ABM-SIRTEM: A Hybrid Agent-Based and Epidemiological Model for Pandemic Response

2026-09-16

AI Summary

本文提出ABM-SIRTEM模型，结合职业、经济生产力和个人福利等因素，动态模拟政府干预下的遵从行为，以研究疾病传播与社会经济行为之间的相互作用。

Abstract

The COVID-19 pandemic has had profound impacts on global health, social structures, and economies. It disproportionately affected lower socioeconomic groups and those reliant on interaction-based jobs. Regulatory bodies faced the challenge of designing policies that preserve public health while limiting disruption to economic stability and productivity. Epidemiological models such as SIR and agent-based models (ABMs) have been used to study disease dynamics and the socioeconomic impacts of disease and interventions. Population-level models often simplify individual heterogeneity, while detailed ABMs can become computationally expensive as the numbers of agents and interactions increase. We propose ABM-SIRTEM, a hybrid model that incorporates occupation categories, economic productivity, and welfare at the individual level while dynamically modeling compliance with government interventions. We calibrate the model against historical positive and negative test counts from four U.S. states and examine the resulting compliance dynamics. This framework provides a basis for studying the interaction between disease spread and socioeconomic behavior in pandemic-response planning.

Problem

• Pandemic Response
• Economic Stability
• Public Health
• Socioeconomic Behavior

Innovation

• hybrid model
• agent-based models
• epidemiological models
• compliance with interventions
• socioeconomic behavior