Optimal Vaccination in a Stochastic Epidemic Model of Two Non-Interacting Populations |
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| Authors: | Edwin C Yuan David L Alderson Sean Stromberg Jean M Carlson |
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| Institution: | 1Physics Department, University of California Santa Barbara, Santa Barbara, California, United States of America;2Operations Research Department, Naval Postgraduate School, Monterey, California, United States of America;3Applied Physics Department, Stanford University, Stanford, California, United States of America;University of Melbourne, AUSTRALIA |
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| Abstract: | Developing 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 efficient algorithm that enables us to calculate the complete probability distribution for the final 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. |
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