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"Wait and see" vaccinating behaviour during a pandemic: a game theoretic analysis
Samit Bhattacharyya1, Chris T Bauch
1Department of Mathematics and Statistics, University of Guelph, 50 Stone Road, Guelph, N1G 2W1 ON, Canada. samit@math.utah.edu
Many people delay vaccination during pandemics, waiting for more information. This "wait and see" strategy relies on herd immunity from early vaccinators, impacting epidemic timing and vaccine uptake.
Area of Science:
- Epidemiology
- Game Theory
- Public Health
Background:
- During the 2009 H1N1 pandemic, a significant portion of the population adopted a "wait and see" approach to vaccination.
- This behavior suggests strategic interactions influencing vaccination decisions based on evolving information about costs and risks.
Purpose of the Study:
- To analyze the impact of "wait and see" vaccination strategies on disease transmission dynamics.
- To combine game theory with epidemiological modeling to understand individual decision-making during novel influenza outbreaks.
Main Methods:
- Developed a game theory model integrated with a disease transmission model for a novel influenza strain.
- Analyzed Nash equilibrium strategies, specifically the "wait and see" approach, considering herd immunity and information diffusion.
Main Results:
- Identified a "wait and see" Nash equilibrium where individuals delay vaccination, relying on early adopters for herd immunity and safety data.
- Observed that this strategic behavior conserves epidemic peak timing across various transmission rates, unlike models without adaptive behavior.
- Demonstrated a feed-forward mechanism where initial high perceived vaccination costs lead to sustained lower vaccine coverage.
Conclusions:
- Individual "wait and see" vaccination strategies significantly influence pandemic outcomes by creating reliance on herd immunity.
- Early risk communication is crucial, as initial perceptions of vaccination cost can have amplified and lasting effects on vaccine uptake.
- Pandemic response strategies must account for adaptive individual behaviors to effectively manage disease spread.
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