A new method of exercising pandemic preparedness through an interactive simulation and visualization.
As seen in the spring 2009 A/H1N1 influenza outbreak, influenza pandemics can have profound social, legal and economic effects. This experience has also made the importance of public health preparedness exercises more evident. Universities face unique challenges with respect to pandemic preparedness due to their dense student populations, location within the larger community and frequent student/faculty international travel. Depending on the social structure of the community, different mitigation strategies should be applied for decreasing the severity and transmissibility of the disease. To this end, Arizona State University has developed a simulation model and tabletop exercise that facilitates decision-maker interactions around emergency-response scenarios. This simulation gives policy makers the ability to see the real-time impact of their decisions. Therefore, tabletop exercises with computer simulations are developed to practice these decisions, which can possibly give opportunities for practicing better policy implementations. This paper introduces a new method of designing and performing table-top exercises for pandemic influenza via state-of-the-art technologies including system visualization and group decision making with a supporting simulation model. The presented exercise methodology can increase readiness for a pandemic through the support of computer and information technologies and the survey results that we include in this paper certainly support this result. The video scenarios and the computer simulation model make the exercise appear very compelling and real, which makes this presented method of exercising different than the other table-top exercises in the literature. Finally, designing a pandemic preparedness exercise with supporting technologies can help identifying the communication gaps between responsible authorities and advance the table-top exercising methodology.
Araz
Ozgur M
OM
Center for Computational Biology and Bioinformatics, The University of Texas, Austin, TX, USA. oaraz@asu.edu
Jehn
Megan
M
Lant
Timothy
T
Fowler
John W
JW
D001130:Arizona; D004189:Disaster Planning / Q000379:methods*; D006801:Humans; D017146:Models, Organizational; D058873:Pandemics; D011050:Policy Making