Introduction The federal meaningful use initiative is a major driver to the establishment of expanded electronic syndromic surveillance capacity across the United States. Much has been documented about the background and requirements for eligible hospitals to achieve the syndromic meaningful use objectives. However, the role and efforts by public health agencies in the syndromic onboarding proc...

1. Sichel LS, Greenko J, Heffernan R, Weiss D. Field investigations of emergency department syndromic surveillance signals, New York City. Presentation at the 2003 National Syndromic Surveillance Conference [cited 2004 Jan]. Available from: http://www.syndromic.org/pdf/con2LS-8b.pdf 2. Sosin DM. Syndromic surveillance: the case for skillful investment. Biosecur Bioterror. 2003;1:247–53. 3. Cent...

Introduction Veterinary syndromic surveillance (VSS) is a fast growing field, but development has been limited by the limited use of standards in recording animal health events and thus their categorization into syndromes. The adoption of syndromic classification standards would allow comparability of outputs from systems using a variety of animal health data sources (clinical data, laboratory ...

Our objective was to study the ability of a syndromic surveillance system to identify spatio-temporal clusters of drops in the number of calvings among beef cows during the Bluetongue epizootic of 2007 and 2008, based on calving seasons. France was partitioned into 300 iso-populated units, i.e. units with quite the same number of beef cattle. Only 1% of clusters were unlikely to be related to B...

BACKGROUND Although syndromic surveillance is increasingly used to detect unusual illness, there is a debate whether it is useful for detecting local outbreaks. We evaluated whether syndromic surveillance detects local outbreaks of lower-respiratory infections (LRIs) without swamping true signals by false alarms. METHODS AND FINDINGS Using retrospective hospitalization data, we simulated pros...

Although syndromic surveillance systems using nonclinical data have been implemented in the United States, the approach has yet to be tested in France. We present the results of the first model based on drug sales that detects the onset of influenza season and forecasts its trend. Using weekly lagged sales of a selected set of medications, we forecast influenzalike illness (ILI) incidence at th...

Syndromic surveillance has, so far, considered only simple models for Bayesian inference. This paper details the methodology for a serious, scalable solution to the problem of combining symptom data from a network of U.S. hospitals for early detection of disease outbreaks. The approach requires high-end Bayesian modeling and significant computation, but the strategy described in this paper appe...