Table 2. Information flow from open-source internet data in event-based surveillance systems.

EBS	Data collection	Data processing	Data analytics	Reporting
Moderated systems	Human analysts search and identify open-source internet data for health-related concern	Human analysts review, filter and designate the threat level of the event	None	Reports on health-related threats are communicated through email and posted on EBS system website
Partially moderated and fully automated systems	Automated feed of open-source internet data	Taxonomic classification and ML algorithms filter and classify events based on their metadata (e.g. type of threat, location and date). ML algorithms score the level of relevancy. In partially moderated systems, highly scored data sources are curated by human analysts	Analytic techniques evolve with time and differ among EBS systems. Current techniques include the following: mapping of geo-tagged events; bar plots showing changes over time to keyword counts, number of identified articles and expected and observed number of disease cases; word clouds showing importance of keyword terms; alert notices given sudden increases to case counts, reliability of sources and/or number of unique sources	Reports on health-related threats are communicated through email and posted on EBS system website and notified to appropriate web application user communities

Abbreviations: EBS, event-based surveillance; ML, machine learning