NDLI: Simulation of casualty sustainment during naval combat operations

Content Provider	IEEE Xplore Digital Library
Author	Blood, C.G. Odowick, M.S. Marks, J.S.
Copyright Year	1996
Description	Author affiliation: Naval Health Research Center (Blood, C.G.)
Abstract	Accurate forecasts of the casualties likely to be sustained during naval warfare allow sufficient resources to be programmed to meet the medical demands of the operation while at the same time minimizing resource overallocation. A simulation tool called the shipboard casualty projection system (SHIPCAS) has recently been developed to assist planners in medical resource programming. SHIPCAS is a forecasting tool that projects WIA (wounded-in-action), KIA (killed-in action), and DNBI (disease and non-battle injuries) incidence among naval surface forces. By simulating ship strikes during naval operations, SHIPCAS provides medical planners with the injury and illness estimates required to assist in determining the needed medical resources. The SHIPCAS system models casualties afloat by allowing the user to define a specific scenario in terms of task force composition, expected battle intensity, and length of operation. The model then produces graphical and tabular information detailing the total number of casualties across the operation, the daily average number of casualties, the maximum daily number of casualties, and the casualty rates per 1000 strength per day. In addition to projecting the number of ships hit and the resulting casualties, SHIPCAS also provides estimates of the temporal points in the operation during which ship strikes are most likely.
Starting Page	912
Ending Page	917
File Size	422273
Page Count	6
File Format	PDF
ISBN	0780333837
DOI	10.1109/WSC.1996.873384
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1996-12-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Winter Simulation Conf. Board of Dir.
Subject Keyword	Marine vehicles Blood Computational modeling Injuries Demand forecasting Medical simulation Medical treatment Diseases Data mining Frequency
Content Type	Text
Resource Type	Article

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