My talk from the Epidemics² conference in Athens describes our recent application of bandit-based search for computing antiviral distributions for the U.S. National Antiviral Stockpile.

At the beginning of the summer in 2009, the U.S. government learned of the swine-origin influenza outbreak.  Immediately, the government released 11 million courses of antivirals from the national stockpile for immediate use by the states.  The states themselves had purchased some antivirals, totaling 35 million courses available for immediate use.  Additionally, the U.S. government had 50 million courses in reserve in the national stockpile.  We address the question of how and when antivirals from U.S. National Antiviral Stockpile should be released to best control an influenza outbreak.  We do this quantitatively, using a national scale disease model and recent simulation optimization techniques.

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Lauren Ancel Meyers, Sebastian Goll, and I have developed a simulation and optimization software bundle targeted at computing disease control strategies.  The bundle is called the Disease Control System (DiCon) and comes with a ready-made national scale disease simulator, an optimization platform for computing intervention strategies, and a visualization toolkit.  The visualization toolkit was developed by Greg Johnson at TACC and the simulator was developed by Priyank Patel.

Talks detailing both the features of DiCon and a recent application of the system to antiviral control of H1N1 have recently been uploaded.

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My talk from the San Diego INFORMS, 2009, describes a general model for vector-borne disease modeling and control.  But, more interestingly, the talk covers our application of that model to the spead of Leishmaniasis in Texas.

Leishmaniasis has been spreading north, from the border with Mexico and into Texas for the past several decades.  The disease made a jump in around the year 2000 from west Texas to east Texas.  We found that this was due to the underlying reservoir populations.  In addition, in this talk, I discuss computational techniques for computing control locations to stop the spread of Leishmaniasis.

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