A Statistical Approach for Estimating Casualty Rates During Combat Operations
Technical rept. May-Dec 2013
NAVAL HEALTH RESEARCH CENTER SAN DIEGO CA
Pagination or Media Count:
Estimating casualties during military operations is critical in planning the medical response to military operations. Casualty occurrence variability poses challenges since the range of casualties can be as few as 1 to as high as 50 per day, as evidenced during the second battle of Fallujah. In this paper, random variables from lognormal, exponential, gamma, and Weibull distributions were generated and compared with the actual distribution of the casualty rates evidenced from selected combat units who saw recent combat in Afghanistan and Iraq. We found that wounded-in-action WIA casualty rates can be modeled using an exponential or a gamma distribution across four representative combat phases from Afghanistan and Iraq. We also found that the WIA casualty counts can be simulated using a Poisson mixture model, where the mixing distribution of the Poisson rate is the WIA casualty rate distribution. Statistical chi-square goodness-of-fit tests were used to select the fitted WIA casualty rate probability distributions for the combat phases. The proposed casualty rate distributions were validated by the close correspondence of the Poisson mixture model simulated casualty counts to the actual casualty counts. This paper defines a new approach to WIA casualty rate determination, contrasts that approach with past research, and provides insight into the approach s assumptions and limitations, as well as the importance of casualty rate estimation.
- Weapons Effects (Biological)
- Statistics and Probability
- Military Operations, Strategy and Tactics