Projecting the Pandemic Trajectory through Modeling the Transmission Dynamics of COVID-19

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• COVID-19 pandemic highlighted the need for understanding disease trends and epidemiological dynamics.
• Classic compartmental models require modifications to accurately reflect real-world disease progression and public health interventions.

Purpose of the Study:

• To present extensions of the SIRS model for analyzing viral pandemics.
• To support public health decision-making by incorporating factors like disease severity, vaccination strategies, and variant emergence.

Main Methods:

• Developed modified SIRS epidemiological models.
• Incorporated parameters for disease severity, varying vaccine effectiveness, and multiple doses.
• Modeled the impact of new viral variants on pandemic trajectories.
• Utilized numerical simulations to validate model predictions against observed COVID-19 phenomena.

Main Results:

• Mildly infectious individuals constitute the majority of infections.
• Prompt vaccination significantly reduces pandemic waves and mortality.
• A three-dose vaccine is effective against a single variant with high vaccine efficiency.
• Emergence of highly transmissible variants with reduced vaccine efficacy can lead to dominant strains, as seen with Omicron.

Conclusions:

• The extended SIRS models provide valuable insights into viral pandemic behavior.
• Vaccination strategies, including dose number and timing, are crucial for pandemic control.
• The models accurately reflect the impact of variants on disease spread and vaccine effectiveness.