A Faster Way to Trace Epidemics

My recent Decoded Science article, “Trace the Source of a Rumour or Epidemic via its Network“, introduces a paper written by Dr. Pedro Pinto about a pair of improved algorithms for backtracking messages in a network.

Why Bother Tracing Messages or Infections?

"Graph of CSCW Tweets" image by Marc_Smith (Marc Smith)
“Graph of CSCW Tweets” image by Marc_Smith (Marc Smith)

(If this image of “CSCW Tweets” confuses you, just read my article for the explanation).

Being able to re-trace a message in a complex network is critical for learning who started a viral rumour on the Internet. It’s a life-or-death matter to find the source of infection in an epidemic, which spreads much like a message throughout a “network” of people.

Dr. Pinto’s improvement reduces the work required to trace any such message. My article explains some of the concepts in more detail, and links to his site so you can read his paper. He also deals with the math and statistics to demonstrate that his proposed process works more efficiently than previous network tracking algorithms.
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Publicity for  my Epidemic Tracing Article

In my Blog of Writing, “Better Network Backtracking” adds an un-trace-able writing tip for bloggers who interview their sources.

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Thank you for reading about my article explaining a new math algorithm that traces rumours and epidemics back through networks.