Public health informatics - biosurveillance and operations strategies

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Liu, Yifan
Lee, Eva K.
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Infectious diseases are one of the most common yet most serious types of public health crisis. To react efficiently and effectively to waves of infectious disease outbreaks, decision-makers and public health officers must quickly analyze the current situation and predict the potential trend of an outbreak, evaluate multiple countermeasures and strategies, and implement an intervention plan that optimizes utilization of the limited resource while achieving the best containment results. In this dissertation, we advance infectious diseases models with applications in medical countermeasure operations and biosurveillance. We first propose a general-purpose modeling framework for infectious disease outbreaks by expanding and abstracting the traditional compartmental models. Our modeling framework is highly generic and can be viewed as a meta-model for compartmental models. We discuss how it can be used to facilitate decision making to achieve best containment results by equipping the disease modeling framework with an optimization engine to determine the optimal resource allocation strategy during an outbreak and investigate the impact of point-of-dispensing sites (PODs) for rapid medical countermeasures dispensing during an outbreak. We demonstrate how this modeling technique can be computerized and used to support public health operations by explaining the design and functionalities of an enterprise software package, the RealOpt suite. Designed at Georgia Institute of Technology in collaboration with the Centers for Disease Control and Prevention since 2005, RealOpt is a modularized system. We focus the discussion on an expanded module within the RealOpt suite known as RealOpt-Regional.
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