Displaying results 1 - 4 of 4
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Bayesian Methods for Syndromic Surveillance
Content Type: Abstract
Syndromic surveillance needs to be (1) transparent, (2) actionable, and (3) flexible. Traditional frequentist approaches to syndromic surveillance, such as cusum charts and scan statistics, tend to fail on all three criteria. First, the validity of… read more -
A Spatio-Temporal Bayesian Model for Syndromic Surveillance: Properties and Model Performance
Content Type: Abstract
Syndromic surveillance uses syndrome (a specific collection of clinical symptoms) data that are monitored as indicators of a potential disease outbreak. Advanced surveillance systems have been implemented globally for early detection of infectious… read more -
A spatio-temporal absorbing state model for disease and syndromic surveillance
Content Type: Abstract
The goal of disease and syndromic surveillance is to monitor and detect aberrations in disease prevalence across space and time. Disease surveillance typically refers to the monitoring of confirmed cases of disease, whereas syndromic… read more -
Applications of Bayesian Statistics for Biosurveillance
Content Type: Webinar
For its January 2010 meeting, the ISDS Research Committee hosted a topical webinar on the "Applications of Bayesian Statistics for Biosurveillance," to address questions including:- How can I combine recent trends with historical data…