title: Event-driven architecture for health event detection from multiple sources.
abstract: Early detection of potential health threats is crucial for taking actions in time. It is unclear in which information source an event is reported first and, information from various sources can be complementing. Thus, it is important to search for information in a very broad range of sources. Furthermore, real-time processing is necessary to deal with the huge amounts of incoming data in time. Event-driven architectures are designed to address such challenges. This will be shown in this paper by presenting the architecture of a public health surveillance system that follows this style. Starting from concrete user requirements and scenarios, we introduce the architecture with its components for content collection, data analysis and integration. The system will allow for the monitoring of events in real-time as well as retrospectively.
authors: L3S Research Center, Hannover, Germany.
authors: Kerstin
authors: K
authors: Denecke
authors: Göran
authors: G
authors: Kirchner
authors: Peter
authors: P
authors: Dolog
authors: Pavel
authors: P
authors: Smrz
authors: Jens
authors: J
authors: Linge
authors: Gerhard
authors: G
authors: Backfried
authors: Johannes
authors: J
authors: Dreesman
mesh_terms: D000465:Algorithms; D003140:Communicable Disease Control / Q000379:methods*; D003141:Communicable Diseases / Q000175:diagnosis; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data*; D004813:Epidemiology; D006751:Hospital Information Systems; D006801:Humans; D020407:Internet; D008498:Medical Record Linkage; D011159:Population Surveillance / Q000379:methods*; D011634:Public Health / Q000379:methods*; D040442:Public Health Informatics; D012984:Software; D018511:Systems Integration