Optimal control for stochastic model of epidemic infections

Ali Nasir; Huma Rehman

doi:10.1109/IBCAST.2017.7868065

Optimal control for stochastic model of epidemic infections

Ali Nasir
, Huma Rehman

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

This paper discusses the development of a discrete stochastic model for SIR epidemic infection and calculation of the optimal control policy for the proposed model. Specifically, a Markov Decision Process based modeling approach is proposed as opposed to the traditional state space modeling. Proposed model consists of set of discrete states, actions, and transition probabilities. Selection of an optimality criterion is discussed for calculation of the optimal control policy. The behavior of the optimal policy and the tradeoffs involved in the selection of the optimality criterion are discussed through case study and graphical representations respectively. Furthermore, the concept of scaling the population size is introduced in order to tackle large scale problems.

Original language	English
Title of host publication	Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017
Editors	Muhammad Zafar-uz-Zaman
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	278-284
Number of pages	7
ISBN (Electronic)	9781467390736
DOIs	https://doi.org/10.1109/IBCAST.2017.7868065
State	Published - 1 Mar 2017
Externally published	Yes
Event	14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017 - Islamabad, Pakistan Duration: 10 Jan 2017 → 14 Jan 2017

Publication series

Name	Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017

Conference

Conference	14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017
Country/Territory	Pakistan
City	Islamabad
Period	10/01/17 → 14/01/17

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Markov Decision Processes
Optimal Policy
SIR Models
Stochastic Control

ASJC Scopus subject areas

Computer Science (miscellaneous)

Access to Document

10.1109/IBCAST.2017.7868065

Cite this

Nasir, A., & Rehman, H. (2017). Optimal control for stochastic model of epidemic infections. In M. Zafar-uz-Zaman (Ed.), Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017 (pp. 278-284). Article 7868065 (Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IBCAST.2017.7868065

Nasir, Ali ; Rehman, Huma. / Optimal control for stochastic model of epidemic infections. Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017. editor / Muhammad Zafar-uz-Zaman. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 278-284 (Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017).

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title = "Optimal control for stochastic model of epidemic infections",

abstract = "This paper discusses the development of a discrete stochastic model for SIR epidemic infection and calculation of the optimal control policy for the proposed model. Specifically, a Markov Decision Process based modeling approach is proposed as opposed to the traditional state space modeling. Proposed model consists of set of discrete states, actions, and transition probabilities. Selection of an optimality criterion is discussed for calculation of the optimal control policy. The behavior of the optimal policy and the tradeoffs involved in the selection of the optimality criterion are discussed through case study and graphical representations respectively. Furthermore, the concept of scaling the population size is introduced in order to tackle large scale problems.",

keywords = "Markov Decision Processes, Optimal Policy, SIR Models, Stochastic Control",

author = "Ali Nasir and Huma Rehman",

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year = "2017",

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Nasir, A & Rehman, H 2017, Optimal control for stochastic model of epidemic infections. in M Zafar-uz-Zaman (ed.), Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017., 7868065, Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017, Institute of Electrical and Electronics Engineers Inc., pp. 278-284, 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017, Islamabad, Pakistan, 10/01/17. https://doi.org/10.1109/IBCAST.2017.7868065

Optimal control for stochastic model of epidemic infections. / Nasir, Ali; Rehman, Huma.
Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017. ed. / Muhammad Zafar-uz-Zaman. Institute of Electrical and Electronics Engineers Inc., 2017. p. 278-284 7868065 (Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2017/3/1

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N2 - This paper discusses the development of a discrete stochastic model for SIR epidemic infection and calculation of the optimal control policy for the proposed model. Specifically, a Markov Decision Process based modeling approach is proposed as opposed to the traditional state space modeling. Proposed model consists of set of discrete states, actions, and transition probabilities. Selection of an optimality criterion is discussed for calculation of the optimal control policy. The behavior of the optimal policy and the tradeoffs involved in the selection of the optimality criterion are discussed through case study and graphical representations respectively. Furthermore, the concept of scaling the population size is introduced in order to tackle large scale problems.

AB - This paper discusses the development of a discrete stochastic model for SIR epidemic infection and calculation of the optimal control policy for the proposed model. Specifically, a Markov Decision Process based modeling approach is proposed as opposed to the traditional state space modeling. Proposed model consists of set of discrete states, actions, and transition probabilities. Selection of an optimality criterion is discussed for calculation of the optimal control policy. The behavior of the optimal policy and the tradeoffs involved in the selection of the optimality criterion are discussed through case study and graphical representations respectively. Furthermore, the concept of scaling the population size is introduced in order to tackle large scale problems.

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KW - Optimal Policy

KW - SIR Models

KW - Stochastic Control

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M3 - Conference contribution

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BT - Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017

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Nasir A, Rehman H. Optimal control for stochastic model of epidemic infections. In Zafar-uz-Zaman M, editor, Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 278-284. 7868065. (Proceedings of 2017 14th International Bhurban Conference on Applied Sciences and Technology, IBCAST 2017). doi: 10.1109/IBCAST.2017.7868065

Optimal control for stochastic model of epidemic infections

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this