Wavelet-Based Monitoring for Biosurveillance

Wavelet-Based Monitoring for Biosurveillance

Biosurveillance, focused on the early detection of disease outbreaks, relies on classical statistical control charts for detecting disease outbreaks. However, such methods are not always suitable in this context. Assumptions of normality, independence and stationarity are typically violated in syndromic data. Furthermore, outbreak signatures are typically of unknown patterns and, therefore, cal...

Wavelet-based Monitoring for Modern Biosurveillance

Current biosurveillance relies on classical statistical control charts for detecting disease outbreaks. However, these are not always suitable in this context. Assumptions of normality, independence, and stationarity are typically violated in syndromic data. Furthermore, outbreak signatures in such data are of unknown patterns, and therefore call for “general detectors”. We propose wavelet-base...

Statistical Selection and Wavelet - Based Profile Monitoring

A robust wavelet based profile monitoring and change point detection using S-estimator and clustering

Some quality characteristics are well defined when treated as response variables and are related to some independent variables. This relationship is called a profile. Parametric models, such as linear models, may be used to model profiles. However, in practical applications due to the complexity of many processes it is not usually possible to model a process using parametric models.In these cas...

The Global Biosurveillance Portal: Biosurveillance for the Department of Defense

Introduction The 2012 National Strategy for Biosurveillance1 calls for improved integration, synchronization, and coordination of national biosurveillance activities and acknowledges the benefits of collective knowledge through sharing and receiving of biosurveillance information via strengthened partnerships amongst international, federal, state, local, tribal, territorial, private sector, non...