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 -
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 -
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 -
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