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Bull Math Biol ; 83(5): 57, 2021 04 09.
Article in English | MEDLINE | ID: covidwho-1173982


As COVID-19 spreads throughout the world without a straightforward treatment or widespread vaccine coverage in the near future, mathematical models of disease spread and of the potential impact of mitigation measures have been thrust into the limelight. With their popularity and ability to disseminate information relatively freely and rapidly, information from social media platforms offers a user-generated, spontaneous insight into users' minds that may capture beliefs, opinions, attitudes, intentions and behaviour towards outbreaks of infectious disease not obtainable elsewhere. The interactive, immersive nature of social media may reveal emergent behaviour that does not occur in engagement with traditional mass media or conventional surveys. In recognition of the dramatic shift to life online during the COVID-19 pandemic to mitigate disease spread and the increasing threat of further pandemics, we examine the challenges and opportunities inherent in the use of social media data in infectious disease modelling with particular focus on their inclusion in compartmental models.

COVID-19/epidemiology , COVID-19/psychology , Health Behavior , Pandemics , SARS-CoV-2 , Social Media , Attitude to Health , COVID-19/prevention & control , Epidemiological Monitoring , Health Belief Model , Humans , Internet/statistics & numerical data , Mathematical Concepts , Pandemics/prevention & control , Social Media/statistics & numerical data
Br J Gen Pract ; 71(703): 82-85, 2021.
Article in English | MEDLINE | ID: covidwho-1088973