Welcome to the Surveillance Knowledge Repository

Click on a topic under the Key Topic Areas section in the left column, then select a resource  from the list of resources that appear for that topic. You may also search for specific topics by entering one or more keywords in the Search bar. You can filter the search results by Content Type, Year, or Author Name.


Key Topic Areas

Author Name


Reset filters

Approximately one quarter of people treated for tuberculosis (TB) have no supporting microbiology, and thus are not detectable through laboratory reporting systems. Health departments depend upon clinicians to report these cases, but there is important underreporting. We previously described the... Read more

Content type: Abstract

The Maryland Department of Health and Mental Hygiene conducts enhanced surveillance using the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE). The current version of ESSENCE for the National Capital Region consists of information from multiple data... Read more

Content type: Abstract

During influenza season, the Boston Public Health Commission uses syndromic surveillance to monitor Emergency Department visits for chief complaints indicative of influenza-like illness (ILI). We created three syndrome definitions for ILI to capture variable presentations of disease, and... Read more

Content type: Abstract


A “whole-system facsimile” recreates a complex automated biosurveillance system running prospectively on real historical datasets. We systematized this approach to compare the performance of otherwise identical surveillance systems that used alternative statistical outbreak... Read more

Content type: Abstract

The New York City (NYC) Department of Health and Mental Hygiene monitors visits daily from 49 of 54 NYC emergency departments (EDs), capturing 95% of all ED visits. ED visits for influenza-like illness (ILI) have reflected influenza activity in NYC, better than the more broadly defined fever/flu... Read more

Content type: Abstract

The statistical process control (SPC) community has developed a wealth of robust, sensitive monitoring methods in the form of control charts [1]. Although such charts have been implemented for a wide variety of health monitoring purposes [2], some implementations monitor data that violate basic... Read more

Content type: Abstract

SaTScan is a freely available software that uses the scan statistic to detect clusters in space, time or space-time. SaTScan uses Monte Carlo hypothesis testing in order to produce a p-value for the null hypothesis that no clusters are present. Monte Carlo hypothesis testing can be a powerful... Read more

Content type: Abstract

Bordetella Pertussis outbreaks cause morbidity in all age groups, but the infection is most dangerous for young infants. Pertussis is difficult to diagnose, especially in its early stages, and definitive test results are not available for several days. Because of temporal and geographic... Read more

Content type: Abstract

Outbreak detection algorithms for syndromic surveillance data are becoming increasingly complex. Initial algorithms focused on temporal data but newer methods incorporate geospatial dimensions. As methods evolve, it is important to understand the effects on detection of both algorithm parameters... Read more

Content type: Abstract

http://Google.org developed a regression model that used the volume of influenza-related search queries best correlated with the proportion of outpatient visits related to influenza-like illness (ILI) model to estimate the level of ILI activity. For calibration, the model used ILINet data from... Read more

Content type: Abstract


Didn't find what you're looking for? Then try searching our archives.

Contact Us

NSSP Community of Practice

Email: syndromic@cste.org


This website is supported by Cooperative Agreement # 6NU38OT000297-02-01 Strengthening Public Health Systems and Services through National Partnerships to Improve and Protect the Nation's Health between the Centers for Disease Control and Prevention (CDC) and the Council of State and Territorial Epidemiologists. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC. CDC is not responsible for Section 508 compliance (accessibility) on private websites.

Site created by Fusani Applications