ISEE-423 Introduction: Some neurologic diseases such as Amyotrophic Lateral Sclerosis (ALS) and Multiple Sclerosis (MS) are thought to be caused by a complex interplay of environmental, genetic, and autoimmune determinants. Additionally, the mortality incidence of ALS and MS incidence has risen over time. As such, these conditions are of special interest to the environmental public health tracking network (EPHTN), and the public. As a prelude to environmental exposure and hazard linkage, we studied the space-time distribution and potential clustering of ALS and MS mortality and hospitalization in Wisconsin. Space-time clustering, denoting areas and periods of increased or decreased incidence, could suggest populations, regions, exposure periods, and potential environmental risk factors for enhanced tracking scrutiny as the EPHTN is fully deployed. Methods: ALS and MS deaths were selected (underlying cause) from the 1990-2001 death files; hospitalizations from 1990-2002 (principal diagnosis) using ICD9 and 10 codes. Cases were arrayed by age, gender, and county. Rates were constructed using annual county, age, and gender specific census estimates. SaTScanTM software was used to analyze space-time point data using the scan statistic, testing whether these conditions were randomly distributed over space and time. An age adjusted Poisson-based model was used; separate models were constructed for males, females, and genders combined. Results: There were a total of 1,361 ALS deaths (2.2/100,000), and 2,123 hospitalizations (3.1/100,000), while there were 1,176 MS deaths (1.9/100,000) and 24,015 MS hospitalizations (35.5/100,000). With combined genders, an ALS cluster consisting of a four county mortality deficit was detected, but not significant (p>0.05). A single county cluster excess (RR=1.8, ns, p>0.05) was similarly found. ALS hospitalizations significantly clustered in a four county region (RR=1.8, p=0.001), while another four county area was significantly low (RR=0.4, p<0.01). The MS mortality analysis revealed a non-significant 3 county elevation (RR=1.4, p>0.05) as well as two single counties, one with an elevation, the other with a deficit risk (both not significant). However MS hospitalizations found a total of 19 significant clusters (p<0.05), three clusters with elevations and 16 cluster regions of decreased risk. Discussion: A Poisson space-time scan statistical analysis of ALS and MS revealed a number of regional disease clusters, consisting of both rate elevations and deficits. These findings will be used to inform exposure database modeling and follow back inquiry for the full implementation of Wisconsin’s Environmental Public Health Tracking Network.
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