The World Health Organization's Global Influenza Surveillance and Response System (GISRS) has been in operation since 1995, and aggregates infected sample data weekly from laboratories and flu centers around the world. The FluNet website was constructed to provide access to this data, but the ability to visualize this data is limited. This is a fresh visualization built around the GISRS data, showing the propagation of influenza across the globe over time.
Reid Rankin and Ayush Khandelwal, Old Dominion University, December 2013
All the data used in this tool can be downloaded here:
JSON JSON (GZipped) Microsoft Excel
We would like to thank the World Health Organization (WHO) for the GISRS and the data it provides. The effort that has gone into collecting this data is clearly Herculean, and the data itself is an invaluable contribution to science. We hope that our work will produce more public interest in the WHO's scientific efforts.
We would also like to thank the World Bank and the United States Census Bureau for providing the population and area data used in our dynamic filters.
The United Nations Statistics Division provided the mappings of ISO 3166-1 alpha-3 codes to names, which are used to pair GISRS data with geographic regions.
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Countries have different numbers of people in them, and this leads to different numbers of infected samples, even when the infection rate itself is identical. This filter allows you compare virulence rather than numbers of patients by basing map colors on the number of infected samples per person.
Different countries have different areas, and thus take up different amounts of space on the screen. A larger country, if colored the same as a smaller country, will appear to be more infected simply because of the quantity of space covered by the larger country’s color. This filter corrects for this by dispensing equal amount of “ink” to color each country, no matter its size.
GISRS participation rates vary between countries and between years. This filter attempts to correct for these factors.
The propagation of Influenza type B can be hard to visualize because Type A is so widespread. This filter amplifies the visibility of type B by a factor of 10, allowing you to see its spread better even when it is relatively overwhelmed by type A.