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10.1038/srep43634 http://scihub22266oqcxt.onion/10.1038/srep43634 C5333634!5333634!28252663     free     free     free       Sci+Rep 2017 ; 7 (ä): ä Nephropedia Template TP {{tp|p=28252663|t=2017. Dueling biological and social contagions |pdf=|usr=}}{{28252663}} gab.com Text Dueling biological and social contagions JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28252663 #FOAvip Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of ?dueling contagions?, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions. Twit Text FOAVip Dueling biological and social contagions ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28252663 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28252663 #FOAvip English Wikipedia <ref>{{Cite pmid|28252663}}</ref> Dueling biological and social contagions #MMPMID28252663 Fu F; Christakis NA; Fowler JH Sci Rep 2017[]; 7 (ä): ä PMID28252663show ga Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of ?dueling contagions?, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R0 of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions. äDueling biological and social contagions (epmc).pdf DeepDyve Pubget Overpricing