Displaying results 9 - 16 of 38
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Evaluation of Alerting Sparse-Data Streams of Population Healthcare-Seeking Data
Content Type: Abstract
Objective This presentation discusses the problem of detecting small-scale events in biosurveillance data that are relatively sparse in the sense that the median count of monitored time series values is zero. Research goals are to understand… read more -
Evaluation of Spatial Estimation Methods for Cluster Detection
Content Type: Abstract
CDC’s BioSense system provides near-real time situational awareness for public health monitoring through analysis of electronic health data. Determination of anomalous spatial and temporal disease clusters is a crucial part of… read more -
Hybrid Probabilistic Modeling and Automated Data Fusion for Biosurveillance Applications
Content Type: Abstract
The increased threat of bioterrorism and naturally occurring diseases, such as pandemic influenza, continually forces public health authorities to review methods for evaluating data and reports. The objective of bio-surveillance is to automatically… read more -
Minimizing False Alarms in Syndromic Surveillance
Content Type: Abstract
This paper describes a method of avoiding false alerts in automated syndromic surveillance algorithms which monitor the temporal relationship between a particular monitored syndrome (the ìtargetî) in relationship to other reference healthcare data… read more -
Modeling Disease Surveillance and Assessing its Effectiveness for Detection of Acute Respiratory Outbreaks in Resource-Limited Settings
Content Type: Abstract
A U.S. Department of Defense program is underway to assess health surveillance in resource-poor settings and to evaluate the Early Warning Outbreak Reporting System. This program has included several information-gathering trips,… read more -
Modifications to Spatial Scan Statistics for Estimated Probabilities at Fine-Resolution in Highly Skewed Spatial Distributions
Content Type: Abstract
Estimation of representative spatial probabilities and expected counts from baseline data can cause problems in applying spatial scan statistics when observed events are sparse in a large percentage of the spatial zones (e.g.,… read more -
Resolving the 'Boy Who Cried Wolf' Syndrome
Content Type: Abstract
To date, most syndromic surveillance systems rely heavily on complicated statistical algorithms to identify aberrations. The assumption is that when the statistics identify something unusual, follow-up should occur. However, with multiple strata… read more -
Performance Characteristics of Control Chart Detection Methods
Content Type: Abstract
To recognize outbreaks so that early interventions can be applied, BioSense uses a modification of the EARS C2 method, stratifying days used to calculate the expected value by weekend vs weekday, and including a rate-based method… read more