Collection

Modeling and Control of Epidemics

Submission status
Closed

The recent COVID-19 pandemic has caused a significant social and economic disruption in today’s connected world. There is an imminent need to understand and control the spreading of the disease over networks. Dynamic games provide a natural framework to model and analyze the individual incentives and their social interactions over large networks. Sophisticated models such as evolutionary games and mean-field games have enabled the understanding of the emerging population-level phenomena and effective control mechanisms. Connecting dynamic games and epidemic models offers a scientific foundation for rigorous and quantitative analysis and design of screening, containment, and mitigation strategies for large-scale dynamic and network systems. This cross-disciplinary approach will not only address the current challenges with COVID-19 but also shed light on related problems of computer viruses and misinformation in networks.

Editors

  • Quanyan Zhu Quanyan Zhu , 

    Quanyan Zhu

    New York University, Department of Electrical and Computer Engineering, Brooklyn, NY, USA

  • Elena Gubar Elena Gubar  &

    Elena Gubar

    Saint-Petersburg State University, Department of Mathematical Game Theory and Statistical Decisions, St Petersburg, Russia

  • Eitan Altman Eitan Altman

    Eitan Altman

    INRIA Sophia Antipolis, France

Articles (13 in this collection)

  2. The Mask Game with Multiple Populations

    Authors (first, second and last of 5)

    • Eitan Altman
    • Mandar Datar
    • Daniel Sadoc Menasché
    • Content type: OriginalPaper
    • Published: 28 February 2022
    • Pages: 147 - 167