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10.1007/s11538-020-00757-4 http://scihub22266oqcxt.onion/10.1007/s11538-020-00757-4 32617673!7329999!32617673     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Bull+Math+Biol 2020 ; 82 (7): 86 Nephropedia Template TP {{tp|p=32617673|t=2020. Trending on Social Media: Integrating Social Media into Infectious Disease Dynamics |pdf=|usr=}}{{32617673}} gab.com Text Trending on Social Media: Integrating Social Media into Infectious Disease Dynamics JO: Bull Math Biol http://www.kidney.de/pget.php?&tw=1&pmid=32617673 #FOAvip Social media plays an important role in alerting and educating the public during disease outbreaks. By increasing awareness of the disease and its prevention, it can lead to a modification of behaviour which then affects contact/incidence rates. Social media data may also be used when formulating, developing and parameterising models. As mobile technology continues to evolve and proliferate, social media is expected to occupy an increasingly prominent role in the field of infectious disease modelling to improve their predictive power. This article presents a review of existing models incorporating media in general and highlights opportunities for social media to enhance traditional compartmental models so as to make the best use of this resource in controlling the spread of disease. Twit Text FOAVip Trending on Social Media: Integrating Social Media into Infectious Disease Dynamics ????Bull Math Biol http://www.kidney.de/pget.php?&tw=1&pmid=32617673 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32617673 #FOAvip English Wikipedia <ref>{{Cite pmid|32617673}}</ref> Trending on Social Media: Integrating Social Media into Infectious Disease Dynamics #MMPMID32617673 Sooknanan J; Comissiong DMG Bull Math Biol 2020[Jul]; 82 (7): 86 PMID32617673show ga Social media plays an important role in alerting and educating the public during disease outbreaks. By increasing awareness of the disease and its prevention, it can lead to a modification of behaviour which then affects contact/incidence rates. Social media data may also be used when formulating, developing and parameterising models. As mobile technology continues to evolve and proliferate, social media is expected to occupy an increasingly prominent role in the field of infectious disease modelling to improve their predictive power. This article presents a review of existing models incorporating media in general and highlights opportunities for social media to enhance traditional compartmental models so as to make the best use of this resource in controlling the spread of disease. |*Disease Outbreaks/prevention & control[MESH] |*Social Media[MESH] |Communicable Disease Control[MESH] |Communicable Diseases/*epidemiology/psychology[MESH] |Health Behavior[MESH] |Health Education[MESH] |Health Risk Behaviors[MESH] |Humans[MESH] |Incidence[MESH] |Mathematical Concepts[MESH] |Models, Biological[MESH] |Models, Psychological[MESH]Trending on Social Media: Integrating Social Media into Infectious Dis(epmc).pdf DeepDyve Pubget Overpricing