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In the event of a public health emergency, it is very important that people receive medical treatment quickly. To implement a fast, effective response, we must have exceptionally efficient supply chains, and we must be prepared to make a huge number of logistical decisions rapidly. Consider, for example, an inhalational anthrax attack. Affected individuals must begin antibiotic prophylaxis within 48 hours to minimize the risk of fatal illness. The necessary antibiotics are stockpiled by the federal government, which must move the medicine to the affected state, which is responsible for setting up a distribution warehouse and moving the antibiotics either to ad hoc clinics or directly to individuals.
Operating this system requires countless logistical decisions. How much medicine should be moved to clinics and when should it be sent? How should delivery truck routes be planned? How many clinics should be opened and when? My work aims to help answer these types of questions. I am developing a set of dynamic optimization models of the supply chain, from the national stockpiles to the state-run distribution centers to the local treatment clinics. My goal is to derive optimal policies for managing the limited supplies of inventory to ensure that individuals receive care in the necessary time window, given that staff, transportation, and other resources are also constrained. I am also studying how, with a limited budget, infrastructure investments should be made to provide the most effective response.
Finding such policies is made difficult by the large size of the information state space and the stochastic nature of the problem. Even solving an approximation involves solving millions of individual optimization problems. In order to solve these problems using realistically large data sets, I am working to develop and implement highly parallelized algorithms which must then be run on a high performance machine.
Hupert, Nathaniel, Wei Xiong, Kathleen King, Michelle Castorena, Caitlin Hawkins, Cindie Wu, and John A. Muckstadt. "Uncertainty and Operational Considerations in Mass Prophylaxis Workforce Planning." Disaster Medicine and Public Health Preparedness. 2009;3:S121-131S.
Chan, Edward W., Carol E. Fan, Matthew W. Lewis, Kathleen King, Paul Dreyer, and Christopher Nelson. "The RSS-POD Supply Chain Management Game: An Exercise for Improving the Inventory Management and Distribution of Medical Countermeasures." RAND Working Paper. September 2009.
King, Kathleen and Jack Muckstadt. "Evaluating Planned Capacities for Public Health Emergency Supply Chain Models." Cornell University Technical Report No. 1475, September 2009.
Tilley, Burt S., Yevgeniya Zastavker, Kathleen King, Joanne Pratt. Evolution Equations of Biological Structures Formed in Cholesterol Crystallization Processes. Presented at SIAM Annual Meeting, July 2006.
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