Publication:
Modeling influenza pandemic and planning food distribution

dc.contributor.authorEkici, Ali
dc.contributor.authorKeskinocak, P.
dc.contributor.authorSwann, J. L.
dc.contributor.departmentIndustrial Engineering
dc.contributor.ozuauthorEKİCİ, Ali
dc.date.accessioned2014-11-25T12:54:44Z
dc.date.available2014-11-25T12:54:44Z
dc.date.issued2014
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.en_US
dc.description.abstractBased on the recent incidents of H5N1, H1N1, and influenza pandemics in history (1918, 1957, and 1968) experts believe that a future influenza pandemic is inevitable and likely imminent. Although the severity of influenza pandemics vary, evidence suggests that an efficient and rapid response is crucial for mitigating morbidity, mortality, and costs to society. Hence, preparing for a potential influenza pandemic is a high priority of governments at all levels (local, state, federal), nongovernmental organizations (NGOs), and companies. In a severe pandemic, when a large number of people are ill, infected persons and their families may have difficulty purchasing and preparing meals. Various government agencies and NGOs plan to provide meals to these households. In this paper, in collaboration with the American Red Cross, we study food distribution planning during an influenza pandemic. We develop a disease spread model to estimate the spread pattern of the disease geographically and over time, combine it with a facility location and resource allocation network model for food distribution, and develop heuristics to find near-optimal solutions for large instances. We run our combined disease spread and facility location model for the state of Georgia and present the estimated number of infections and the number of meals needed in each census tract for a one-year period along with a design of the supply chain network. Moreover, we investigate the impact of voluntary quarantine on the food demand and the food distribution network and show that its effects on food distribution can be significant. Our results could help decision makers prepare for a pandemic, including how to allocate limited resources and respond dynamically.en_US
dc.identifier.doi10.1287/msom.2013.0460
dc.identifier.endpage27
dc.identifier.issn1526-5498
dc.identifier.issue1
dc.identifier.scopus2-s2.0-84893903387
dc.identifier.startpage11
dc.identifier.urihttps://doi.org/10.1287/msom.2013.0460
dc.identifier.volume16
dc.identifier.wos000343747400002
dc.language.isoengen_US
dc.peerreviewedyesen_US
dc.publicationstatuspublisheden_US
dc.publisherInformsen_US
dc.relation.ispartofManufacturing & Service Operations Management
dc.relation.publicationcategoryInternational Refereed Journal
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsInfluenza pandemicen_US
dc.subject.keywordsFood distribution planningen_US
dc.subject.keywordsDisease spread modelsen_US
dc.subject.keywordsMultiperiod facility locationen_US
dc.subject.keywordsDynamic updateen_US
dc.titleModeling influenza pandemic and planning food distributionen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isOrgUnitOfPublication5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b
relation.isOrgUnitOfPublication.latestForDiscovery5dd73c02-fd2d-43e0-9a23-71bab9ae0b6b

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