EigenEvent: An algorithm for event detection from complex data streams in syndromic surveillance

@article{FanaeeT2015EigenEventAA,
  title={EigenEvent: An algorithm for event detection from complex data streams in syndromic surveillance},
  author={Hadi Fanaee-T and Jo{\~a}o Gama},
  journal={ArXiv},
  year={2015},
  volume={abs/1406.3496}
}
Syndromic surveillance systems continuously monitor multiple pre-diagnostic daily streams of indicators from different regions with the aim of early detection of disease outbreaks. The main objective of these systems is to detect outbreaks hours or days before the clinical and laboratory confirmation. The type of data that is being generated via these systems is usually multivariate and seasonal with spatial and temporal dimensions. The algorithm What's Strange About Recent Events (WSARE) is… 

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