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Duration:04:48
Uploaded:2014-11-15
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SciShow News explains how Wikipedia has been used to track, and even predict, outbreaks of disease all over the world, and then introduces you to the most complete naturally mummified bison ever found.

Hosted by: Hank Green
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Sources:
Mummified Bison sources:
http://www.uaf.edu/museum/press/spotlight/blue-babe/index.xml (pictures of Blue Babe, the 33,000 year old mummified bison)
http://strangesounds.org/2014/11/10000-year-old-yukagir-bison-mummy-is-ready-to-reveal-its-secrets.html

http://onlinelibrary.wiley.com.weblib.lib.umt.edu:8080/doi/10.1111/1749-4877.12079/full
http://vertpaleo.org/The-Society/SVP---Paleo-News/Society-News-and-Events/Press-Release---Complete-9000-Year-Old-Frozen-Biso.aspx

Wikipedia study
http://www.plos.org/wp-content/uploads/2014/11/plcb-10-11-Generous.pdf
http://www.eurekalert.org/emb_releases/2014-11/p-fdu110614.php
[Intro]   It shouldn't surprise you to hear that I think science and the internet go fantastic together.  I mean, most of the time.  Yeah, once a year or so, the internet tries to convince us that the Yellowstone Supervolcano is going to explode just because some bison are running down a road or something, and it did convince some people that the world was gonna end in 2012, but the internet is also why you have me.  And it turns out that this thing that we are using here together is surprisingly good at monitoring the health of our species.     According to new research published this week, public health officials have been able to accurately track and even predict the spread of diseases by studying how often those diseases have been looked up on Wikipedia.  Scientists at Los Alamos National Laboratory were able to successfully monitor influenza outbreaks in the United States, Poland, Japan, and Thailand, as well as Dengue Fever in Brazil by monitoring the number of views received by pages related to those diseases.  The team was also able to forecast half of the outbreaks they studied at least 28 days in advance.  The results suggest that people start researching the diseases online when they, or people they know, begin to show symptoms, but before they get medical attention.  Scientists were able to track Wikipedia searches, thanks to the site's open source access logs. These logs show how many times a page is view an hour and in what language.  So, for example, since the majority of people who speak Thai live in Thailand, scientists could monitor the access log for the Thai page for influenza and get a sense of the disease's prevalence there.  They also monitored pages having to do with specific symptoms, like chills, fever, and headache.  Then, they aggregated all of this data into a computer model and compared it with the actual weekly reports of seven diseases in nine countries.  Their method worked particularly well in countries that spoke a single language that wasn't spoken in other countries, like Thailand or Poland, but it also worked well in tracking influenza in the US and Dengue Fever in Brazil, which surprised the scientists, because those countries use two of the most commonly spoken languages, English and Portuguese.  They think that their predictions still worked because the US dominates the English speaking internet landscape, while Brazil is the only Portuguese speaking country that has Dengue.   As you can probably guess, we are still a long way from the internet being able to predict our next public health crisis for us.  Not only are there problems with using language as a proxy for nationality, but more importantly, the model can only track people who have internet access, and by some estimates, that's only about 35% of the world's population.  Plus, the monitoring only worked for diseases that develop quickly and tend to appear in seasonal cycles.  So while it was effective at tracking influenza and Dengue, it was of no help in forecasting rates of Tuberculosis or HIV infections.  Still, the study is yet another step toward harnessing the power of the internet for the aims of science, and it's always good to see those two gettin' along.   Alright, now, if you're like us, few things thrill you more than finding really old dead things, especially if they're frozen.  And if that's the case, you were probably as excited as we were when the news came about the Yukagir Mummy, the most complete, naturally preserved bison ever found.  First discovered in 2011 in the permafrost of Eastern Siberia, the mummy is a 9000 year old Steppe Bison, a species that became extinct at the end of the last Ice Age.  Its organs are almost fully preserved and include a heart and stomach, lungs, intestines, and a brain. He still has fur and a tail and even the tips of his little ears.  An autopsy performed by Russian researchers showed that the bison died when he was about four years old, and that he had very low body fat, suggesting he may have starved to death.  But Yukagir is not the first bison mummy scientists have discovered.   There are actually four of them, including a 36,000 year old specimen unearthed by Alaskan gold miners during the 1970s.  But all of these mummies were either scavenged by animals or partly destroyed by the freezing and thawing.  But Yukagir wasn't, so the data that we'll glean from him will help us better understand all kinds of things about the long-gone Steppe Bison, from what they ate, to what parasites they carried, to where they roamed.  And yes, I know you're wondering, so I'll tell you that researchers have gotten fragments of DNA from the bison's hair, which will help clarify how Steppe Bison are related to modern-day bison and cattle.  But in case you're having dreams of riding a Steppe Bison in some futuristic Pleistocene theme park, there are no plans to use that DNA to bring the Steppe Bison back through a process known as resurrection biology, or de-extinction.     So I'm sorry to burst that particular bubble, but thank you for joining me here on SciShow News.  If you want to help us share science with the world, which we couldn't do without support from people like you, you can become a supporting subscriber at Subbable.com/SciShow, and if you just want to keep getting smarter with us, you can go to YouTube.com/SciShow and subscribe.