What value can Google search data add to existing syndromic surveillance systems?

Globally, there have been various studies assessing trends in Google search terms in the context of public health surveillance1. However, there has been a predominant focus on individual health outcomes such as influenza, with limited evidence on the added value and practical impact on public health action for a range of diseases and conditions routinely monitored by existing surveillance programmes. A proposed advantage is improved timeliness relative to established surveillance systems.

January 25, 2018

Spatial temporal cluster analysis to enhance awareness of disease re-emergence on a global scale

The re-emergence of an infectious disease is dependent on social, political, behavioral, and disease-specific factors. Global disease surveillance is a requisite of early detection that facilitates coordinated interventions to these events. Novel informatics tools developed from publicly available data are constantly evolving with the incorporation of new data streams. Re-emerging Infectious Disease (RED) Alert is an open-source tool designed to help analysts develop a contextual framework when planning for future events, given what has occurred in the past.

January 25, 2018

Experience of GIS Technology Application in the Surveillance of Tick-Borne Infections

The epidemiological situation of natural foci of tick-borne infections (TBI) in Ukraine, as well as globally, is characterized by significant activation of processes due to global climate change, growing human-induced factor and shortcomings in the organization and running of epidemiological surveillance. For the Western region of Ukraine, among all tick-borne zoonoses the most important are tick-borne viral encephalitis (TBVE), Lyme disease (LD), human granulocytic anaplasmosis (HGA) and some others.

January 25, 2018

Nonparametric Models for Identifying Gaps in Message Feeds

Timely and accurate syndromic surveillance depends on continuous data feeds from healthcare facilities. Typical outlier detection methodologies in syndromic surveillance compare predictions of counts for an interval to observed event counts, either to detect increases in volume associated with public health incidents or decreases in volume associated with compromised data transmission.

January 25, 2018

Now Trending in Your Community: Social Media Insights For Your Public Health Mission

In today’s fast paced world, information is available (and expected) instantaneously. Social media has only fueled this expectation as it has permeated all aspects of our lives. More and more of the population is turning to social media outlets to share their thoughts and update their status, especially during disasters. With all these conversations occurring, it is only reasonable to assume that health status is part of the information being shared.

November 22, 2017

Executive Summary of the ISDS DTRA Consultancy Project 2014-2017

The International Society for Disease Surveillance (ISDS) fills the need for a practical forum and coordinating mechanism for collaboration among subject matter experts (SMEs) from stakeholder groups that may normally not interact but who, when brought together, enable innovative approaches to problems and solutions that are not possible by any one group alone. The objective of the Analytic Solutions for Real-Time Biosurveillance project was to advance a

April 18, 2017

Negation Processing in Free Text Emergency Department Data for Public Health Surveillance

Materials associated with the Analytic Solutions for Real-Time Biosurveillance: Negation Processing in Free Text Emergency Department Data for Public Health Surveillance consultancy held January 19-20, 2017 at the University of Utah, Salt Lake City.

Problem Summary

False positive syndrome hits are created when a syndromic classification process cannot properly identify negated terms. For example, a visit is classified into a fever syndrome when the chief complaint or triage note says “denies fever.”

March 23, 2017

Data Quality Committee (DQC)

Our mission as the Data Quality Committee is to engage the NSSP Community of Practice to identify and attempt to address syndromic surveillance data quality challenges with thoughtful discussion and the inclusion of outside stakeholders. We strive to foster relationships between all groups with a hand in syndromic messaging in order to better syndromic surveillance practice for everyone. 


October 31, 2018

Metadata Visualization App (MVA) Workgroup

The Metadata Visualization App (MVA) workgroup has been developing a metadata visualization application as part of a proof of concept tool containing jurisdiction specific information on Electronic Health Record (EHR) vendors, EHR  vendor products, aggregate data quality metrics(timeliness, validity and completeness), and facility types participating in syndromic surveillance.

October 31, 2018

User-friendly Rshiny web applications for supporting syndromic surveillance analysis

The French syndromic surveillance system SursaUD® has been set up by Santé publique France, the national public health agency (formerly French institute for public health - InVS) in 2004. In 2016, the system is based on three main data sources: the attendances in about 650 emergency departments (ED), the consultations to

August 22, 2017


Contact Us

NSSP Community of Practice

Email: syndromic@cste.org


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