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Biosurveillance in resource-limited settings is essential because of both enhanced risk of diseases rarely seen elsewhere (e.g. cholera) and pandemic threats (e.g. avian influenza). However, access to care and laboratory test capability are typically inadequate in such areas, amplifying the... Read more

Content type: Abstract

The Veterans Health Administration (VHA) operates over 880 outpatient clinics across the nation. The Johns Hopkins Applied Physics Laboratory’s Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE) utilizes VHA ICD9 coded outpatient visit data for the... Read more

Content type: Abstract

The new 2005 International Health Regulations (IHR), a legally binding instrument for all 194 WHO member countries, significantly expanded the scope of reportable conditions and are intended to help prevent and respond to global public health threats. SAGES aims to improve local public health... Read more

Content type: Abstract

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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 specific discriminants: (1) the rapid development of disease... Read more

Content type: Abstract

Automated disease surveillance systems that analyze data by syndrome categories have been used to look for outbreaks of disease for about 10 years. Most of these systems notify users of increases in the prevalence of reports in syndrome categories and allow users to view patient level data... Read more

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Recent events have focused on the role of emerging and re-emerging diseases not only as a significant public health threat but also as a serious threat to the economy and security of nations. The lead time to detect and contain a novel emerging disease or events with public health importance has... Read more

Content type: Abstract

In order to be best prepared to identify health events using electronic disease surveillance systems, it is vital for users to participate in regular exercises that realistically simulate how events may present in their system following disease manifestation in the community. Furthermore, it is... Read more

Content type: Abstract

Recently published studies evaluate statistical alerting methods for disease surveillance based on detection of modeled signals in a data background of either authentic historical data or randomized samples. Differences in regional and jurisdictional data, collection and filtering methods,... Read more

Content type: Abstract

We evaluated several classifications of emergency department (ED) syndromic data to ascertain best syndrome classifications for ILI.

Content type: Abstract

More than a decade ago, in collaboration with the U.S. Department of Defense, the Johns Hopkins University Applied Physics Laboratory (JHU/APL) developed the Electronic Surveillance System for the Early Notification of Community-based Epidemics (Enterprise ESSENCE), which is currently used by ... Read more

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