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

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NSSP Community of Practice

Email: syndromic@cste.org

 

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