ArticleJournal of community health2019
Spatial Clusters and Non-spatial Predictors of Tick-Borne Disease Diagnosis in Indiana.
Article in Journal of community health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- Article
- Assessing Tick-Borne Disease Risk and Surveillance: Toward a Multi-Modal Approach to Diagnostic Positioning and Prediction.Microorganisms · 2022Article
- A spatiotemporal data mining study to identify high-risk neighborhoods for out-of-hospital cardiac arrest (OHCA) incidents.Scientific reports · 2022Article
- Tick-Borne Surveillance Patterns in Perceived Non-Endemic Geographic Areas: Human Tick Encounters and Disease Outcomes.Healthcare (Basel, Switzerland) · 2021Article
- Tick trails: the role of online recreational trail reviews in identifying risk factors and behavioral recommendations associated with tick encounters in Indiana.BMC public health · 2021Article
- Predictors of Tick Exposure Risk-Reduction Behavior in Indiana.Journal of community health · 2020Article
- Spatio-Temporal Dynamics of Tick-Borne Diseases in North-Central Wisconsin from 2000-2016.International journal of environmental research and public health · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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® to determine significant clusters of high-risk TBD diagnosis counties. We also used X
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.