start, and the corresponding maximum SDI values of 8148, 15060, and 29259, respectively. In the case of Switzerland, starting from 1 January 2022, the peak of the Omicron wave would have reached between 31 January and 13 February 2022. In the optimistic case, the total cumulative number of Omicron infections would have been 0.208, which would have gone up to 0.824 in the pessimistic case.

Conclusions

To summarize, the study predicted that among others, the German health system could cope with a maximum Omicron SDI value of 2800, which is 2.5 times less than the maximum Omicron SDI value of 7090 in the optimistic case, largely due to high percentage of vaccinated and boosted population in Germany.

In addition, the predicted hospitalization rate due to Omicron infections in Germany would be much less. However, to achieve this, Germany will have to either reduce the duration of intensive care during the period of maximum Omicron infections or use the non-uniform spread of the Omicron wave across the country.

The reduced Omicron hospitalization rate would also result in a significantly lesser mortality rate in Germany. In the optimistic scenario, the predicted total number of fatalities (D∞) was 7445, and the maximum death rate (dmax) was 418 per day, lesser than the fatality and death rates observed during the COVID-19 outburst due to the β variant. In the pessimistic scenario, however, these numbers will increase by a factor of 4.5.

*Important notice

medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

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