Spatial Clusters and Non-spatial Predictors of Tick-Borne Disease Diagnosis in Indiana

The purpose of this study was two-fold. First, we sought to identify spatial clusters of self-reported tick-borne disease (TBD) diagnosis in Indiana. Secondly, we determined the significant predictors of self-reported TBD diagnosis in a sample of Indiana residents. Study participants were selected from existing online panels maintained by Qualtrics and completed a cross-sectional survey (n = 3003). Our primary outcome of interest was self-reported TBD diagnosis (Yes/No). Cases and background population were aggregated to the county level. We used a purely spatial discrete Poisson model in SatScan (R) to determine significant clusters of high-risk TBD diagnosis counties. We also used X-2 tests in bivariate analyses, to identify potential predictor variables for inclusion in an initial model, and backward elimination selection method to identify the final model. Two clusters of counties with significant high relative risk of self-reported TBD diagnosis in the southeast and southwest of Indiana were detected. Males in Indiana were more likely to self-report TBD diagnosis compared to females. Study participants who conducted a thorough tick check after being outdoors were significantly less likely to report TBD diagnosis compared to those who did not. Increased positive perceptions of TBD personal protective measures were associated with reduced self-reported TBD diagnosis. Older study participants were less likely to self-report TBD diagnosis compared to younger participants. The identification of two clusters of TBD diagnosis in southern Indiana is consistent with a northern spread of TBDs and suggests a need for continued surveillance of the counties in the vicinity of the observed clusters. Future studies should be designed to identify risk factors for TBD diagnosis in the affected counties of Indiana.