Displaying results 1 - 8 of 14
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A Novel, Context-Sensitive Approach to Anonymizing Spatial Surveillance Data: Impact on Outbreak Detection
Content Type: Abstract
The use of spatially-based methods and algorithms in epidemiology and surveillance presents privacy challenges for researchers and public health agencies. We describe a novel method for anonymizing individuals in public health datasets, by… read more -
A Visual Analytics Toolkit for Evaluating Potential Syndromic Outbreaks
Content Type: Abstract
Our toolkit adds statistical trend analysis, interactive plots, and kernel density estimation to an existing spatio-temporal visualization platform. The goal of these tools is to provide both a quick assessment of the current… read more -
Enhancing Syndromic Surveillance through Cross-border Data Sharing
Content Type: Abstract
In the fall of 2006, the Ohio Department of Health (ODH) and the Indiana State Department of Health (ISDH) proactively began general discussions regarding surveillance issues of mutual interest. Both states, having operational… read more -
Evaluating the Performance of a Spatial Scan Statistic Using Simulated Outbreak Characteristics
Content Type: Abstract
Research evaluating the use of spatial data for surveillance purposes is ongoing and evolving. As spatial methods evolve, it is important to characterize their effectiveness in real-world settings. Assessing the performance of… read more -
Collaborative development of use cases for geospatially enabling a health information exchange
Content Type: Abstract
Given the clear relationship between spatial contexts and health, the Indiana Center of Excellence in Public Health Informatics (ICEPHI) aims to serve both the needs of public health researchers and practitioners by… read more -
The Day-of-the-Week Effect: A Study Across the Indiana Public Health Emergency Surveillance System
Content Type: Abstract
Complex, highly parameterized data models are often used to detect syndromic outbreaks. Unfortunately, such models can pose greater maintenance challenges as parameter variations increase. As such, our work focuses on whether day… read more -
Using Open-Source Grid-Computing Technology to Improve Processing Time for Geospatial Syndromic Surveillance Data
Content Type: Abstract
Outbreak detection algorithms for syndromic surveillance data are becoming increasingly complex. Initial algorithms focused on temporal data but newer methods incorporate geospatial dimensions. As methods evolve, it is important to understand the… read more -
An Evaluation of Electronic Laboratory Data Quality and a Health Information Exchange
Content Type: Abstract
Electronic laboratory reporting (ELR) was demonstrated just over a decade ago to be an effective method to improve the timeliness of reporting as well as the number of reports submitted to public health agencies. The quality of data (inc.… read more