A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks

Joint Authors

Zheng, Leyi
Tang, Longkun

Source

Complexity

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-02-03

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Philosophy

Abstract EN

We focus on the node-based epidemic modeling for networks, introduce the propagation medium, and propose a node-based Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model with infective media.

Theoretical investigations show that the endemic equilibrium is globally asymptotically stable.

Numerical examples of three typical network structures also verify the theoretical results.

Furthermore, comparison between network node degree and its infected percents implies that there is a strong positive correlation between both; namely, the node with bigger degree is infected with more percents.

Finally, we discuss the impact of the epidemic spreading rate of media as well as the effective recovered rate on the network average infected state.

Theoretical and numerical results show that (1) network average infected percents go up (down) with the increase of the infected rate of media (the effective recovered rate); (2) the infected rate of media has almost no influence on network average infected percents for the fully connected network and NW small-world network; (3) network average infected percents decrease exponentially with the increase of the effective recovered rate, implying that the percents can be controlled at low level by an appropriate large effective recovered rate.

American Psychological Association (APA)

Zheng, Leyi& Tang, Longkun. 2019. A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks. Complexity،Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1131282

Modern Language Association (MLA)

Zheng, Leyi& Tang, Longkun. A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks. Complexity No. 2019 (2019), pp.1-14.
https://search.emarefa.net/detail/BIM-1131282

American Medical Association (AMA)

Zheng, Leyi& Tang, Longkun. A Node-Based SIRS Epidemic Model with Infective Media on Complex Networks. Complexity. 2019. Vol. 2019, no. 2019, pp.1-14.
https://search.emarefa.net/detail/BIM-1131282

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1131282