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Game theoretic modelling of infectious disease dynamics and intervention methods: a review.
Journal of Biological Dynamics ( IF 2.8 ) Pub Date : 2020-01-29 , DOI: 10.1080/17513758.2020.1720322
Sheryl L Chang 1 , Mahendra Piraveenan 1, 2 , Philippa Pattison 3 , Mikhail Prokopenko 1, 4
Affiliation  

We review research studies which use game theory to model the decision-making of individuals during an epidemic, attempting to classify the literature and identify the emerging trends in this field. The literature is classified based on (i) type of population modelling (classical or network-based), (ii) frequency of the game (non-repeated or repeated), and (iii) type of strategy adoption (self-learning or imitation). The choice of model is shown to depend on many factors such as the immunity to the disease, the strength of immunity conferred by the vaccine, the size of population and the level of mixing therein. We highlight that while early studies used classical compartmental modelling with self-learning games, in recent years, there is a substantial growth of network-based modelling with imitation games. The review indicates that game theory continues to be an effective tool to model decision-making by individuals with respect to intervention (vaccination or social distancing).

中文翻译:

传染病动力学和干预方法的博弈论模型:综述。

我们回顾了使用博弈论对流行病期间的个人决策建模的研究,试图对文献进行分类并确定该领域的新兴趋势。文献的分类基于(i)人口模型的类型(基于经典或基于网络的),(ii)游戏的频率(不重复或重复)和(iii)策略采用的类型(自学或模仿) )。显示模型的选择取决于许多因素,例如对疾病的免疫力,疫苗赋予的免疫力,人口规模和其中的混合水平。我们着重指出,尽管早期的研究使用带有自学游戏的经典隔间建模,但近年来,基于网络的带有仿制游戏的建模有了很大的增长。
更新日期:2020-01-29
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