We describe RealOpt©, a simulation and decision-support system for planning large-scale emergency dispensing clinics to respond to biological threats and infectious-disease outbreaks. The system allows public-health administrators to investigate clinic-design and staffing scenarios quickly. The system incorporates efficient optimization technology seamlessly interfaced with a simulation module. The simulation studies we present explore facility-layout and staffing scenarios for an actual anthrax-emergency drill, and we discuss post-event analysis. Using our staff allocation and assignments for the exercise, DeKalb County achieved the highest throughput among all counties that simultaneously conducted the same scale of anthrax drill at various locations. Its labor usage was at or below that of the other counties. The external evaluators commented that DeKalb produced the most efficient floor plan (with no path crossing), the most cost-effective dispensing (lowest labor and throughput value), and the smoothest operations (shortest average wait time, average queue length, and equalized utilization rate). The study proves that even without historical data, the use of our system enables emergency personnel to plan ahead and be able to estimate required labor resources accurately. The exercise also revealed many areas that need attention during the operations planning and design of dispensing centers. A real-time decision-support system is, therefore, viable through careful design of a stand-alone simulator, coupled with powerful and tailored optimization solvers. The system facilitates analysis of “what-if” scenarios, and serves as an invaluable tool for operational planning and dynamic, on-the-fly reconfigurations of large-scale emergency dispensing clinics. It also allows performing “virtual field exercises” on the decision-support system, offering insight into operations flow and bottlenecks when mass dispensing is required for a region with a large population. Working with emergency-response departments, we will perform additional tuning and development of the system to address different biological attacks and infectious-disease outbreaks, and to ensure its practicality and usability.

A simulation and decision support system, RealOpt c , for planning large-scale emergency dispensing clinics to respond to biological threats and infectious disease outbreaks is described. The system allows public health administrators to investigate clinic design and staffing scenarios quickly.RealOpt c incorporates efficient optimization technology seamlessly interfaced with a simulation module. The system's correctness and computational advantage are validated via comparisons against simulation runs of the same model developed on a commercial system. Simulation studies to explore facility layout and staffing scenarios for smallpox vaccination and for an actual anthrax-treatment dispensing exercise and post event analysis are presented.The system produces results consistent with the model built on the commercial system, but requires only a fraction of the computational time. Each smallpox scenario runs within 1 CPU minute on RealOpt c , versus run times of over 5-10 hours on the commercial system. The system's fast computational time enables its use in large-scale studies, in particular an anthrax response planning exercise involving a county with 864,000 households. The computational effort required for this exercise was roughly 30 min for all scenarios considered, Preliminary results of this study were presented at INFORMS Colorado Oct. 2004. The system developed has been reported in the Springer 26 Ann Oper Res (2006) 148:25-53 demonstrating that RealOpt c offers a very promising avenue for pursuing a comprehensive investigation involving a more diverse set of scenarios, and justifying work towards development of a robust system that can be widely deployed for use by state, local, and tribal health practitioners.Using our staff allocation and assignments for the Anthrax field exercise, DeKalb county achieved the highest throughput among all counties that simultaneously conducted the same scale of Anthrax exercise at various locations, with labor usage at or below the other counties. Indeed, DeKalb exceeded the targeted number of households, and it processed 50% more individuals compared to the second place county. None of the other counties achieved the targeted number of households. The external evaluators commented that DeKalb produced the most efficient floor plan (with no path crossing), the most cost-effective dispensing (lowest labor/throughput value), and the smoothest operations (shortest average wait time, average queue length, equalized utilization rate). The study proves that even without historical data, using our system one can plan ahead and be able to wisely estimate the required labor resources.The exercise also revealed many areas that need attention during the operations planning and design of dispensing centers. The type of disaster being confronted (e.g., biological attack, infectious disease outbreak, or a natural disaster) also dictates different design considerations with respect to the dispensing clinic, facility locations, dispensing and backup strategies, and level of security pro...