Displaying results 1 - 8 of 15
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A Comparison of Ambulatory Care and Emergency Department Encounters as Data Sources for Detection of Clusters of Lower Gastrointestinal Illness
Content Type: Abstract
We sought to compare ambulatory care (AC) and emergency department (ED) data for the detection of clusters of lower gastrointestinal illness, using AC and ED data and AC+ED data combined, from two geographically separate health plans participating… read more -
Empirical/Asymptotic P-Values for Monte Carlo-Based Hypothesis Testing: An Application to Cluster Detection Using the Scan Statistic
Content Type: Abstract
SaTScan is a freely available software that uses the scan statistic to detect clusters in space, time or space-time. SaTScan uses Monte Carlo hypothesis testing in order to produce a p-value for the null hypothesis that no… read more -
Clustering under the Null: One Reason for Too Many Signals
Content Type: Abstract
I examine the nature and expression of the null hypothesis often used in spatial surveillance. I also show an example of how incorrect specification of the null can lead to excess signals without interesting outbreaks, and argue that this may be a… read more -
Comparing the Utility of Ambulatory Care and Emergency Room Data for Disease Outbreak Detection
Content Type: Abstract
To compare the ability to detect disease outbreaks of separate and combined data streams from ambulatory care and emergency department from Harvard Pilgrim Health Care. -
An Empirical Study of the Effect of Sentinel Sample Size in Syndromic Surveillance Using a Space-Time Permutation Method
Content Type: Abstract
Our goal was to assess the impact of sentinel sample size and criteria for a signal on performance of daily prospective space-time permutation detection by comparing results in varying size random samples from a large health plan to results found in… read more -
Evaluating Outbreak-Detection Methods Using Simulations: Volume Under the Time-ROC Surface
Content Type: Abstract
There are many proposed methods of identifying outbreaks of disease in surveillance data. However, there is little agreement about appropriate ways to choose amongst them. One common basis for comparison is simulating outbreaks and adding the simu… read more -
in silico Surveillance: Using Detailed Computer Simulations to Develop and Evaluate Outbreak Detection
Content Type: Abstract
Developing and evaluating outbreak detection is challenging for many reasons. A central difficulty is that the data the detection algorithms are “trained” on are often relatively short historical samples and thus do not represent the full… read more -
Multi-Method Comparison of Detecting Common Events of Public Health Interest: a Multi-Site, Multi-Stream Simulation Study
Content Type: Abstract
Existing statistical methods can perform well in detecting simulated bioterrorism events. However, these methods have not been well-evaluated for detection of the type of respiratory and gastrointestinal events of greatest… read more