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An analytic framework to develop policies for testing, prevention, and treatment of two-stage contagious diseases

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  • Hoda Parvin
  • Piyush Goel
  • Natarajan Gautam

Abstract

In this paper we consider healthcare policy issues for trading off resources in testing, prevention, and cure of two-stage contagious diseases. An individual that has contracted the two-stage contagious disease will initially show no symptoms of the disease but is capable of spreading it. If the initial stages are not detected which could lead to complications eventually, then symptoms start appearing in the latter stage when it would be necessary to perform expensive treatment. Under a constrained budget situation, policymakers are faced with the decision of how to allocate budget for prevention (via vaccinations), subsidizing treatment, and examination to detect the presence of initial stages of the contagious disease. These decisions need to be performed in each period of a given time horizon. To aid this decision-making exercise, we formulate a stochastic dynamic optimal control problem with feedback which can be modeled as a Markov decision process (MDP). However, solving the MDP is computationally intractable due to the large state space as the embedded stochastic network cannot be decomposed. Hence we propose an asymptotically optimal solution based on a fluid model of the dynamics in the stochastic network. We heuristically fine-tune the asymptotically optimal solution for the non-asymptotic case, and test it extensively for several numerical cases. In particular we investigate the effect of budget, length of planning horizon, type of disease, population size, and ratio of costs on the policy for budget allocation. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Hoda Parvin & Piyush Goel & Natarajan Gautam, 2012. "An analytic framework to develop policies for testing, prevention, and treatment of two-stage contagious diseases," Annals of Operations Research, Springer, vol. 196(1), pages 707-735, July.
    • Handle: RePEc:spr:annopr:v:196:y:2012:i:1:p:707-735:10.1007/s10479-012-1103-8
    DOI: 10.1007/s10479-012-1103-8
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    References listed on IDEAS

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    1. Lawrence M. Wein & Stefanos A. Zenios, 1996. "Pooled Testing for HIV Screening: Capturing the Dilution Effect," Operations Research, INFORMS, vol. 44(4), pages 543-569, August.
    2. Joseph T. Wu & Lawrence M. Wein & Alan S. Perelson, 2005. "Optimization of Influenza Vaccine Selection," Operations Research, INFORMS, vol. 53(3), pages 456-476, June.
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    Cited by:

    1. László Á. Kóczy, 2022. "Core-stability over networks with widespread externalities," Annals of Operations Research, Springer, vol. 318(2), pages 1001-1027, November.
    2. Marina Johnson & Abdullah Albizri & Serhat Simsek, 2022. "Artificial intelligence in healthcare operations to enhance treatment outcomes: a framework to predict lung cancer prognosis," Annals of Operations Research, Springer, vol. 308(1), pages 275-305, January.
    3. Dimitrov, Nedialko B. & Dimitrov, Stanko & Chukova, Stefanka, 2014. "Robust decomposable Markov decision processes motivated by allocating school budgets," European Journal of Operational Research, Elsevier, vol. 239(1), pages 199-213.

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