Department of Mathematics and Statistics, Texas Tech University, Lubbock, TX 79409-1042, United States.
Math Biosci. 2019 May;311:82-90. doi: 10.1016/j.mbs.2018.09.003. Epub 2018 Nov 8.
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.
接种疫苗被认为是控制传染病传播的最关键方法之一。然而，由于其取决于人类行为，因此难以预测预期的疫苗接种率。我们考虑确定性和随机性模型来模拟接种场景下个体如何选择策略。在无限人口中，构建了一个复制者方程系统并计算了预期水平。讨论了无结构有限人口和结构有限人口中的决策过程。计算并分析了预期的疫苗接种率。在结构有限人口中，定义了被动决策过程和主动决策过程。还从理论和数值两方面证明了被动决策过程可以预测比主动决策过程更高的疫苗接种率。
