Impact of decentralized decision making on access to cholera treatment in Haiti

dc.contributor.authorMoore, Brian D.
dc.date.accessioned2012-06-07T15:01:47Z
dc.date.available2012-06-07T15:01:47Z
dc.date.graduationmonthAugust
dc.date.issued2012-06-07
dc.date.published2012
dc.description.abstractIn many humanitarian and public health settings, multiple organizations act independently to locate facilities to serve an affected population. As a result of this decentralized decision-making environment, individuals’ access to facility resources may suffer in comparison to a hypothetical system in which a single planner locates the facilities to optimize access for all. Furthermore, due to the unanticipated nature of humanitarian events and the urgency of the need, responders often must cope with a high level of uncertainty regarding the future supply of resources and demand for relief. The contributions of this thesis address the challenges that arise due to the decentralized and dynamic nature of humanitarian response. The first goal of this research is to quantify the difference between decentralized system performance and that possible with a centralized planner. The second goal is to demonstrate the value and feasibility of using a dynamic, rolling-horizon framework to optimize facility location decisions over time. This work compares individuals’ access to health facilities resulting from location decisions made by decentralized decision-makers to the access achieved by a centralized model that optimizes access for all. Access is measured using a special case of the gravity model, the Enhanced Two-Step Floating Catchment Area (E2SFCA) method, which is a distance-weighted ratio of capacity to demand. The E2SFCA method is integrated with integer programming to optimize public access to health facilities. This method is applied to the location of cholera treatment facilities in Haiti, which has been afflicted with a cholera epidemic since October 2010. This research finds that access varied significantly across Haiti, and in the month of February 2011, thirty-seven of the 570 sections, representing 474,286 persons (4.8 percent of the population), did not have adequate access to cholera treatment facilities. Using centralized models to optimize accessibility, performance can be improved but no single model is dominant. This paper recommends use of an efficiency-oriented model in conjunction with an equity constraint to make facility location decisions in future responses. Finally, this work successfully integrates measures of access and equity into a rolling-horizon facility location model and demonstrates that these measures can be incorporated in a full-scale implementation to provide dynamic decision support to planners. This paper advocates for greater awareness of the impact of decentralization in humanitarian response and recommends that future work be undertaken to discover incentives and strategies to mitigate the impact of decentralization in future responses.
dc.description.advisorJessica L. Heier Stamm
dc.description.degreeMaster of Science
dc.description.departmentDepartment of Industrial & Manufacturing Systems Engineering
dc.description.levelMasters
dc.identifier.urihttp://hdl.handle.net/2097/13919
dc.language.isoen_US
dc.publisherKansas State University
dc.rights© the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectDecentralized decision-making
dc.subjectFacility location
dc.subjectAccessibility
dc.subjectEquity
dc.subjectHaiti
dc.subject.umiEngineering (0537)
dc.subject.umiGeographic Information Science and Geodesy (0370)
dc.subject.umiIndustrial Engineering (0546)
dc.subject.umiOperations Research (0796)
dc.subject.umiPublic Health (0573)
dc.titleImpact of decentralized decision making on access to cholera treatment in Haiti
dc.typeThesis

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