Analyzing the COVID-19 Vaccination Behavior Based on Epidemic Model with Awareness-information

Background: The widespread use of effective COVID-19 vaccines could prevent substantial morbidity and mortality. Individual decision behavior about whether or not to be vaccinated plays an important role in achieving adequate vaccination coverage and herd immunity.

Methods: This research proposes a new susceptible-vaccinated-exposed-infected-recovered with awareness-information (SEIR/V-AI) model to study the interaction between vaccination and information dissemination. Information creation rate and information sensitivity are introduced to understand the individual decision behavior of COVID-19 vaccination. We then analyze the dynamical evolution of the system and validate the analysis by numerical simulation.

Results: The decision behavior of COVID-19 vaccination in China and the United States are analyzed. The results showed the coefficient of information creation and the information sensitivity affect vaccination behavior of individuals.

Conclusions: The information-driven vaccination is an effective way to curb the COVID-19 spreading. Besides, to solve vaccine hesitancy and free-ride, the government needs to disseminate accurate information about vaccines safety to alleviate public concerns, and provide the widespread public educational campaigns and communication to guide individuals to act in group interests rather than self-interest and reduce the temptation to free-riding, which often results from individuals who are inadequately informed about vaccines and thus blindly imitate free-riding behavior.