Displaying results 1 - 8 of 38
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Analytic Methodologies for Disease Surveillance Using Multiple Sources of Evidence
Content Type: Webinar
This presentation is for public health practitioners and methodology developers interested in using statistical methods to combine evidence from multiple data sources for increased sensitivity to disease outbreaks. Methods described will account for… 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 -
Automated Time Series Forecasting for Biosurveillance
Content Type: Abstract
The statistical process control (SPC) community has developed a wealth of robust, sensitive monitoring methods in the form of control charts [1]. Although such charts have been implemented for a wide variety of health monitoring purposes [2], some… read more -
Classification of Emergency Department Syndromic Data for Seasonal Influenza Surveillance
Content Type: Abstract
We evaluated several classifications of emergency department (ED) syndromic data to ascertain best syndrome classifications for ILI. -
Data-Adapted Temporal Alerting Algorithms for Routine Health Monitoring
Content Type: Abstract
This paper discusses selection of temporal alerting algorithms for syndromic surveillance to achieve reliable detection performance based on statistical properties and the epidemiological context of the input data. We used quantities calculated from… read more -
Data-Adaptive Multivariate Control Charts for Routine Health Monitoring
Content Type: Abstract
This paper investigates the use of data-adaptive multivariate statistical process control (MSPC) charts for outbreak detection using real-world syndromic data. The widely used EARS [1] methods and other adaptive implementations assume implicitly… read more -
Development and Evaluation of a Data-adaptive Algorithm for Univariate Temporal Biosurveillance Data
Content Type: Abstract
Numerous recent papers have evaluated algorithms for biosurveillance anomaly detection. Common essential problems in the disparate, evolving data environment include trends, day-of-week effects, and other systematic behavior.… read more -
Essential Requirements for Effective Advanced Disease Surveillance
Content Type: Abstract
Advanced surveillance systems require expertise from the fields of medicine, epidemiology, biostatistics, and information technology to develop a surveillance application that will automatically acquire, archive, process and present data to the user… read more