2014 journal article
Systems Engineering Methods for Enhancing the Value Stream in Public Health Preparedness: The Role of Markov Models, Simulation, and Optimization
PUBLIC HEALTH REPORTS, 129, 145–153.
MeSH headings : Computer Simulation; Disaster Planning / organization & administration; Disaster Planning / standards; Disease Outbreaks / prevention & control; Humans; Influenza, Human / prevention & control; Markov Chains; Models, Organizational; Operations Research; Public Health Practice; Quality Improvement
TL;DR:
Three models developed through a four-year partnership with stakeholders from state and local public health for effectively, efficiently, and appropriately responding to potential public health threats are presented.
(via Semantic Scholar)
open access via europepmc.org (repository)
UN Sustainable Development Goal Categories
3. Good Health and Well-being
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
Objectives. Large-scale incidents such as the 2009 H1N1 outbreak, the 2011 European Escherichia coli outbreak, and Hurricane Sandy demonstrate the need for continuous improvement in emergency preparation, alert, and response systems globally. As questions relating to emergency preparedness and response continue to rise to the forefront, the field of industrial and systems engineering (ISE) emerges, as it provides sophisticated techniques that have the ability to model the system, simulate, and optimize complex systems, even under uncertainty. Methods. We applied three ISE techniques—Markov modeling, operations research (OR) or optimization, and computer simulation—to public health emergency preparedness. Results. We present three models developed through a four-year partnership with stakeholders from state and local public health for effectively, efficiently, and appropriately responding to potential public health threats: ( 1) an OR model for optimal alerting in response to a public health event, ( 2) simulation models developed to respond to communicable disease events from the perspective of public health, and ( 3) simulation models for implementing pandemic influenza vaccination clinics representative of clinics in operation for the 2009–2010 H1N1 vaccinations in North Carolina. Conclusions. The methods employed by the ISE discipline offer powerful new insights to understand and improve public health emergency preparedness and response systems. The models can be used by public health practitioners not only to inform their planning decisions but also to provide a quantitative argument to support public health decision making and investment.