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.
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.
Authors: Katherine Aaby; Rachel L Abbey; Jeffrey W Herrmann; Mark Treadwell; Carol S Jordan; Kathy Wood Journal: J Public Health Manag Pract Date: 2006 Jul-Aug
Authors: Ali Asgary; Mahdi M Najafabadi; Sarah K Wendel; Daniel Resnick-Ault; Richard D Zane; Jianhong Wu Journal: Health Technol (Berl) Date: 2021-10-05