Decision-dependent distributionally robust Markov decision process method in dynamic epidemic control

In this article, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is widely used to represent the stochastic spread of infectious diseases, such as COVID-19. Al...

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Bibliographic Details
Published in:IISE transactions Vol. ahead-of-print; no. ahead-of-print; pp. 1 - 13
Main Authors: Song, Jun, Yang, William, Zhao, Chaoyue
Format: Journal Article
Language:English
Published: Taylor & Francis 02.04.2024
Subjects:
Distributionally robust Markov decision process
distributionally robust optimization
epidemic control
real-time dynamic programming
SEIR model
ISSN:2472-5854, 2472-5862
Online Access:Get full text
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Summary:In this article, we present a Distributionally Robust Markov Decision Process (DRMDP) approach for addressing the dynamic epidemic control problem. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is widely used to represent the stochastic spread of infectious diseases, such as COVID-19. Although the Markov Decision Process (MDP) offers a mathematical framework for identifying optimal actions, such as vaccination and transmission-reducing intervention, to combat disease spread calculated using the SEIR model. However, uncertainties in these scenarios demand a more robust approach that is less reliant on error-prone assumptions. The primary objective of our study is to introduce a new DRMDP framework that allows for an ambiguous distribution of transition dynamics. Specifically, we consider the worst-case distribution of these transition probabilities within a decision-dependent ambiguity set. To overcome the computational complexities associated with policy determination, we propose an efficient Real-Time Dynamic Programming (RTDP) algorithm that is capable of computing optimal policies based on the reformulated DRMDP model in an accurate, timely, and scalable manner. Comparative analysis against the classic MDP model demonstrates that the DRMDP achieves a lower proportion of infections and susceptibilities at a reduced cost.
ISSN:2472-5854
2472-5862
DOI:10.1080/24725854.2023.2219281