A Dynamic Model of Information-Vaccination-Disease That Accounts for Emerging Viral Variants: Model Development and a Case Study for COVID-19 in Iceland - Laijun Zhao; Mingmin Ying; Ying Qian; Lixin Zhou; Pingle Yang (Discrete Dynamics in Nature and Society)
Pathogens mutate as diseases spread, and variants that become epidemic or pandemic strains have higher transmission rates and a greater capacity to escape vaccine protection. Considering different vaccine efficacy and vaccination rates is of great significance for the prevention and control of infectious diseases. The spread of vaccination information and the level of trust in vaccinations determine whether people will choose to be vaccinated. To analyze these factors, we developed mean-field equations for system dynamics to model the complex system of vaccine information dissemination and vaccination, calculated the basic reproduction rate number, and used the Icelandic COVID-19 outbreak (Omicron variant) as a case study. We found that in the face of emerging variants, increasing vaccine efficacy is more effective than increasing vaccination rates. If vaccine efficacy increases from 40% to 90%, infections can be decreased by 98.5%. However, even a 100% vaccination rate cannot stop the spread of a mutated virus if vaccine efficacy falls below a certain level. High vaccination rates decrease the virus transmission rate. If the efficacy of the vaccine diminishes, the infection will spread rapidly, leading to a greater number of individuals becoming infected with the infectious disease. Due to the high vaccine efficacy against major illnesses and fatalities, improving vaccination rates can lower deaths. Iceland could decrease deaths by 44.8% by raising the vaccination rate from 75.9% to 95.0%. To combat emerging virus variants, it is therefore necessary to both create more effective vaccines and raise awareness of the benefits of vaccination to increase vaccination rates.