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An analecta of visualizations for foodborne illness trends and seasonality.

Ryan B SimpsonBingjie ZhouTania M Alarcon FalconiElena N Naumova
Published in: Scientific data (2020)
Disease surveillance systems worldwide face increasing pressure to maintain and distribute data in usable formats supplemented with effective visualizations to enable actionable policy and programming responses. Annual reports and interactive portals provide access to surveillance data and visualizations depicting temporal trends and seasonal patterns of diseases. Analyses and visuals are typically limited to reporting the annual time series and the month with the highest number of cases per year. Yet, detecting potential disease outbreaks and supporting public health interventions requires detailed spatiotemporal comparisons to characterize spatiotemporal patterns of illness across diseases and locations. The Centers for Disease Control and Prevention's (CDC) FoodNet Fast provides population-based foodborne-disease surveillance records and visualizations for select counties across the US. We offer suggestions on how current FoodNet Fast data organization and visual analytics can be improved to facilitate data interpretation, decision-making, and communication of features related to trend and seasonality. The resulting compilation, or analecta, of 436 visualizations of records and codes are openly available online.
Keyphrases
  • public health
  • big data
  • electronic health record
  • healthcare
  • physical activity
  • emergency department
  • machine learning
  • mental health
  • adverse drug
  • global health
  • risk assessment
  • data analysis
  • cell proliferation