Comparative Cluster Analysis for Establishing the Etiology of Multiple Sclerosis
Track: Health and Human Services
Author(s): Megan Blewett
Multiple Sclerosis (MS) was first diagnosed some 600 years ago, though its etiology remains unknown. This paper extends previous correlation and multiple-regression work by employing comparative cluster analysis to investigate whether MS and related neuronal demyelinating diseases, as well as certain cancers, share a common vector. If this were true, we would expect three main results: clusters of the diseases exist, the clusters co-occur, and the clusters co-occur with the same key environmental factors. The first hypothesis is tested using Moran's Index, General G, and Gi*. To examine the second hypothesis, SaTSCAN is used to quantify the degree of overlap between MS and other distributions. The K-function and standard deviational ellipse tools provided in the ArcGIS software are also employed. To investigate the third hypothesis, MS and other distributions are compared to environmental factors, including seabird density, tick density, and the primary land use statistic.
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