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Let's take a step back and think about the entire planet-- the planet we live on, Earth. We've got lots of little continents and water, right? I'm going to draw that out here. And, if I was to ask you, how much flu affects this planet-- all the people that inhabit this planet-- in one year, probably the best place to go to answer that question would be the WHO. And that's exactly what I did. I went to the World Health Organization, and I wanted to know how many people on our planet, Earth, in one year-- let me write that out here so we know that we're not talking about many, many years, just one year-- how many people are hospitalized from the flu? So this is actually a pretty mind-numbing number. Look at this huge number, 5 million-- 3 million to 5 million-- end up going to the hospital, because they have severe complications of flu. This could be anything from like, pneumonia to bronchitis, to having a horrible asthma attack, something like that. So this is not how many people get sick with the flu, but how many actually end up in the hospital or have severe disease from influenza. And then, another number I wanted to look up is how many actually die of having the flu? And you know, a lot of people will say, well, you know, the flu is not a big deal. It doesn't really affect you much, and you just get kind of sick. And if that were true, then we wouldn't be having a quarter million to a half a million deaths each year from the flu. This is a really kind of a sad commentary, when you consider the fact that this is something that we actually do have a vaccine for. So in the world, we have a huge number of deaths happening. Now, whenever I hear statistics like this, my mind always kind of takes comfort. Like, I always think, well, I'm living in a developed country, and I have health insurance, and I can go to the doctor if I need to. And so, what are the numbers like in the US? I mean, I'm sure that they're obviously not as high as that. And what I wanted to prove to you is, actually, the numbers are not insignificant. So in the US, we have the CDC. And the Centers for Disease Control tells us that we have about 200,000 people going to the hospital each year because of the flu. Now you have millions of people getting the flu, right? That's another number. But this is just how many people end up going to the hospital because of it. And then this is probably the scariest thing, we have 3,000 to 49,000 people dying of the flu every single year. And I wanted to see why they had such a big range. So I actually looked at the study. And it turns out, between 1976 and 2007, they actually kept track of how many people had died of the flu. And this is not, obviously, an exact graph. But I just wanted to show you that they said, well, one year, the number was as high as 49,000. This is number of people that died because of the flu in the United States. And one year, the number was as low as 3,000. And I say as low as 3,000, but, I mean, 3,000 deaths is still a lot of deaths. So we have thousands of people dying of flu, and we have hundreds of thousands of people going to the hospital for flu. So if someone ever tells you that it's not a serious problem in the US or in developed countries, that is definitely not true. And it's a huge problem internationally. Now I want to show you some interesting data. This actually comes from the CDC. They actually put this on their website, and you can check this out. It's actually pretty neat and helpful to understand exactly how we gather information about flu. So the key word here is surveillance. You see this influenza surveillance report here. And surveillance basically means, how do we gather data around a disease, or gather data around anything, really? So let's talk through that process. The traditional way we do it was we say, OK, we have a person. Let's say this person is me. Let's say I'm feeling pretty lousy from the flu. I've got a case of sore throat, and I've got some runny nose, and maybe I've got some fevers and body aches. So I'm going to go to my doctor. And my doctor is going to be over here, in blue. And my doctor's going to be pretty smart, pretty savvy. And they're going to figure out pretty quickly that I've got the flu. They're smiling because they figured it out. And so, then they're going to take that information, and they're going to say, OK, well, I have a person here by the name of Rishi, and he has the flu. And they're going to send that information where? It's going to go to the hospital that they work in-- or the clinic, let's say. So that clinic now has a record of all the people that walk through and have the flu. So now that clinic or that hospital is going to also take that list of people-- and, you know, it's protected, confidential information, so it may, at this point, not even have your name on it, maybe they just have the total number of people with the flu-- and they're going to send that over, let's say, to the county. And I live in San Francisco. So let's say this is San Francisco County. So they send that information to my county, San Francisco County. And then, that county is going to get that information. They're going to say, well, thank you, hospital, for sending it over. And they're going to take that whole list, and they're going to add it to all the other hospitals that sent them information. And they're going to get a bigger number. And they're going to get that bigger number, and they're going to send it to the state of California. The state of California gathers information about the flu. And they're going to say, thank you so much, county, for sending it over. This is California. And California is going to gather up all the information about who's got flu in their entire state-- all the different counties that send them information. And they're going to send that information, finally, to the United States' kind of public health authority, and it's based over here in Atlanta. So eventually that information goes to the Centers for Disease Control. So this is kind of the chain of information that we traditionally use. And that's why, over here, it says, this is estimates reported by the state and territorial epidemiologists, so all the different territories and states that are encompassed by the United States. So that's what that means. And this graph is telling us that we're seeing regional and widespread flu in almost every state at the end of 2012-- so, just a couple weeks ago, since, today, the date is January 10th. Now some really smart people got together, and they said, is this the only way to actually gather information about the flu? Maybe there's another way. So some folks at Google got in touch with some folks at the CDC. And they said, let's put our brains together, and let's figure out if there are other ways that we can actually gather information. Now think about me. Now, I had the flu, right? What else might I do? Well, I might jump on my computer, because I'm a computer kind of guy, and I like to learn about what's going on. And so I might jump on my computer. And I'll say, OK, let me search in Google. Maybe I'll search in Google to find out what I might have. So I'll type into Google and say, hey Google, tell me what I need to worry about. And I'll go through, and I might find that Google tells me that if you type in sore throat-- let's say, I type in the word sore throat here-- it might give me some search results. It'll say, well, maybe you should take this medicine or that medicine. Or I might type in the word cough or fever. These are all words that I might type in the day that I get sick. And I might also go to the hospital, or I might not. Maybe I'm not that sick. So I think, let me just type in these words. And what Google gets is they get all the searches that Rishi did that day, as well as all the searches that other people in my community are doing. So maybe there are other people searching. Maybe Mr. Red is searching, and maybe Mrs. Blue is searching. So maybe all these other people are searching as well for the same kind of words. And what are these words? These are basically all flu searches, right? Kind of searches related to the flu. So I'm going to call them flu searches. And there are many other terms as well, but I'm not listing all of them, just kind of some of them, so you get a sense for what this means. So Google, what they could do is they could actually tally up the total number of searches related to the flu that are happening in a community, let's say in San Francisco, in one day. And that total I'm calling this total right here, flu searches. That's the total searches for flu-related terms in a day out of San Francisco. Now, over here, we've got other searches. So let's say we've got searches for weather in Nepal. Maybe I'm going on a trip to Nepal, or somebody in my community is going, and they search for that. Or maybe someone is searching for basketball news. They want to know which team won and which team lost. They want to know that. And maybe a third person is searching for cell phones. So really, these are all the other kind of searches that are happening on Google. And there are probably thousands and thousands of them. And you could tally all these searches up, and this would be the total searches in Google. And this is, again, the searches happening in one day in one community. This could be all the searches happening in San Francisco. And maybe there's a person over here, a little girl in yellow, and maybe this is a man in purple who's searching, and maybe this is a person in green. And these aren't necessarily different people, right? It could be, maybe Mr. Red searched for sore throat, and then later he was interested in basketball news. So he actually was in both groups. So really, we're not counting people, we're counting total searches. That's the key idea here. Total searches is what matters, in a day, in some community. Now you could actually take these numbers and make some sense out of them. This is where the folks at Google and the folks at the CDC did something very clever. They said, OK, let's put this number here and this number here, and let's divide by them. So let's do flu searches divided by total searches. And if you divide the two, you're going to get some fraction, some percentage. And it's going to be pretty small, because flu searches is going to be a small fraction of the total searches that are happening. And then you could take that fraction-- this is where it gets really interesting-- and you could say, OK, let's look at a whole year. This fraction we got for a given day, but you could do this every single day for a whole year. And you could say, January, February, March, April. You could go through the entire year, the entire calendar. This is June. And let's say July. This is August, September, October, November, December. And if you did this 365 times, you know, each day you did this, let's say, or you could do this weekly, however you want, you would get some fraction, some percent. And maybe the percentages would be small, but you could graph them out if you wanted to. And you'd probably notice something like this-- you'd notice that in the winter months, the numbers get bigger, and in the summer months, the numbers get smaller. Because, in the summertime, fewer people are probably searching for cough, runny nose, things like that, because those things usually happen in the winter. So you might get something like this-- this is percent, over here. So this is kind of a trend that you might see. Now, as I said, the people at the CDC and the people at Google were very clever to think of this. And they actually compared data. They said, OK, let's compare data from Google to CDC data. Let's see how they actually look side-by-side. Here, in my graph, I had done one year. This is one year, from here to here. And you can actually see that this is basically the same thing. This is from January through December. So we're seeing peaks in the wintertime, and that's understandable. But the great thing about this graph is you can see that Google flu trends actually line up really nice with the US data. And the US data, if you look down here, comes from, as we said, the CDC. So this is actually information from the CDC about influenza-like illness. And they're seeing, or we're seeing, that there's a fantastic correlation, both in the timing, because the peaks are happening basically at the same time, and also in the magnitude, so some years are smaller and some years are bigger. So it's actually pretty impressive that the data from searches that are happening on Google actually lines up really well with data, the traditional way that we get data, through surveillance in our public health system. Let me show you one more thing now. So if you look currently-- so the last graph was six years. I just want to quickly point that out. This is six years of data, 2004 to 2009. But, if you look currently, we actually have 20-- and, where's the date here-- 2012 and 2013. And here we are between December and January. In fact, today's date is January 10th, and it's 2013. So here we are, and you can see that the searches are really peaking out. This is looking at national data, but you could also change it. You could say, well, instead of the US, I'd like to look at Mexico, or I'd like to look at Canada, or some other country. Or you could say, instead of looking nationally, I want to look at some city or some state. So you could change it, and this is actually something I encourage you to play with if you're interested. Go to and play around. Check out your own country, your own community, and you could see how many people in your area are searching for flu-related words. And then, finally, if you actually look at the international level, you can actually see the map that's happening internationally, globally. And here some interesting trends also appear. You can see all this activity in the northern hemisphere, and a lot less in the southern hemisphere, which makes sense, because it's our winter season, and flu is definitely a virus that affects us more in the wintertime. And you can see that some countries have really intense levels, like the US, and high levels, like Canada, and some of these countries have more moderate levels, or low levels, like Europe and Russia and Japan.