Using cross-correlation networks to identify and visualize patterns in disease transmission

Syndromic surveillance data such as the incidence of influenza-like illness (ILI) is broadly monitored to provide awareness of respiratory disease epidemiology. Diverse algorithms have been employed to find geospatial trends in surveillance data, however, these methods often do not point to a route of transmission. We seek to use correlations between regions in time series data to identify patterns that point to transmission trends and routes.

June 27, 2019

Designing Epidemiological Networks for Real-world Surveillance Settings

This paper describes the syndromic networks paradigm and its application to various surveillance settings.

July 30, 2018

What do GPs Want in Return from a Syndromic Surveillance System?

In the Northern part of Norway, all General Practitioners (GPs) and hospitals use electronic health records (EHR). They are connected via an independent secure IP-network called the Norwegian Health Network. The newly developed “Snow Agent System” can utilize this environment by distributing processes to, and extracting epidemiological data directly from, the EHR system in a geographic area. This system may enable the GPs to discover local disease outbreaks that may have affected the current patient by providing epidemiological data from the local population.

July 30, 2018

Implementation of a New Syndromic Surveillance System in April 2006 in French Guiana

An outbreak of dengue fever has occured in French Guiana since the end of November 2005 until July 2006. The dengue serotype circulating was DEN-2, responsible of more than 2 000 confirmed cases and 4 deaths. The previous surveillance system was only based on the laboratories data, and didn’t permit to assess the real situation of dengue infection within the population of French Guiana.

March 26, 2019

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Email: syndromic@cste.org

 

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