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dc.contributor.authorDimitrov, Nedialko B.
dc.contributor.authorMeyers, Lauren Ancel
dc.dateNovember 2010
dc.date.accessioned2013-03-27T18:21:51Z
dc.date.available2013-03-27T18:21:51Z
dc.date.issued2010-11
dc.identifier.citationTutORials in Operations Research, Hanover, MD: INFORMS, November 2010
dc.identifier.urihttps://hdl.handle.net/10945/30356
dc.description.abstractMathematics has long been an important tool for understanding and controlling the spread of infectious diseases. Here, we begin with an overview of compartmental models, the traditional approach to modeling infectious disease dynamics, and then introduce contact network epidemi- ology, a relatively new approach that applies bond percolation on random graphs to model the spread of infectious disease through heterogeneous populations. As we illustrate, these methods can be used to address public health challenges and have recently been coupled with powerful computational methods to optimize epidemic control strategies.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.titleMathematical Approaches to Infectious Disease Prediction and Controlen_US
dc.typeArticleen_US


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