Enhancing Pandemic Preparedness Using Mean Field and Simulation Modeling

Mohammad Dehghanimohammadabadai, Gökçe Dayanikli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The COVID-19 pandemic has emphasized the importance of preparedness and response plans for healthcare providers and rational responses from society to effectively manage infectious disease outbreaks. Strategic guidelines should be created to ensure the availability of required resources while considering the rational response of individuals under different policy scenarios. This study uses a simulation-optimization-game theory approach to first determine the daily number of infected people in response to social distancing policies in a game theoretical setup. Second, this daily number of infected people is used in a simulation to determine an optimal replenishment policy for restocking personal protective equipment (PPE) items. The model incorporates a combination of mean field games modeling and a simulation model in Simio to perform optimization tasks. This approach aims to guarantee the availability of required resources by taking into account the rational response of individuals under different policy scenarios.

Original languageEnglish (US)
Title of host publication2023 Winter Simulation Conference, WSC 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages970-981
Number of pages12
ISBN (Electronic)9798350369663
DOIs
StatePublished - 2023
Event2023 Winter Simulation Conference, WSC 2023 - San Antonio, United States
Duration: Dec 10 2023Dec 13 2023

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736

Conference

Conference2023 Winter Simulation Conference, WSC 2023
Country/TerritoryUnited States
CitySan Antonio
Period12/10/2312/13/23

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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