Department of Mathematics, Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA,
Bull Math Biol. 2013 Oct;75(10):1961-84. doi: 10.1007/s11538-013-9879-5. Epub 2013 Aug 14.
Around the world, infectious disease epidemics continue to threaten people's health. When epidemics strike, we often respond by changing our behaviors to reduce our risk of infection. This response is sometimes called "social distancing." Since behavior changes can be costly, we would like to know the optimal social distancing behavior. But the benefits of changes in behavior depend on the course of the epidemic, which itself depends on our behaviors. Differential population game theory provides a method for resolving this circular dependence. Here, I present the analysis of a special case of the differential SIR epidemic population game with social distancing when the relative infection rate is linear, but bounded below by zero. Equilibrium solutions are constructed in closed-form for an open-ended epidemic. Constructions are also provided for epidemics that are stopped by the deployment of a vaccination that becomes available a fixed-time after the start of the epidemic. This can be used to anticipate a window of opportunity during which mass vaccination can significantly reduce the cost of an epidemic.
在全球范围内,传染病疫情继续威胁着人们的健康。当疫情爆发时,我们通常会通过改变行为来降低感染风险。这种反应有时被称为“社交隔离”。由于行为改变可能代价高昂,我们希望了解最佳的社交隔离行为。但是行为变化的好处取决于疫情的进程,而疫情的进程又取决于我们的行为。差分人口博弈论为解决这种循环依赖提供了一种方法。在这里,我提出了一个特殊情况下的差分 SIR 传染病人口博弈的分析,其中社交隔离时的相对感染率是线性的,但下限不为零。对于无界疫情,构建了平衡点的封闭形式解。还提供了通过在疫情开始后固定时间部署疫苗来阻止疫情的构造。这可以用来预测一个机会窗口,在此期间大规模接种疫苗可以显著降低疫情的成本。