• Daniel A Dworkis, James Marvel, Nerses Sanossian, and Sanjay Arora.
• Department of Emergency Medicine, Keck School of Medicine of USC, Los Angeles, CA, United States of America; The Lever Institute, Los Angeles, CA, United States of America. Electronic address: dworkis@usc.edu.
• Am J Emerg Med. 2020 Apr 1; 38 (4): 794-798.

ObjectiveIdentifying communities at high risk of stroke is an important step in improving systems of stroke care. Stroke is known to show spatial clustering at the state and county levels, but it is not known if clusters are present within city boundaries.MethodsWe performed a geospatial analysis of the prevalence of stroke within 500 major cities in the United States using the Centers for Disease Control and Prevention 500 Cities Project. For each city, we calculated the Moran's I statistic, which looks for evidence of spatial clustering, and used Monte Carlo simulation to assess for clustering significance.ResultsThe mean overall crude prevalence of self-reported history of stroke at the city level was 2.8% (IQR 2.4-3.2%). Monte Carlo simulations of spatial patterns of stroke were successfully performed for 497 cities, of which 136 (27.3%) showed significant spatial clustering at the neighborhood level. All nine cities with more than one million inhabitants in 2010 showed significant spatial clustering.ConclusionsThis is the first study to demonstrate that stroke shows clustering at the neighborhood level within many major cities in the United States and within all of the largest cities. Understanding where stroke clusters exist within cities can form the basis of optimizing emergency medical services deployment and improving systems of stroke care.Copyright © 2019 Elsevier Inc. All rights reserved.

19 keywords...

hide…