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Title of Journal: Ann Oper Res

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Abbravation: Annals of Operations Research

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Springer US

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DOI

10.1007/s00419-005-0442-1

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1572-9338

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An analytic framework to develop policies for test

Authors: Hoda Parvin Piyush Goel Natarajan Gautam
Publish Date: 2012/03/14
Volume: 196, Issue: 1, Pages: 707-735
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Abstract

In this paper we consider healthcare policy issues for trading off resources in testing prevention and cure of twostage contagious diseases An individual that has contracted the twostage 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 decisionmaking 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 finetune the asymptotically optimal solution for the nonasymptotic 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 allocationThe authors would like to thank Prof BE Pruitt in the department of Health and Kinesiology at Texas AM University who provided us with help and guidance to formulate this problem as well as to lay out the appropriate assumptions The authors are also grateful to the editor and referees for their comments that significantly improved the content and presentation of this paper

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