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

Area of Science:

• Epidemiology
• Mathematical Biology
• Virology

Background:

• The COVID-19 pandemic has seen millions of deaths and hospitalizations globally.
• Emergence of SARS-CoV-2 variants of concern, like Omicron, has altered pandemic dynamics.
• Omicron caused widespread infections, with increased deaths during its wave compared to prior SARS-CoV-2 waves.

Purpose of the Study:

• To investigate the dynamics of the COVID-19 Omicron wave using a novel mathematical model.
• To analyze the impact of vaccination, asymptomatic spread, and waning immunity on Omicron's spread and severity.
• To understand how increased transmissibility and decreased fatality of Omicron contribute to overall mortality.

Main Methods:

• Development of a highly nonlinear mathematical model for COVID-19.
• Inclusion of vaccinated, asymptomatic individuals, and waning vaccine immunity within the model.
• Simulation of various scenarios to analyze Omicron wave consequences.

Main Results:

• Omicron's higher transmissibility, despite lower case fatality rate, led to increased deaths and hospitalizations.
• The mathematical model explains the large Omicron wave under varying conditions of vaccine efficacy and transmissibility.
• Simulations demonstrated that less deadly variants can still cause significant mortality and morbidity.

Conclusions:

• New SARS-CoV-2 variants can cause more overall deaths even with a lower individual fatality rate.
• Mathematical modeling provides crucial insights into variant-driven pandemic waves.
• Understanding variant characteristics is vital for predicting and mitigating future public health crises.