Development of composite indices and a regional assessment framework for analyzing nation-state health

In support of efforts to predict nation-states’ health, this paper develops a methodology that addresses incorporating disparate data from a variety of sources and utilizing both subject matter expertise and mathematical insights to effectively choose variables to use in a predictive model. The developed model can then capture the interrelatedness and complexities reflective of an actual operational environment. When selecting the indicators to be included in the composite indices, it is critical to evaluate the correlation that exists (or does not exist) between indices. If significant correlation is found, it could result in “double-counting” one or more variables, meaning bias exists in the analysis. Once the indicators have been selected and composite indices formed, in order to effectively evaluate a country’s health, we have developed a regional assessment framework and provided an example risk assessment based on the country of Syria. The results of this research provide a robust analysis approach to understanding and, ultimately, assessing a nation-state’s health. While the initial steps rely heavily on subject matter expert input for identification of indicators for each Political, Military, Economic, Social, Information index, once a solid list of indicators has been selected and weighted, future analysis can be readily conducted following the Region Mean Assessment Framework plan.