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首页> 外文期刊>Journal of community health >Spatial Clusters and Non-spatial Predictors of Tick-Borne Disease Diagnosis in Indiana
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Spatial Clusters and Non-spatial Predictors of Tick-Borne Disease Diagnosis in Indiana

机译:印第安纳蜱传播疾病诊断的空间簇与非空间预测因子

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摘要

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.
机译:本研究的目的是两倍。首先,我们试图识别印第安纳州自我报告的蜱型疾病(TBD)诊断的空间簇。其次,我们确定了印第安纳州居民样本中自我报告的TBD诊断的重要预测因子。学习参与者被选中由高音乐维护的现有在线面板,并完成了横断面调查(n = 3003)。我们兴趣的主要结果是自我报告的TBD诊断(是/否)。案件和背景群体汇总到县级。我们在Satscan(R)中使用了纯粹的空间离散泊松模型,以确定高风险的TBD诊断县的重要集群。我们还在双变量分析中使用了X-2测试,以识别潜在的预测变量以包含在初始模型中,并向后消除选择方法识别最终模型。检测到南南部和印第安纳州西南部的自我报告的TBD诊断具有显着高相对风险的两种县。与女性相比,印第安纳州的男性更有可能自我报告的TBD诊断。在户外进行彻底蜱检查的学习参与者显着不太可能向没有的人报告TBD诊断。提高对TBD个人保护措施的积极看法与减少的自我报告的TBD诊断有关。与年轻参与者相比,较旧的研究参与者不太可能自我报告的TBD诊断。印第安纳州南部两株TBD诊断的鉴定与TBDS的北方传播一致,并建议需要继续监测观察到的簇附近。未来的研究应旨在识别印第安纳州受影响县的TBD诊断的危险因素。

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