Displaying results 105 - 112 of 2343
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A Novel Approach to Using Chief Complaint-Driven Syndromic Surveillance: Use of CDC's EARS-X by Hospital Infection Control Practitioners
Content Type: Abstract
Syndromic surveillance has traditionally been used by public health to supplement mandatory disease reporting. The use of chief complaints as a data source is common for early event detection. Though some public health syndromic surveillance systems… read more -
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 Pilot Study of Aberration Detection Algorithms with Simulated Data
Content Type: Abstract
To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data. read more -
A Robust Expectation-Based Spatial Scan Statistic
Content Type: Abstract
This paper describes a new expectation-based scan statistic that is robust to outliers (individual anomalies at the store level that are not indicative of outbreaks). We apply this method to prospective monitoring of over-the-counter (OTC) drug… read more -
A Scan Statistic Based on Anscombe's Variance Stabilization Transformation
Content Type: Abstract
This paper proposes a new scan statistic which detects disease clusters more accurately than that based on the likelihood ratio. -
A Simple Method of Using Linked Health Data in Syndromic Surveillance
Content Type: Abstract
This paper describes a simple technique for utilizing linked health information in syndromic surveillance. Using knowledge of which patient encounters resulted in laboratory test requests and prescriptions may improve sensitivity and specificity of… read more -
A Space Time Permutation Scan Statistic with Irregular Shape for Disease Outbreak Detection
Content Type: Abstract
This paper describes a methodology for detecting irregular space-time cluster using the space time permutation scan statistic. The methodology includes sequential Monte Carlo simulation and distribution approximation to estimate the error type I. -
A Spatial Scan Statistic Scanning Only the Regions with Elevated Risk
Content Type: Abstract
To propose a new spatial scan statistic that has higher ability of pinpointing the true cluster.