Mathematical Modeling of SARS-CoV-2 Omicron Wave under Vaccination Effects

Abstract

Over the course of the COVID-19 pandemic millions of deaths and hospitalizations have been reported. Different SARS-CoV-2 variants of concern have been recognized during this pandemic and some of these variants of concern have caused uncertainty and changes in the dynamics. The Omicron variant has caused a large amount of infected cases in the US and worldwide. The average number of deaths during the Omicron wave toll increased in comparison with previous SARS-CoV-2 waves. We studied the Omicron wave by using a highly nonlinear mathematical model for the COVID-19 pandemic. The novel model includes individuals who are vaccinated and asymptomatic, which influences the dynamics of SARS-CoV-2. Moreover, the model considers the waning of the immunity and efficacy of the vaccine against the Omicron strain. This study uses the facts that the Omicron strain has a higher transmissibility than the previous circulating SARS-CoV-2 strain but is less deadly. Preliminary studies have found that Omicron has a lower case fatality rate compared to previous circulating SARS-CoV-2 strains. The simulation results show that even if the Omicron strain is less deadly it might cause more deaths, hospitalizations and infections. We provide a variety of scenarios that help to obtain insight about the Omicron wave and its consequences. The proposed mathematical model, in conjunction with the simulations, provides an explanation for a large Omicron wave under various conditions related to vaccines and transmissibility. These results provide an awareness that new SARS-CoV-2 variants can cause more deaths even if their fatality rate is lower.

Existence of Traveling Waves of a Diffusive Susceptible–Infected–Symptomatic–Recovered Epidemic Model with Temporal Delay

“…This numerical result supports the theoretical results, despite the fact that the model (1) was designed for the early phase of the COVID-19 pandemic. A more complex model is needed for the current pandemic to account for vaccinated individuals and the waning of immunity [8,[45][46][47].…”

“…The SIR (susceptible-infected-recovered) model is by far the most commonly used mathematical model based on differential equations [1]. Recently, the SAIR model, or its variants, has been used to address well-known asymptomatic cases [6][7][8][9]. In [10], a SIR model that incorporates awareness and a time delay to account for the latent stage was studied.…”

Computation to Fight SARS-CoV-2 (COVID-19)

“…These findings raise awareness that even though SARS-CoV-2 genotypes have a reduced mortality rate, they can nevertheless result in more deaths. Accordingly, the developed model can be useful for understanding the Omicron wave and the impact of novel highly transmissible strains [3]. In a different study authored by Afiahayati and colleagues, a computer-based technique was described for precisely estimating the number of cases of COVID-19 in the coming days, which could be extremely valuable in decision-making for providing proper advice to mitigate pandemic health emergencies.…”

Optimal Control Strategy of a Mathematical Model for the Fifth Wave of COVID-19 Outbreak (Omicron) in Thailand

“…The World Health Organization (WHO) identified all five Coronavirus variants, i.e., Alpha, Beta, Gamma, Delta, and more recently Omicron [19,20]. The Omicron COVID-19 variant was first found in South Africa towards the end of November 2021 [21][22][23] and Thailand detected its first case of Omicron at the beginning of January 2022. The Omicron variant has more than 50 mutations, compared to SARS-CoV-2 [22,23], and spreads significantly faster.…”

“…The Omicron COVID-19 variant was first found in South Africa towards the end of November 2021 [21][22][23] and Thailand detected its first case of Omicron at the beginning of January 2022. The Omicron variant has more than 50 mutations, compared to SARS-CoV-2 [22,23], and spreads significantly faster. Therefore, its spread has to be closely monitored.…”