An Algorithm for Early Outbreak Detection in Multiple Data Streams

Current biosurveillance systems run multiple univariate statistical process control (SPC) charts to detect increases in multiple data streams. The method of using multiple univariate SPC charts is easy to implement and easy to interpret. By examining alarms from each control chart, it is easy to identify which data stream is causing the alarm. However, testing multiple data streams simultaneously can lead to multiple testing problems that inflate the combined false alarm probability.

June 18, 2019

Progress towards Companion Animal Zoonotic Disease Surveillance in the U.S. Army

Dogs, cats and other companion animals have played an integral role in many aspects of human life. Human and companion animal (CAs) interactions have a wide range of benefits to human health [1-3]. The threat of zoonotic transmission between CAs and humans is exacerbated by proximity (56% of dog owners and 62% of cat owners sleep with their animal next to them [4]) and the number of diseases CAs share with humans. Many of these highlighted zoonoses are spread by direct contact, and others are vector-transmitted (e.g., fleas, ticks, flies, and mosquitos).

June 18, 2019

Data Science, Analytics and Collaboration for a Biosurveillance Ecosystem

After the 2009 H1N1 pandemic, the Assistant Secretary of Defense for Nuclear, Chemical and Biological Defense indicated œbiodefense would include emerging infectious disease. In response, DTRA launched an initiative for an innovative, rapidly emerging capability to enable real-time biosurveillance for early warning and course of action analysis. Through competitive prototyping, DTRA selected Digital Infuzion to develop the platform and next generation analytics.

June 18, 2019

Biosurveillance study of Schmallenberg disease in Azerbaijan in 2012-2017

In 2012 - 2017 in Azerbaijan there was an unexpected increase of abortions in cattle and sheep that was unrelated to brucellosis or chlamydia infection. The first confirmed case of Schmallenberg disease was received from Beylagan district of Azerbaijan in October 2012. The import of cattle from Europe to Azerbaijan has commenced in 2012. Therefore, the surveillance study was launched to determine spread of infection among cattle and sheep and to monitor the situation in the country.

June 18, 2019

Machine Learning for Identifying Relevance to Biosurveillance in Multilingual Text

Global biosurveillance is an extremely important, yet challenging task. One form of global biosurveillance comes from harvesting open source online data (e.g. news, blogs, reports, RSS feeds). The information derived from this data can be used for timely detection and identification of biological threats all over the world. However, the more inclusive the data harvesting procedure is to ensure that all potentially relevant articles are collected, the more data that is irrelevant also gets harvested. This issue can become even more complex when the online data is in a non-native language.

January 25, 2018

NBIC Biofeeds: Deploying a New, Digital Tool for Open Source Biosurveillance across Federal Agencies

NBIC integrates, analyzes, and distributes key information about health and disease events to help ensure the nation’s responses are well-informed, save lives, and minimize economic impact. To meet its mission objectives, NBIC utilizes a variety of data sets, including open source information, to provide comprehensive coverage of biological events occurring across the globe. NBIC Biofeeds is a digital tool designed to improve the efficiency of analyzing large volumes of open source reporting and increase the number of relevant insights gleaned from this dataset.

January 25, 2018

Virtual Speed Networking with the Analytic Solutions Committee (ASC)

Presented January 11, 2018.

The purpose of the event was to stimulate and facilitate constructive communication and collaboration among analytic method developers and practitioners charged with routine public health surveillance, ranging from disease outbreak surveillance to chronic disease burden assessment and disaster response.

January 11, 2018

Epi Evident: Biosurveillance to Monitor, Compare, and Forecast Disease Case Counts

The Epi Evident application was designed for clear and comprehensive visualization for monitoring, comparing, and forecasting notifiable diseases simultaneously across chosen countries. Epi Evident addresses the taxing analytical evaluation of how diseases behave differently across countries. This application provides a user-friendly platform with easily interpretable analytics which allows analysts to conduct biosurveillance with minimal user tasks.

January 25, 2018

NBIC Collaboration at Multiple Jurisdictional Levels During the Zika Epidemic

NBIC is charged with enhancing the capability of the Federal Government to enable early warning and shared situational awareness of acute biological events to support better decisions through rapid identification, characterization, localization, and tracking. A key aspect of this mission is the requirement to integrate and collaborate with federal and, state, local, tribal, and territorial (SLTT) government agencies.

January 25, 2018

Syndromic Surveillance Analysis & Interpretation

Presented January 31, 2018

 

David Swenson presented the following slides during the 2018 ISDS Annual Conference in Orlando, Florida. This presentation provides a use case for developing and implementing surveillance prodocols to conduct public health monitoring, analyze data collected, and engage partners/leadership in follow-up procedures.

 

Presenter: David Swenson, AHEDD Project Manager, Infectious Disease Surveillance Section DPHS, DHHS, New Hampshire

January 26, 2019

Pages

Contact Us

NSSP Community of Practice

Email: syndromic@cste.org

 

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