Quantify the role of superspreaders -opinion leaders- on COVID-19 information propagation in the Chinese Sina-microblog.

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ID: 107509
2020
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Abstract
Effective communication of accurate information through social media constitutes an important component of public health interventions in modern time, when traditional public health approaches such as contact tracing, quarantine and isolation are among the few options for the containing the disease spread in the population. The success of control of COVID-19 outbreak started from Wuhan, the capital city of Hubei Province of China relies heavily on the resilience of residents to follow public health interventions which induce substantial interruption of social-economic activities, and evidence shows that opinion leaders have been playing significant roles in the propagation of epidemic information and public health policy and implementations.We design a mathematical model to quantify the roles of information superspreaders in single specific information which outbreaks rapidly and usually has a short duration period, and to examine the information propagation dynamics in the Chinese Sina-microblog. Our opinion-leader susceptible-forwarding-immune (OL-SFI) model is formulated to track the temporal evolution of forwarding quantities generated by opinion leaders and normal users.Data fitting from the real data of COVID-19 obtained from Chinese Sina-microblog can identify the different contact rates and forwarding probabilities (and hence calculate the basic information forwarding reproduction number of superspreaders), and can be used to evaluate the roles of opinion leaders in different stages of the information propagation and the outbreak unfolding.The parameterized model can be used to nearcast the information propagation trend, and the model-based sensitivity analysis can help to explore important factors for the roles of opinion leaders.
Reference Key
yin2020quantifyplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yin, Fulian;Xia, Xinyu;Song, Nan;Zhu, Lingyao;Wu, Jianhong;
Journal PloS one
Year 2020
DOI
10.1371/journal.pone.0234023
URL
Keywords
Epidemiology coronavirus wuhan serial interval

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