6 ms·

Google Flu Trends

158 points by sethbannon 14y ago

pyre 14y ago
If you look at Canada[1], there was a larger spike (than the current trend in Canada) around October 2009. [Under "Past Years" select "2009-2010" to see just that plot.] [1] http://www.google.org/flutrends/ca/#CA http://www.google.org/flutrends/ca/#CA
- rbancroft 14y ago
  That spike seems to exist in a lot of countries, including the US, France, etc.. My guess is that it has more to do with the swine flu panic than actual cases of flu.
  - bparsons 14y ago
    Yeah, you might recall that there was a huge push by public health officials to get folks to take the H1N1 vaccine. The actual flu that year was not that bad, so the spike was a bit of an anomaly.
seiji 14y ago
I'm a fan of the CDC flu map with "horrible outbreak" being represented by a dull default beige color: http://www.cdc.gov/flu/weekly/usmap.htm http://www.cdc.gov/flu/weekly/usmap.htm
- svdad 14y ago
  And showing data for the week ending Jan 11 2014. CDC staying one step (year) ahead of Google.
rnadna 14y ago
In case it's of any interest, below is code in the R language that produces time-series graphs for two provinces in Canada. fluPlot <- function(country="ca", regions="Nova.Scotia") { url <- sprintf("http://www.google.org/flutrends/intl/en_us/%s/data.txt", country) d <- read.csv(url, skip=11, header=TRUE) n <- length(regions) t <- as.POSIXct(d[["Date"]]) for (i in 1:n) { if (i == 1) { plot(t, d[[regions[i]]], xlab="", ylab=regions[i], type='l', col=i) grid() } else { lines(t, d[[regions[i]]], col=i) } } legend("top", col=1:n, lwd=par('lwd'), legend=regions, bg='white') } par(mar=c(2, 2, 2, 2), mgp=c(2, 0.7, 0)) fluPlot("ca", c("Ontario", "Nova.Scotia"))
- minikomi 14y ago
  I made a year-by-year line overlay for the Japanese data. You can probably plug in any other area's data. the JS is just in the index.html. http://poyo.co/d3stuff/flu/ http://poyo.co/d3stuff/flu/
- wch 14y ago
  Nice! I've adapted your code and made a version that uses ggplot2. It also uses memoise() so that each data set only needs to be downloaded once per R session. # Memoize read.csv so each data set only needs to be downloaded once require(memoise) readcsv <- memoise(read.csv) fluPlot2 <- function(country="ca", regions="Nova.Scotia") { require(ggplot2) require(reshape2) url <- sprintf("http://www.google.org/flutrends/intl/en_us/%s/data.txt", country) d <- readcsv(url, skip=11, header=TRUE) d$Date <- as.Date(d$Date) # Convert to long format dl <- melt(d, id.vars = "Date", variable.name = "region") # Select regions of interest dlsub <- subset(dl, region %in% regions) ggplot(dlsub, aes(x=Date, y=value, colour=region)) + geom_line() + theme_bw() } fluPlot2("us", c("Minnesota", "California"))
carbocation 14y ago
It would be nice if they would somehow show the delta versus the actual CDC data when it's released 2 weeks later. I would like to understand how good the correlation is for each year and time point.
- shawnps 14y ago
  Is this what you mean (under Historical estimates)? http://www.google.org/flutrends/about/how.html http://www.google.org/flutrends/about/how.html
  - carbocation 14y ago
    Yes, fantastic. That's perfect.
deleted 14y ago
[deleted]
ballard 14y ago
Near-realtime clustering of web searches for symptoms and remedies as well as retail store transaction datasets are how most of the outbreak surveillance systems are implemented. Example: http://biostorm.stanford.edu http://biostorm.stanford.edu
DocSavage 14y ago
It's interesting to compare that graph with the delayed graph at the CDC: http://www.cdc.gov/flu/weekly/index.htm#OISmap http://www.cdc.gov/flu/weekly/index.htm#OISmap In particular, limit the Past Years on the Google graph to 2009-10 (pandemic year) or 2007-2008 (moderately severe season). It correlates pretty well. Using the axis on the CDC graph and guesstimating based on relative size of peak vs those previous years, it looks like we're approaching about 12% of visits for influenza-like illness. Hopefully we peak in the next few weeks. I'd also be curious how well this season's vaccine targeted the current mix of viruses.
- eli 14y ago
  According to NYT this morning, most people are getting H3N2 (which is a nasty one), but the vaccine is very effective against it. Note that it takes two weeks after the shot for immunity to build up. http://www.nytimes.com/2013/01/10/health/flu-widespread-leading-a-range-of-winters-ills.html?_r=0 http://www.nytimes.com/2013/01/10/health/flu-widespread-lead...
  - justsee 14y ago
    According to one of the leading experts on influenza (Tom Jefferson) there's no good scientific evidence that flu vaccines are of much use [1]. Jefferson has also concluded the same regarding Tamiflu. Forbes covered this dearth of supportive data in a piece a few days ago [2]. A few months ago the NYT ran an article reporting on the Center for Infectious Disease Research and Policy at the University of Minnesota announcing the same opinion on flu vaccine effectiveness, (which the article states is apparently heresy in the public health world) [3]. Fascinating that a significant, widely-supported health policy appears to be faith-based medicine masquerading as science-based medicine. I would emphasize that Jefferson doesn't say the vaccine is harmful or that it doesn't work. He merely points out there's no good scientific evidence indicating it's of much use. If The Atlantic's article is to be believed, that was enough to get him ostracized from the medical establishment: “Tom Jefferson has taken a lot of heat just for saying, ‘Here’s the evidence: it’s not very good,’” says Majumdar. “The reaction has been so dogmatic and even hysterical that you’d think he was advocating stealing babies.” Such classic groupthink in an apparently science-driven community is rather troubling, considering the significant social impact of professionals preferring consensus over hard data. [1] http://www.theatlantic.com/magazine/archive/2009/11/does-the-vaccine-matter/307723/?single_page=true http://www.theatlantic.com/magazine/archive/2009/11/does-the... [2] http://www.forbes.com/sites/harlankrumholz/2013/01/08/the-myth-of-tamiflu-5-things-you-should-know/ http://www.forbes.com/sites/harlankrumholz/2013/01/08/the-my... [3] http://well.blogs.nytimes.com/2012/11/05/reassessing-flu-shots-as-the-season-draws-near/ http://well.blogs.nytimes.com/2012/11/05/reassessing-flu-sho...
zoba 14y ago
I'm sure Larry Page will be looking at this data after personally paying for free flu shots to bay area kids. In his article he mentions "...flu shots can have a big effect in preventing flu in the whole region...", so I wouldn't be surprised if this page was directly related to him providing free shots. https://plus.google.com/+LarryPage/posts/32xY3Z1zckL https://plus.google.com/+LarryPage/posts/32xY3Z1zckL
- deleted 14y ago
  [deleted]
- cloudwalking 14y ago
  False, they are not related. Google has been predicting flu severity (based on search data) since 2006.
  - zoba 14y ago
    False. My assertion was that Larry will be looking at this data based on him providing flu shots. I then posited that there is a connection between this page and Larry's flu shot charity -- not that one caused the other, but implied that within Google there was a discussion on the relationship between Larry's activity and this page. In addition, the comment was intended to draw attention to Larry's assertion that flu shots can reduce flu severity in a region...and then provoke readers to investigate whether they find that to be the case. I came to no conclusions about the Bay Area's severity being particularly worse or better than other regions and assumed others may have commentary.
tmostak 14y ago
You can also check out the GPU database I've been working on at http://worldmap.harvard.edu/tweetmap http://worldmap.harvard.edu/tweetmap. Its VERY beta but if you move the start date back to early December and the end of Decemberand you'll see a spike, particularly in the south. Sample size is ~ 175 million tweets.
jpswade 14y ago
I looked for United Kingdom, wasn't there. I looked for Britain, wasn't there, I looked for England, still nothing. I was disappointed.
mnml_ 14y ago
Why is it so high this year ?
theycallmemorty 14y ago
Imagine the cool data you could visualize if you had access to this kind of info from Facebook. You trace who had the flu before you and who had it before them, all the way back to patient zero. Obviously this would be a tremendous privacy violation, so they would never do it, but it would still be interesting.
- dmckeon 14y ago
  Here you go: contest: https://www.facebook.com/pages/CDC-Flu-App-Challenge/146348798766259 https://www.facebook.com/pages/CDC-Flu-App-Challenge/1463487... app: https://www.facebook.com/helpremedies/app_177924539013408 https://www.facebook.com/helpremedies/app_177924539013408 The app seems to have gotten a lot of coverage in popular media. I haven't used it, so have no idea if it works at all, or well. The flu virus is naturally recombinant among species, so patient zero for a given strain is likely to be a farm pond populated by ducks and pigs, very likely in China.
dimitrii 14y ago
http://www.cdc.gov/flu/weekly/weeklyarchives2012-2013/picILI01.htm http://www.cdc.gov/flu/weekly/weeklyarchives2012-2013/picILI...

158 points by sethbannon 14y ago

pyre 14y ago

If you look at Canada[1], there was a larger spike (than the current trend in Canada) around October 2009. [Under "Past Years" select "2009-2010" to see just that plot.] [1] http://www.google.org/flutrends/ca/#CA http://www.google.org/flutrends/ca/#CA

rbancroft 14y ago
That spike seems to exist in a lot of countries, including the US, France, etc.. My guess is that it has more to do with the swine flu panic than actual cases of flu.
- bparsons 14y ago
  Yeah, you might recall that there was a huge push by public health officials to get folks to take the H1N1 vaccine. The actual flu that year was not that bad, so the spike was a bit of an anomaly.

seiji 14y ago

I'm a fan of the CDC flu map with "horrible outbreak" being represented by a dull default beige color: http://www.cdc.gov/flu/weekly/usmap.htm http://www.cdc.gov/flu/weekly/usmap.htm

svdad 14y ago
And showing data for the week ending Jan 11 2014. CDC staying one step (year) ahead of Google.

rnadna 14y ago

In case it's of any interest, below is code in the R language that produces time-series graphs for two provinces in Canada. fluPlot <- function(country="ca", regions="Nova.Scotia") { url <- sprintf("http://www.google.org/flutrends/intl/en_us/%s/data.txt", country) d <- read.csv(url, skip=11, header=TRUE) n <- length(regions) t <- as.POSIXct(d[["Date"]]) for (i in 1:n) { if (i == 1) { plot(t, d[[regions[i]]], xlab="", ylab=regions[i], type='l', col=i) grid() } else { lines(t, d[[regions[i]]], col=i) } } legend("top", col=1:n, lwd=par('lwd'), legend=regions, bg='white') } par(mar=c(2, 2, 2, 2), mgp=c(2, 0.7, 0)) fluPlot("ca", c("Ontario", "Nova.Scotia"))

minikomi 14y ago
I made a year-by-year line overlay for the Japanese data. You can probably plug in any other area's data. the JS is just in the index.html. http://poyo.co/d3stuff/flu/ http://poyo.co/d3stuff/flu/
wch 14y ago
Nice! I've adapted your code and made a version that uses ggplot2. It also uses memoise() so that each data set only needs to be downloaded once per R session. # Memoize read.csv so each data set only needs to be downloaded once require(memoise) readcsv <- memoise(read.csv) fluPlot2 <- function(country="ca", regions="Nova.Scotia") { require(ggplot2) require(reshape2) url <- sprintf("http://www.google.org/flutrends/intl/en_us/%s/data.txt", country) d <- readcsv(url, skip=11, header=TRUE) d$Date <- as.Date(d$Date) # Convert to long format dl <- melt(d, id.vars = "Date", variable.name = "region") # Select regions of interest dlsub <- subset(dl, region %in% regions) ggplot(dlsub, aes(x=Date, y=value, colour=region)) + geom_line() + theme_bw() } fluPlot2("us", c("Minnesota", "California"))

carbocation 14y ago

It would be nice if they would somehow show the delta versus the actual CDC data when it's released 2 weeks later. I would like to understand how good the correlation is for each year and time point.

shawnps 14y ago
Is this what you mean (under Historical estimates)? http://www.google.org/flutrends/about/how.html http://www.google.org/flutrends/about/how.html
- carbocation 14y ago
  Yes, fantastic. That's perfect.

deleted 14y ago

[deleted]

ballard 14y ago

Near-realtime clustering of web searches for symptoms and remedies as well as retail store transaction datasets are how most of the outbreak surveillance systems are implemented. Example: http://biostorm.stanford.edu http://biostorm.stanford.edu

DocSavage 14y ago

It's interesting to compare that graph with the delayed graph at the CDC: http://www.cdc.gov/flu/weekly/index.htm#OISmap http://www.cdc.gov/flu/weekly/index.htm#OISmap In particular, limit the Past Years on the Google graph to 2009-10 (pandemic year) or 2007-2008 (moderately severe season). It correlates pretty well. Using the axis on the CDC graph and guesstimating based on relative size of peak vs those previous years, it looks like we're approaching about 12% of visits for influenza-like illness. Hopefully we peak in the next few weeks. I'd also be curious how well this season's vaccine targeted the current mix of viruses.

eli 14y ago
According to NYT this morning, most people are getting H3N2 (which is a nasty one), but the vaccine is very effective against it. Note that it takes two weeks after the shot for immunity to build up. http://www.nytimes.com/2013/01/10/health/flu-widespread-leading-a-range-of-winters-ills.html?_r=0 http://www.nytimes.com/2013/01/10/health/flu-widespread-lead...
- justsee 14y ago
  According to one of the leading experts on influenza (Tom Jefferson) there's no good scientific evidence that flu vaccines are of much use [1]. Jefferson has also concluded the same regarding Tamiflu. Forbes covered this dearth of supportive data in a piece a few days ago [2]. A few months ago the NYT ran an article reporting on the Center for Infectious Disease Research and Policy at the University of Minnesota announcing the same opinion on flu vaccine effectiveness, (which the article states is apparently heresy in the public health world) [3]. Fascinating that a significant, widely-supported health policy appears to be faith-based medicine masquerading as science-based medicine. I would emphasize that Jefferson doesn't say the vaccine is harmful or that it doesn't work. He merely points out there's no good scientific evidence indicating it's of much use. If The Atlantic's article is to be believed, that was enough to get him ostracized from the medical establishment: “Tom Jefferson has taken a lot of heat just for saying, ‘Here’s the evidence: it’s not very good,’” says Majumdar. “The reaction has been so dogmatic and even hysterical that you’d think he was advocating stealing babies.” Such classic groupthink in an apparently science-driven community is rather troubling, considering the significant social impact of professionals preferring consensus over hard data. [1] http://www.theatlantic.com/magazine/archive/2009/11/does-the-vaccine-matter/307723/?single_page=true http://www.theatlantic.com/magazine/archive/2009/11/does-the... [2] http://www.forbes.com/sites/harlankrumholz/2013/01/08/the-myth-of-tamiflu-5-things-you-should-know/ http://www.forbes.com/sites/harlankrumholz/2013/01/08/the-my... [3] http://well.blogs.nytimes.com/2012/11/05/reassessing-flu-shots-as-the-season-draws-near/ http://well.blogs.nytimes.com/2012/11/05/reassessing-flu-sho...

zoba 14y ago

I'm sure Larry Page will be looking at this data after personally paying for free flu shots to bay area kids. In his article he mentions "...flu shots can have a big effect in preventing flu in the whole region...", so I wouldn't be surprised if this page was directly related to him providing free shots. https://plus.google.com/+LarryPage/posts/32xY3Z1zckL https://plus.google.com/+LarryPage/posts/32xY3Z1zckL

deleted 14y ago
[deleted]
cloudwalking 14y ago
False, they are not related. Google has been predicting flu severity (based on search data) since 2006.
- zoba 14y ago
  False. My assertion was that Larry will be looking at this data based on him providing flu shots. I then posited that there is a connection between this page and Larry's flu shot charity -- not that one caused the other, but implied that within Google there was a discussion on the relationship between Larry's activity and this page. In addition, the comment was intended to draw attention to Larry's assertion that flu shots can reduce flu severity in a region...and then provoke readers to investigate whether they find that to be the case. I came to no conclusions about the Bay Area's severity being particularly worse or better than other regions and assumed others may have commentary.

tmostak 14y ago

You can also check out the GPU database I've been working on at http://worldmap.harvard.edu/tweetmap http://worldmap.harvard.edu/tweetmap. Its VERY beta but if you move the start date back to early December and the end of Decemberand you'll see a spike, particularly in the south. Sample size is ~ 175 million tweets.

jpswade 14y ago

I looked for United Kingdom, wasn't there. I looked for Britain, wasn't there, I looked for England, still nothing. I was disappointed.

mnml_ 14y ago

Why is it so high this year ?

theycallmemorty 14y ago

Imagine the cool data you could visualize if you had access to this kind of info from Facebook. You trace who had the flu before you and who had it before them, all the way back to patient zero. Obviously this would be a tremendous privacy violation, so they would never do it, but it would still be interesting.

dmckeon 14y ago
Here you go: contest: https://www.facebook.com/pages/CDC-Flu-App-Challenge/146348798766259 https://www.facebook.com/pages/CDC-Flu-App-Challenge/1463487... app: https://www.facebook.com/helpremedies/app_177924539013408 https://www.facebook.com/helpremedies/app_177924539013408 The app seems to have gotten a lot of coverage in popular media. I haven't used it, so have no idea if it works at all, or well. The flu virus is naturally recombinant among species, so patient zero for a given strain is likely to be a farm pond populated by ducks and pigs, very likely in China.

dimitrii 14y ago

http://www.cdc.gov/flu/weekly/weeklyarchives2012-2013/picILI01.htm http://www.cdc.gov/flu/weekly/weeklyarchives2012-2013/picILI...