Game-Theoretic Vaccination Against Networked SIS Epidemics and Impacts of Human Decision-Making
Game-Theoretic Vaccination Against Networked SIS Epidemics and Impacts of Human Decision-Making
复制标题
DOI：
10.1109/tcns.2019.2897904
复制
发表时间：
2019-12-01
影响因子：
4.2
通讯作者：
Sundaram, Shreyas
中科院分区：
文献类型：
--
作者：
Hota, Ashish R.;Sundaram, Shreyas
在本文中，我们研究了分散的保护策略，对网络上的易受感染的流行病。我们考虑一个人口博弈框架，节点选择是否接种疫苗，和流行病的风险被定义为在流行病的流行状态下的感染概率基于度的平均场近似。行为经济学的研究表明，人类感知概率和风险的非线性方式的动机，我们专门研究这种误解的纳什均衡保护策略的影响。我们首先建立了一个阈值均衡的存在性和唯一性，其中度大于一定阈值的节点接种疫苗。当疫苗接种成本足够高时，我们发现行为偏差会导致更少的玩家接种疫苗，反之亦然。我们量化这种影响的一类网络的幂律度分布证明紧边界的比例下的行为和真实的感知概率的平衡阈值。我们进一步刻画了社会最优疫苗接种策略，并研究了纳什均衡的无效率性。
In this paper, we study decentralized protection strategies against susceptible-infected-susceptible epidemics on networks. We consider a population game framework where nodes choose whether or not to vaccinate themselves, and the epidemic risk is defined as the infection probability at the endemic state of the epidemic under a degree-based mean-field approximation. Motivated by studies in behavioral economics showing that humans perceive probabilities and risks in a nonlinear fashion, we specifically examine the impacts of such misperceptions on the Nash equilibrium protection strategies. We first establish the existence and uniqueness of a threshold equilibrium where nodes with degrees larger than a certain threshold vaccinate. When the vaccination cost is sufficiently high, we show that behavioral biases cause fewer players to vaccinate, and vice versa. We quantify this effect for a class of networks with power-law degree distributions by proving tight bounds on the ratio of equilibrium thresholds under behavioral and true perceptions of probabilities. We further characterize the socially optimal vaccination policy and investigate the inefficiency of Nash equilibrium.