Spatial Risk Modeling for Infectious Disease Surveillance Using Population Movement Data

Roberto C.S.N.P. Souza, Renato M. Assunção, Daniel B. Neill, Luís G.S. Silva, Wagner Meira Jr.

Oct 20, 2018 NIPS 2018 Workshop Spatiotemporal Blind Submission readers: everyone
  • Abstract: We compare three recently proposed subset scan methods for spatial disease surveillance that use movement data from case and control individuals, rather than a single location per individual, in order to identify areas with a high relative risk of infection. We illustrate the use of these methods to detect spatial clusters of dengue infection risk using geo-located data from Twitter classified into infected cases and non-infected controls.
  • Keywords: event detection, risk modeling, spatial scan statistics, mobility patterns, movement data
  • TL;DR: We compare three recently proposed subset scan methods for spatial disease surveillance that use movement data from case and control individuals.
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