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Impact of media coverage on epidemic spreading in complex networks

Author

Listed:
  • Wang, Yi
  • Cao, Jinde
  • Jin, Zhen
  • Zhang, Haifeng
  • Sun, Gui-Quan

Abstract

An SIS network model incorporating the influence of media coverage on transmission rate is formulated and analyzed. We calculate the basic reproduction number R0 by utilizing the local stability of the disease-free equilibrium. Our results show that the disease-free equilibrium is globally asymptotically stable and that the disease dies out if R0 is below 1; otherwise, the disease will persist and converge to a unique positive stationary state. This result may suggest effective control strategies to prevent disease through media coverage and education activities in finite-size scale-free networks. Numerical simulations are also performed to illustrate our results and to give more insights into the dynamical process.

Suggested Citation

  • Wang, Yi & Cao, Jinde & Jin, Zhen & Zhang, Haifeng & Sun, Gui-Quan, 2013. "Impact of media coverage on epidemic spreading in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(23), pages 5824-5835.
  • Handle: RePEc:eee:phsmap:v:392:y:2013:i:23:p:5824-5835
    DOI: 10.1016/j.physa.2013.07.067
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    References listed on IDEAS

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    1. Wallis, Patrick & Nerlich, Brigitte, 2005. "Disease metaphors in new epidemics: the UK media framing of the 2003 SARS epidemic," Social Science & Medicine, Elsevier, vol. 60(11), pages 2629-2639, June.
    2. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    3. Wang, Jia-zeng & Liu, Zeng-rong & Xu, Jianhua, 2007. "Epidemic spreading on uncorrelated heterogenous networks with non-uniform transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 715-721.
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    Citations

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    Cited by:

    1. Han, Dun & Sun, Mei & Li, Dandan, 2015. "Epidemic process on activity-driven modular networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 354-362.
    2. repec:eee:apmaco:v:251:y:2015:i:c:p:539-563 is not listed on IDEAS
    3. repec:eee:phsmap:v:482:y:2017:i:c:p:757-771 is not listed on IDEAS
    4. Han, Dun & Sun, Mei, 2014. "Can memory and conformism resolve the vaccination dilemma?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 95-104.
    5. Du, Yuxian & Gao, Cai & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2014. "A new method of identifying influential nodes in complex networks based on TOPSIS," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 399(C), pages 57-69.
    6. Han, Dun & Sun, Mei & Li, Dandan, 2015. "The virus variation model by considering the degree-dependent spreading rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 42-50.

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