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  • 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:
    1. How can I combine recent trends with historical data…
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    … ‘Disease surveillance using a hidden Markov model’ www.biomedcentral.com/1472-6947/9/39 Thank you …
  • 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
    … the prob- lems associated with alpha levels and multiple com- parisons, and make better use of prior information. The … Further Information: David Banks, banks@stat.duke.edu www.stat.duke.edu/~banks Advances in Disease Surveillance 2007;2:41 mailto:banks@stat.duke.edu http://www.stat.duke.edu/%7Ebanks Bayesian Methods for Syndromic …
  • 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
    … Heaton et al.; licensee Emerging Health Threats Journal. www.eht-journal.org 2828 …
  • 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
    … USA; 4National Center for Atmospheric Research, Boulder, CO, USA; 5University of Georgia, Athens, GA, USA; …