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arXiv 2201.10529math.DScs.SYeess.SYmath.OC
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流行病种群博弈与进化动力学

Epidemic Population Games And Evolutionary Dynamics

Nuno C. Martins, Jair Certorio, Richard J. La

摘要:

我们提出了一个系统理论的方法来选择和稳定的SIRS流行病模型的地方病平衡点,其中人口的决策战略相互作用的代理决定的传输速率。具体地说,人口的代理人经常修改他们的选择出一组策略,影响到不同的水平的传输速率。一个支付向量量化了计划者为每个策略提供的激励,在扣除策略的内在成本后,影响了修正过程。一个进化动力学模型捕捉人口的偏好,在修订过程中指定的支付向量的函数的代理人的选择流向战略的利率具有较高的回报。我们的主要结果是一个动态的回报机制,保证引导流行病变量(通过激励人口)的地方病平衡与最小的传染分数,受成本约束。我们使用的李雅普诺夫函数不仅建立收敛,但也获得(任何时候)人口的传染性部分的峰值大小的上界。

英文摘要:

We propose a system theoretic approach to select and stabilize the endemic equilibrium of an SIRS epidemic model in which the decisions of a population of strategically interacting agents determine the transmission rate. Specifically, the population's agents recurrently revise their choices out of a set of strategies that impact to varying levels the transmission rate. A payoff vector quantifying the incentives provided by a planner for each strategy, after deducting the strategies' intrinsic costs, influences the revision process. An evolutionary dynamics model captures the population's preferences in the revision process by specifying as a function of the payoff vector the rates at which the agents' choices flow toward strategies with higher payoffs. Our main result is a dynamic payoff mechanism that is guaranteed to steer the epidemic variables (via incentives to the population) to the endemic equilibrium with the smallest infectious fraction, subject to cost constraints. We use a Lyapunov function not only to establish convergence but also to obtain an (anytime) upper bound for the peak size of the population's infectious portion.

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