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COVID-19 Epidemiological, Behavioral, and Economic Model

In: Machine Learning Perspectives of Agent-Based Models

Author

Listed:
  • Anand Rao

    (Carnegie Mellon University, Heinz College of Information Systems and Public Policy)

  • Sindy Ma

    (PricewaterhouseCoopers)

  • Mark Paich

    (PricewaterhouseCoopers)

  • Joseph Voyles

    (PricewaterhouseCoopers)

Abstract

COVID19 had a significant impact not only on the health of individuals across the globe, it also impacted their financial well-being. In addition, COVID19 also had a major impact on companies and their operations, governments and also the larger global macro-economic environment. In this article, we outline how we built a sophisticated collection of agent-based models that addressed the disease progression, the behavioral change of citizens, and the economic impact across different industry sectors, including hospital networks, health insurers, pharmaceutical and life sciences, and retail. Although the focus of these models were US the general principles apply across the globe. We use this as a case study to illustrate how to scope agent-based models, build them, calibrate them, and continuously refine them. We also use this case study to highlight the importance of designing agent-based models in a modular fashion to enable the linking of multiple ABMs.

Suggested Citation

  • Anand Rao & Sindy Ma & Mark Paich & Joseph Voyles, 2025. "COVID-19 Epidemiological, Behavioral, and Economic Model," Springer Books, in: Pedro Campos & Anand Rao & Joaquim Margarido (ed.), Machine Learning Perspectives of Agent-Based Models, chapter 0, pages 99-126, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-73354-3_5
    DOI: 10.1007/978-3-031-73354-3_5
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