Flu Season

Recently, this article in the New York Times about the intensity of this year’s flu season piqued my interest. According to the authors (as well as most epidemiologists), this year’s flu season is unusually severe due to “a confluence of factors: an early start to the flu season, with more people sick in December than usual; a strain that tends to make people sicker; a relatively low vaccination rate; and a mismatch between this year’s flu vaccine and the virus that’s making people sick.”  The fact that we know these data and trends with such certainty highlights one of the huge benefits of our increasingly technological, data-driven society: understanding how diseases move through regions and populations. In other words, what can data do? Track the flu.

Graph taken from http://www.cdc.gov/flu/weekly/For example, the federal website Fluview posts CDC updates on the flu. Just a few quick clicks can assure you that a) as of the first week of January, flu incidence has peaked and is already on the decline,  b) while this season is more severe than 2013-2014, is it comparable in terms of 2012-2013, c) mortality from influenza is on par with previous seasons, and d) hospitalizations are by far most substantial in older adults 65+ years of age, typically with concurrent medical conditions.  So yes, the New York Times article highlights the severity of this flu season, but routine data monitoring by the CDC provides reassurance that this season is really not disproportionally dangerous to most adults.

http://gis.cdc.gov/grasp/fluview/fluportaldashboard.htmlIf you want to dig deeper and look at specific trends using GIS data, you can access information on data points of interest, such as the number of positive flu tests by flu subtype (shown at right).

And for those wanting to free themselves of government-generated data and find an independent source, you can easily look at Google trends data. However, a note of caution– these data are generated by Google search terms and associated modeling under the premise that there is a correlation between flu incidence and the millions of users who search for flu-related topics online. And while Google publishes historical data showing that there is indeed a close relationship between search queries, flu incidence, and CDC data, there have been criticisms that the Google technique overestimates flu incidence.

So what can all these data DO? Well, for one, they may impact behaviors such as travel and vacation time. For example, people may avoid travel to states with high levels of flu outbreaks, or parents may avoid trying to plan vacation time around peak flu season. Caretakers of older adults in particular may choose to exercise caution in scheduling elective surgery in hospitals, knowing that influenza cases peak in medical facilities in December and January.

Taken from "Knowledge Is Beautiful" by David McCandless

Infographic taken from “Knowledge Is Beautiful” by David McCandless

And of course the big picture about our knowledge of yearly influenza outbreaks is that only about 50% of eligible people in the U.S. are vaccinated each year. In part this is because of a host of misinformation about potential negative effects of the flu vaccine (such as headaches, muscle aches, and mini-flu symptoms), but as this info graphic from placebo vs. flu vaccine studies shows, the only established side effect of the vaccine is a temporarily sore arm. More importantly, data show that there is a 27% reduction in risk of hospitalization and 48% reduction in risk of mortality with flu vaccination. So bottom line…track the data, know the trends, but get the shot!


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