Geovisualizing the Ebola Crisis

Media coverage of the Ebola virus outbreak has thus far represented a geospatial and cartographic moment.  Mapping of the outbreak and geovisualization of its different facets is doing much to frame public understanding of the crisis as well as the policies that are attempting to address it.

Population flow measured by mobile phones from Worldpop.org.uk/Flowminder

One the one hand, the widespread use of geovisualizations to report on the Ebola epidemic reflects the high density of information that maps provide.  This has only been increased by the swift integration of traditional cartography with animated graphics and other web-based media to create ever more visually appealing infographics that have a geographic twist.

Geovisualizations demonstrate the importance of place and scale—two fundamental aspects of geography—to the Ebola epidemic.  Maps of the worldwide locations of where infected patients are staying, the locations of medical centers equipped to handle Ebola are located, not to mention the geographic concentrations of new cases give readers a place-based sense of either unease or hope.  Maps of Ebola-related travel restrictions tell us how national governments are responding to the ongoing risk of spread.

But West Africa remains the epicenter of this Ebola outbreak and the region is already suffering a tremendous human and economic toll from the virus.  Using geospatial approaches to understand patterns of human mobility will is playing a central role in efforts to prevent the outbreak from reaching even greater proportions.  One of the best examples of this is work done by researchers associated with the Flowminder Foundation which reveals at an unprecedented level of detail the movements of people in and around the parts of West Africa with the highest concentrations of Ebola cases.  What made this work possible was the use of cell phone records, which are proprietary to the providing telecom companies and sensitive information for the phone users themselves.  Given the growing need for this type of spatial epidemiology to address fast breaking and complex emergencies like the Ebola outbreak, we can expect that norms around data availability and use to change quickly and in unexpected ways.


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United States Mortality by Cause of Death, Race, and Gender

This graph shows mortality in the United states by cause of death, race and gender from 1969-2009.

  • Compare two series by selecting the appropriate variables in the menu found below the graph.
  • Add additional data series by selecting them on the left side of the graph.

 

This graph compares blood diseases and cancer in black women. To see more, click on the graph to open in a new window.

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World Map Distorted by Fertility Rate

This map displays the world, distorted by fertility rate. It contains the same indicators as our World Map, with additional indicators relating to women’s reproductive rights and issues.

  • To examine other indicators, click on the Contents button (contentsbutton) above the Legend.
  • Choose the first drop-down option to the right of “World Map Distorted by Fertility Rate” and select “Change symbols,” then select the desired indicator from the “To Show” drop-down menu.
  • Click on an individual country to see available data on all indicators.
  • -99 values indicate missing data.

 

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