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题名Modeling vaccination decision making process in a finite population
作者
发表日期2019-05-01
发表期刊Mathematical Biosciences
ISSN/eISSN0025-5564
卷号311页码:82-90
摘要

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.

关键词Decision making process Deterministic models Evolutionary game theory Moran process Pairwise approximation Stochastic models
DOI10.1016/j.mbs.2018.09.003
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收录类别SCIE
语种英语English
WOS研究方向Life Sciences & Biomedicine - Other Topics ; Mathematical & Computational Biology
WOS类目Biology ; Mathematical & Computational Biology
WOS记录号WOS:000466821300008
Scopus入藏号2-s2.0-85062899309
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被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符https://repository.uic.edu.cn/handle/39GCC9TT/9003
专题个人在本单位外知识产出
作者单位
Department of Mathematics and Statistics,Texas Tech University,Lubbock,79409-1042,United States
推荐引用方式
GB/T 7714
Bai, Fan. Modeling vaccination decision making process in a finite population[J]. Mathematical Biosciences, 2019, 311: 82-90.
APA Bai, Fan. (2019). Modeling vaccination decision making process in a finite population. Mathematical Biosciences, 311, 82-90.
MLA Bai, Fan."Modeling vaccination decision making process in a finite population". Mathematical Biosciences 311(2019): 82-90.
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