A pandemic influenza modeling and visualization tool

Ross Maciejewski, Philip Livengood, Stephen Rudolph, Timothy F. Collins, David S. Ebert, Robert T. Brigantic, Courtney D. Corley, George A. Muller, Stephen W. Sanders

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

The National Strategy for Pandemic Influenza outlines a plan for community response to a potential pandemic. In this outline, state and local communities are charged with enhancing their preparedness. In order to help public health officials better understand these charges, we have developed a visual analytics toolkit (PanViz) for analyzing the effect of decision measures implemented during a simulated pandemic influenza scenario. Spread vectors based on the point of origin and distance traveled over time are calculated and the factors of age distribution and population density are taken into effect. Healthcare officials are able to explore the effects of the pandemic on the population through a geographical spatiotemporal view, moving forward and backward through time and inserting decision points at various days to determine the impact. Linked statistical displays are also shown, providing county level summaries of data in terms of the number of sick, hospitalized and dead as a result of the outbreak. Currently, this tool has been deployed in Indiana State Department of Health planning and preparedness exercises, and as an educational tool for demonstrating the impact of social distancing strategies during the recent H1N1 (swine flu) outbreak.

Original languageEnglish (US)
Pages (from-to)268-278
Number of pages11
JournalJournal of Visual Languages and Computing
Volume22
Issue number4
DOIs
StatePublished - Aug 1 2011

Keywords

  • Geovisualization
  • Pandemic influenza
  • Risk assessment
  • Visual analytics

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Computer Science Applications

Fingerprint Dive into the research topics of 'A pandemic influenza modeling and visualization tool'. Together they form a unique fingerprint.

  • Cite this

    Maciejewski, R., Livengood, P., Rudolph, S., Collins, T. F., Ebert, D. S., Brigantic, R. T., Corley, C. D., Muller, G. A., & Sanders, S. W. (2011). A pandemic influenza modeling and visualization tool. Journal of Visual Languages and Computing, 22(4), 268-278. https://doi.org/10.1016/j.jvlc.2011.04.002