Friday, May 12, 2017

How Twitter can predict flu outbreaks 6 weeks in advance quoting : KCRA

AdvertisementA team from Northeastern University developed a new model to predict the spread of the flu in real time using Twitter. Researchers at Johns Hopkins University and the University of Rochester have developed other methods of using Twitter to track the flu. The flu season starts in the fall, and usually peaks between December and February, although it can last as late as May. The tweets are used to predict the amount of flu cases and the virus's peak. "[With Twitter], you get the data right at the very moment and it has very accurate localization of the data," Vespignani said.



How Twitter can predict flu outbreaks 6 weeks in advance
Your tweets could help track the spread of seasonal flu in real time, say scientists who have developed a new model that uses Twitter posts to predict how the infection may affect a population. They applied forecasting and other algorithms to the key parameters informed by the Twitter data. Researchers then tested the model against official influenza surveillance systems. They found that it accurately forecast the disease's evolution up to six weeks in advance - significantly earlier than other models. They analysed the evolving dynamics revealed in the past data, and were able to select the model that would most likely forecast the future.

Researchers use Twitter posts to forecast flu spread

Using posts on Twitter in combination with key parameters of each season's epidemic, researchers have developed a computational model to project the spread of the seasonal flu in real time. While the paper reports result using Twitter data, the researchers said that the model could work with data from many other digital sources, too. To ascertain those conditions, the researchers incorporated Twitter into their parameter-driven model. Over those time periods, they applied forecasting and other algorithms week by week to the key parameters informed by the Twitter data. Twitter, which includes GPS locations, is a proxy for that," Vespignani said in a statement released by the university.


collected by :Lucy William
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