Cutting-edge research on computational modeling of public health emergencies and simulations of the potential response, brought together by the University of Pittsburgh Graduate School of Public Health, is featured in a special issue of the Journal of Public Health Management and Practice.

The September/October special issue features nearly a dozen studies sparked by innovative collaborations among infectious disease specialists and industrial engineers, epidemiologists and geospatial engineers, political scientists and statisticians at last year's "Dynamics of Preparedness: A Public Health Systems Conference."

"Such interdisciplinary research collaborations can be challenging, but also very rewarding when it comes to protecting public health," said Margaret Potter, J.D., M.S., guest editor of the special issue and director of the Center for Public Health Practice at Pitt Public Health. "Having now invested in forming these partnerships, it's time to invest in sustaining them."

The special issue of the journal is available online for free to the public. This open access was provided by Pitt Public Health's Models of Infectious Disease Agent Study (MIDAS) National Center of Excellence, funded by the National Institute of General Medical Sciences at the National Institutes of Health.

"At Pitt Public Health, we are at the forefront of computer modeling to address a variety of public health questions," said Donald S. Burke, M.D., Pitt Public Health dean and UPMC-Jonas Salk Chair of Global Health, who co-authored an article in the special issue. "Such work will facilitate better planning and preparedness for a variety of threats to public health, including natural and man-made disasters, as well as important societal problems, such as crime, obesity and smoking. We intend to make modeling and simulation a regular, day-to-day decision support tool for public health officials."

Pitt's Public Health Dynamics Laboratory is developing such tools, including a sophisticated database for gathering and analysis of public health data, a framework for modeling how the actions and interactions of different groups affect the entire population, and a publicly accessible web service that translates epidemiological information onto a map for more intuitive exploration.

Computational modeling to support public health decisions has proven valuable in recent emergencies, explained Nicole Lurie, M.D., M.S.P.H., assistant secretary for preparedness and response, U.S. Department of Health and Human Services, and co-author of a commentary in the journal's special issue.

"Recent public health crises, ranging from the 2009 H1N1 influenza pandemic to the Deepwater Horizon oil spill and Fukushima Daiichi nuclear accident, required leaders at all levels of government and the private sector to make decisions during times when knowledge was highly uncertain and limited," she said. "But each time, the scientific modeling community quickly engaged with public health response efforts to help consider how these events might unfold using computational models to generate alternative scenarios and to predict outcomes."