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dc.contributor.authorYuan, Edwin C.
dc.contributor.authorAlderson, David L.
dc.contributor.authorStromberg, Sean
dc.contributor.authorCarlson, Jean M.
dc.date.accessioned2015-02-04T23:28:52Z
dc.date.available2015-02-04T23:28:52Z
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10945/44460
dc.description.abstractDeveloping robust, quantitative methods to optimize resource allocations in response to epidemics has the potential to save lives and minimize health care costs. In this paper, we develop and apply a computationally e cient algorithm that enables us to calculate the complete probability distribution for the nal epidemic size in a stochastic Susceptible-Infected-Recovered (SIR) model. Based on these results, we determine the optimal allocations of a limited quantity of vaccine between two non-interacting populations. We compare the stochastic solution to results obtained for the traditional, deterministic SIR model. For intermediate quantities of vaccine, the deterministic model is a poor estimate of the optimal strategy for the more realistic, stochastic case.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleOptimal vaccination in a stochastic epidemic model of two non-interacting populationsen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Research
dc.description.funderThis work was supported by an O ce of Naval Research MURI Grant No. DMR0606092, the David and Lucile Packard Foundation, the Institute for Collaborative Biotechnologies through contract no. W911NF-09-D-0001 from the U.S. Army Research O ce, and the Stansberry Fellowship through the CCS SURF foundation.en_US


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