Displaying results 1 - 8 of 9
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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 -
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 -
Implementation and Comparison of Preprocessing Methods for Biosurveillance Data
Content Type: Abstract
Modern biosurveillance relies on multiple sources of both prediagnostic and diagnostic data, updated daily, to discover disease outbreaks. Intrinsic to this effort are two assumptions: (1) the data being analyzed contain early indicators… read more -
Preparing Biosurveillance Data for Classic Monitoring
Content Type: Abstract
Modern surveillance systems use statistical process control (SPC) charts such as Cumulative Sum and Exponentially Weighted Moving Average charts for monitoring daily counts of such quantities as ICD-9 codes from ED visits,… 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 -
Increase in Pneumonia Cases as an Early Indicator of Severe and Pandemic Influenza Outbreak
Content Type: Abstract
Objective To enable the early detection of pandemic influenza, we have designed a system to differentiate between severe and mild influenza outbreaks. Historic information about previous pandemics suggested the evaluation of two… read more