Researchers create model to explore SARS-CoV-2 Omicron and Delta supremacy

By Sam HancockFeb 28 2022Reviewed by Aimee Molineux

The coronavirus disease 2019 (COVID-19) pandemic has spread to nearly every country in the world, and caused over 5.9 million deaths as well as widespread economic crises.

Many countries were forced to enact costly and restrictive measures to help curb the transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) – the organism that causes COVID-19.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources

While the development and mass administration of vaccines allowed many of these measures to be dismantled, the emergence and rise to dominance of new variants of concern (VOC) continue to be of issue. Researchers from the University of Florida have created a model to help identify the dynamics of Delta and Omicron infection in the US, as well as explore the effects of various factors on the overall pandemic.

Their research can be found on the medRxiv* preprint server while the paper undergoes peer review.

The study

The scenario that was modeled aimed to examine the transmission dynamics of COVID-19 in the US in a situation where the Delta variant was dominant, and Omicron was then introduced. The population was stratified into mutually exclusive compartments for the unvaccinated, fully vaccinated but not boosted, fully vaccinated and boosted, those who have been exposed, pre-symptomatic individuals, known infected individuals, symptomatic patients at various points post-symptom onset, and hospitalized and recovered individuals.

The model took into account the rate of loss of immunity both in vaccinated and previously infected individuals, as well as the rate at which unvaccinated individuals become vaccinated, and vaccinated individuals become boosted. Several assumptions were made to allow the model to work – including the assumption that only Delta and Omicron variants were circling, every individual was equally likely to mix with every other individual, and vaccines only offered cross-protective efficacy against the variants.

The model can estimate the effective community transmission rates for infective individuals in each class, the rate at which individuals become fully vaccinated, and the rate at which fully vaccinated individuals become boosted. This is done by fitting the model to confirmed daily cases and then computing the best set of parameter values that minimize the sum of the square difference between the observed and estimated cases through a nonlinear regression procedure, with 95% confidence intervals determined using a bootstrapping technique. The initial fitting of the model to Omicron data between November 2021 and January 2022 showed a very good fit, and predictions made from this data for February 2022 to March 2022 matched the real data very closely.

The vaccination reproduction number of the model measures the average number of new SARS-CoV-2 cases generated by a single individual in a community with some fully vaccinated individuals. The model is locally stable if this number is below one, and unstable if above one. This means that a small influx of infected individuals will not trigger a larger outbreak, allowing the disease to be controlled more easily. When the reproduction numbers for the Omicron and Delta variants were computed and compared, the researchers concluded that the Delta variant had essentially been eliminated and replaced in the USA by the Omicron variant.

Luckily, the Omicron reproduction number is also slightly lower than one, suggesting that the disease may be finally being brought under control. Examination of the vaccine-derived herd immunity threshold was even more hopeful, suggesting that if only 4% of unvaccinated or single-dose vaccinated individuals become fully vaccinated the herd immunity threshold will be reached.

The model also investigates the effect of masks on the herd immunity threshold. It shows that where mask usage is maintained at a baseline level, the reproduction number decreases significantly. If mask-wearing increases by 10%, then the vaccine efficacy required to provide herd immunity could drop by between 4% and 8% (depending on the type of mask).

Simulating the model with different values of vaccination rates allows the impact of vaccination coverage to be monitored. The model is run as a special simulation with no treatment. This shows a significant daily and cumulative decrease in COVID-19 cases as vaccination coverage rises, as well as a decrease in the time-to-elimination of the pandemic. The model predicts that even at the lowest vaccination coverage scenario, COVID-19 can be eliminated by 2024, but if that is increased by 20%, it could occur as soon as June 2022.

The conclusion

The authors highlight that their model can successfully predict the effects of face-mask usage, vaccine coverage as well as many other factors on both overall transmission and the time it will take for the disease to be eliminated. It also predicts that the Delta variant has almost completely been eliminated in the United States as the Omicron variant has risen to dominance.

This model could be very useful for healthcare workers and epidemiologists and could be used to help predict the future direction of the pandemic.

This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources