A0798
Title: Optimizing policy decisions in interconnected populations: A spatially-dependent framework for dynamic decision-making
Authors: Yunan Wu - Tsinghua University (China) [presenting]
Jimi Kim - University of Texas at Dallas (United States)
Abstract: Dynamic decision-making is crucial in policy formation. In reality, states or countries typically make these decisions, and their effects are interdependent due to spatial relationships. However, conventional policy decision-making strategies often overlook these spatial effects, assuming no interference among individuals. A novel framework is proposed to measure these interdependent effects across multiple stages. The methods are also proposed to estimate the optimal policy regime, taking the spatial effects into consideration for a series of time spots, as well as constructing confidence intervals for the coefficients indexing the optimal policy regime based on multiplier bootstrap methods. The validity of the proposed estimation and inference methods is rigorously demonstrated. The proposed method is applied to a case study on COVID-19 school closing policies. By applying the methodologies to real-world data on state-level interventions and outcomes, it is illustrated how this approach can optimize policy decisions. Findings have substantial implications for enhancing the effectiveness of personalized intervention strategies in interconnected populations. This approach has the potential to revolutionize precision policy-making in spatially dependent contexts while maintaining a balance between public health and economic considerations.
