Agent-Based Model of the Impact of Higher Influenza Vaccine Efficacy on Seasonal Influenza Burden

Introduction: Current influenza vaccines have limited effectiveness. COVID-19 vaccines using mRNA technology have demonstrated very high efficacy, suggesting that mRNA vaccines could be more effective for influenza. Several such influenza vaccines are in development. FRED, an agent-based modeling platform, was used to estimate the impact of more effective influenza vaccines on seasonal influenza burden.Methods: Simulations were performed using an agent-based model of influenza that included varying levels of vaccination efficacy (40-95% effective). In some simulations, level of infectiousness and/or length of infectious period in agents with breakthrough infections was also decreased. Impact of increased and decreased levels of vaccine uptake were also modeled. Outcomes included number of symptomatic influenza cases estimated for the US.Results: Highly effective vaccines significantly reduced estimated influenza cases in the model. Decreases in estimated influenza cases in the US ranged from 43% to >99% when vaccine efficacy was increased from 40% to a maximum of 95%, with a decrease from ~28 million yearly cases in the US in the base simulation to ~22,000 cases with a 95% effective vaccine.Discussion: Highly effective vaccines could dramatically reduce influenza burden. Model estimates suggest that even modest increases in vaccine efficacy could dramatically reduce seasonal influenza disease burden.