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Effect of homophily on coupled behavior-disease dynamics near a tipping point.
He, Zitao; Bauch, Chris T.
Affiliation
  • He Z; Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada. Electronic address: zitao.he@uwaterloo.ca.
  • Bauch CT; Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
Math Biosci ; 376: 109264, 2024 Oct.
Article in En | MEDLINE | ID: mdl-39097225
ABSTRACT
Understanding the interplay between social activities and disease dynamics is crucial for effective public health interventions. Recent studies using coupled behavior-disease models assumed homogeneous populations. However, heterogeneity in population, such as different social groups, cannot be ignored. In this study, we divided the population into social media users and non-users, and investigated the impact of homophily (the tendency for individuals to associate with others similar to themselves) and online events on disease dynamics. Our results reveal that homophily hinders the adoption of vaccinating strategies, hastening the approach to a tipping point after which the population converges to an endemic equilibrium with no vaccine uptake. Furthermore, we find that online events can significantly influence disease dynamics, with early discussions on social media platforms serving as an early warning signal of potential disease outbreaks. Our model provides insights into the mechanisms underlying these phenomena and underscores the importance of considering homophily in disease modeling and public health strategies.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Social Media Limits: Humans Language: En Journal: Math Biosci Year: 2024 Document type: Article Country of publication: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Social Media Limits: Humans Language: En Journal: Math Biosci Year: 2024 Document type: Article Country of publication: United States