On the Temporal Distribution of Casualties and Determination of Medical Logistical Requirements

TL;DR

This paper analyzes WWII casualty data, revealing multifractal properties and power-law distributions, which can be used to accurately estimate the likelihood of different casualty levels for medical logistics planning.

Contribution

It demonstrates that WWII casualty data exhibit multifractal structure and introduces a method to estimate casualty likelihoods using power-law tails, improving logistical planning accuracy.

Findings

Casualty data display multifractal statistical structure.

Power-law tails enable casualty level probability estimation.

Estimates align well with historical data.

Abstract

It is demonstrated that World War II casualty data display statistical structure that would be expected from multifractal data. Given that the data displayed these properties, it is shown how the existence of power-law tails in the exceedence probability distributions can be used to estimate the likelihood of various casualty levels. Estimates made using this method matched the historical data well.