H1N1 & Flu Info

I read a fantastic blog from the Freakonomics blog at the New York Times web site. I include everything here as well as the link to the Emory Screening Algorithm which helps you determine if you might have the flu.

From Stephen Dubner's blog:

November 10, 2009, 10:03 am
On the Prevalance of H1N1
By Stephen J. Dubner

In Seattle recently, I met a pulmonologist who said that the H1N1 virus has him busier than he’s ever been, his hospital beds full of flu patients. The uptick hit particularly hard about 10 days ago, he said.

How has the flu been playing out across the country?

Craig Feied, the physician and technologist we write about in SuperFreakonomics (yes, we’ll run a virtual book club session with him soon; he’s in Chapter 2), sent along the following data picture. “Some doctor,” he writes, “made in a few seconds using Amalga.” That’s the hospital software system that Feied and Mark Smith developed at Washington (D.C.) Hospital Center, and which was later acquired by Microsoft.
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Here’s Feied’s commentary on the picture:

For anybody who wonders how much “hype” there is in the H1N1 story, here is an Amalga-created graph of flu seasons in Washington, D.C. from 2002 to 2009.

ILI stands for “Influenza-Like-Illness,” meaning that this includes everybody who shows up at the hospital primarily for symptoms of flu (there’s no attempt to confirm the diagnosis of influenza with specific tests, so this likely includes some people with the “common cold” and people with pneumonia or other respiratory infections).

For each year, January 1 is at the left side of the screen and December 31 is at the right. Historically, the “flu season” has a small bump in the fall, with the serious spike usually beginning early in January and extending into the beginning of March.

It’s instantly apparent that this year is unprecedented in recent history. Long before the typical spike season we are already seeing more cases than we’ve ever seen — and presumably the worst is yet to come.

It’s possible, of course, that some of the surge was caused by patients who wouldn’t have gone to an E.R. but for the media “hype,” as Feied puts it, about H1N1.

To that end, Feied offers another data tool: the the Emory screening algorithm — a self-assessed flu survey “to help people decide when it’s time to go to the E.D.,” he says, “versus when they can safely stay home. As this problem reaches disaster proportions, emergency departments and physician offices will need all the help they can get.”