Mathematical Modeling Evaluates How Vaccinations Affected the Course of COVID-19 Disease Progression

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• The SARS-CoV-2 pandemic's progression is influenced by policies, vaccine characteristics, and viral evolution.
• Mathematical models are crucial for predicting outcomes and informing policy decisions.

Purpose of the Study:

• To expand the SEIR epidemiological model for COVID-19 data, incorporating vaccination and disease severity.
• To investigate the impact of Greece's vaccination program, including rates, dosages, and boosters, on COVID-19 spread.
• To analyze policy scenarios related to vaccination rates, immunity loss, and relaxed measures for vaccinated individuals.

Main Methods:

• Developed an expanded SEIR model with compartments for vaccinated, asymptomatic, hospitalized, and deceased individuals.
• Modeled two population branches based on disease progression severity.
• Incorporated realistic vaccination data from Greece, including varying rates, dosages, and booster shots.

Main Results:

• Observed an alarming increase in the death rate during the Delta variant's dominance, preceding booster vaccinations in Greece.
• Identified vaccinated individuals as potential catalysts for COVID-19 spread due to infection and transmission probabilities.
• Highlighted the continuous interplay between intervention measures, vaccination strategies, and viral evolution throughout the pandemic.

Conclusions:

• Monitoring vaccine and virus evolution is critical for future pandemic response, especially with declining immunity, emerging variants, and incomplete transmission reduction by vaccines.
• The study underscores the complex dynamics influencing COVID-19 spread and the need for adaptive strategies.