Modeling vaccination decision making process in a finite population
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1Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, United States.
Abstract:
Vaccination is considered as one of the most crucial methods in controlling the spread of infectious diseases. However, it is difficult to predict the expected vaccine coverage level because it depends on human behaviors. We consider deterministic and stochastic models to simulate how individuals choose strategies in the scenario of vaccination. In an infinite population, a system of replicator equations is formulated and the expected level is calculated. Decision making processes in both an unstructured finite population and a structured finite population are discussed. Expected vaccine coverage levels are calculated and analyzed. In a structured finite population, passive decision making process and initiative decision making process are defined. It is also analytically and numerically proved that the passive decision making process can predict a higher vaccine coverage level than the process of initiative decision making.
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