谁应该接种疫苗？通过SIR网络实现疫苗个体化分配
Who Should Get Vaccinated? Individualized Allocation of Vaccines Over SIR Network
摘要：
如何在异质个体之间分配疫苗是大流行时期的重要决策之一。本文开发了一个程序来评估有限供应下的个性化疫苗分配政策，利用社会网络数据包含个人的人口统计特征和健康状况。我们模型的疫苗的溢出效应的基础上异质互动SIR网络模型和估计个性化的疫苗分配政策，通过最大化估计的社会福利（公共卫生）标准，将溢出。虽然这个优化问题通常是一个NP-难整数优化问题，我们表明，SIR结构导致一个子模块化的目标函数，并提供了一个计算上有吸引力的贪婪算法近似的解决方案，具有理论性能保证。在此基础上，我们构造了一个有限样本的福利遗憾界，并考察了其一致收敛速度与社会网络的复杂性和风险性的关系。在模拟中，我们通过比较我们的方法与没有网络信息的目标来说明考虑溢出的重要性。
英文摘要：
How to allocate vaccines over heterogeneous individuals is one of the important policy decisions in pandemic times. This paper develops a procedure to estimate an individualized vaccine allocation policy under limited supply, exploiting social network data containing individual demographic characteristics and health status. We model spillover effects of the vaccines based on a Heterogeneous-Interacted-SIR network model and estimate an individualized vaccine allocation policy by maximizing an estimated social welfare (public health) criterion incorporating the spillovers. While this optimization problem is generally an NP-hard integer optimization problem, we show that the SIR structure leads to a submodular objective function, and provide a computationally attractive greedy algorithm for approximating a solution that has theoretical performance guarantee. Moreover, we characterise a finite sample welfare regret bound and examine how its uniform convergence rate depends on the complexity and riskiness of social network. In the simulation, we illustrate the importance of considering spillovers by comparing our method with targeting without network information.
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