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Presented November 29, 2017.

During this 60-minute session, Aaron Kite-Powell, M.S., from CDC and Wayne Loschen, M.S., from JHU-APL provide an overview of tips and tricks in ESSENCE to make it more useful for members and also answer questions regarding ESSENCE functions, capabilities and... Read more

Content type: Webinar

What is R?

R is a language and free software environment for statistical computing and graphics. It compiles and runs on a variety of UNIX platforms, Windows, and MacOS. It is similar to the S language and environment - in fact, much code written in S will run unaltered in R. The R... Read more

Content type: Surveillance Tools and Systems

NOTE: The video requires running Flash and works best on Mozilla Firefox. If you are using Google Chrome or another internet browser, please be aware that the video may not load properly.

The online training course will help novice and intermediate ESSENCE users learn how to perform... Read more

Content type: Training
Objective: To monitor clinical encounters for gonorrhea infection and disease Syndromic surveillance system: ESSENCE Data Sources: Emergency department visits, primary and urgent care visits  Fields used to query the data: Chief Complaint History, Discharge Diagnosis
Content type: Syndrome
Objective: To monitor clinical encounters for chlamydia infection and disease Syndromic surveillance system: ESSENCE Data Sources: Emergency department visits, primary and urgent care visits  Fields used to query the data: Chief Complaint History, Discharge Diagnosis

 

Content type: Syndrome

KDHE has updated the exhisting CO Poisoning Surveillance queries. Version 1 can be found here https://www.surveillancerepository.org/carbon-monoxide-exposure-kansas-d...

Previously, we were querying for carbon monoxide-related cases by using the NSSP ESSENCE SubSyndrome for COPoisoning... Read more

Content type: Syndrome

The space-time scan statistic is a powerful statistical tool for prospective disease surveillance. It searches over a set of spatio-temporal regions (each representing some spatial area S for the last k days), finding the most significant regions (S, k) by maximizing a likelihood ratio statistic... Read more

Content type: Abstract

A comprehensive definition of a syndrome is composed of direct (911 calls, emergency departments, primary care providers, sensor, veterinary, agricultural and animal data) and indirect evidence (data from schools, drug stores, weather etc.). Syndromic surveillance will benefit from quickly... Read more

Content type: Abstract

There is limited closed-form statistical theory to indicate how well the prospective space-time permutation scan statistic will perform in the detection of localized excess illness activity. Instead, detection methods can be applied to simulated data to gain insight about detection performance.... Read more

Content type: Abstract

Expectation-based scan statistics extend the traditional spatial scan statistic approach by using historical data to infer the expected counts for each spatial location, then detecting regions with higher than expected counts. Here we consider five recently proposed expectation-based statistics... Read more

Content type: Abstract

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INTERNATIONAL SOCIETY FOR
DISEASE SURVEILLANCE

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Email:syndromic@syndromic.org

This Knowledge Repository is made possible through the activities of the Centers for Disease Control and Prevention Cooperative Agreement/Grant #1 NU500E000098-01, National Surveillance Program Community of Practice (NSSP-CoP): Strengthening Health Surveillance Capabilities Nationwide, which is in the interest of public health.

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