A Space-Time Permutation Scan Statistic for Evaluating County-Level Tickborne Disease Clusters in Indiana, 2009-2016.

Abstract

The purpose of this study was to identify age group, gender, rural-urban differences, and spatiotemporal clusters of tickborne disease diagnoses in Indiana. We analyzed retrospective surveillance data for Lyme disease, ehrlichiosis, Rocky Mountain spotted fever, typhus/rickettsial diseases, and tularemia diagnosed in Indiana from 2009 to 2016. We used chi-square cross tabulation to test gender, age group, and county classification (rural, rural-mixed, urban) differences in tickborne disease. We used the Kruskal-Wallis test with a post hoc Conover test to identify differences in summated tickborne disease by county classification. Finally, we used retrospective space-time permutation models in SaTScan to test the hypothesis of complete spatiotemporal randomness of tickborne disease. We found more Lyme disease diagnoses among Indiana residents 44 years of age or younger compared with those over 44 years. Conversely, more ehrlichiosis, Rocky Mountain spotted fever, and tularemia were reported in Indiana residents aged over 44 years of age. An analysis of summated tickborne disease by county showed significantly higher diagnosis reported in urban counties, compared with rural and rural-mixed counties. Finally, 2 significant clusters of summated tickborne disease were observed in south-central Indiana in 2014 and in western Indiana from 2010 to 2011. The detection of tickborne disease clusters, coupled with the finding that significant differences exist in the diagnosis of tickborne diseases between urban, rural, and rural-mixed counties in Indiana, suggests a need for continued surveillance of the counties observed within these clusters.