Complexity

Epidemic Spreading Dynamics on Temporal Networks


Publishing date
01 Apr 2022
Status
Closed
Submission deadline
26 Nov 2021

1Sichuan University, Chengdu, China

2Deakin University, Victoria, Australia

3Chongqing University of Posts and Telecommunications, Chongqing, China

This issue is now closed for submissions.
More articles will be published in the near future.

Epidemic Spreading Dynamics on Temporal Networks

This issue is now closed for submissions.
More articles will be published in the near future.

Description

Complex networks are widely used to describe many real-world systems. They can be used in social, biological, and technical systems. The network topologies severely affect the phenomena of nonlinear dynamics of epidemiological and digital epidemiological. Extensive real-data analyses revealed that the network topology varies with time and should be described as temporal networks rather than static networks.

To uncover and understand the effects of network temporality on spatio-temporal evolving patterns, critical phenomena, and phase transitions of networked epidemic spreading is a very hot challenge in network science. Developing some data-driven epidemic spreading models that consider the network temporality and dynamical characters simultaneously is critical. Moreover, some advanced theoretical analysis methods should be developed to help investigate the spreading dynamics. Based on the previous two aspects, the control approaches for epidemic spreading on temporal networks are worthy of further study.

This Special Issue aims to provide theoretical and empirical investigations about the epidemic spreading dynamics on temporal networks. We highly encourage original research and review articles from different disciplines, including biology, physics, computer science, mathematics, and sociology.

Potential topics include but are not limited to the following:

  • Deterministic/stochastic model of epidemic spreading on temporal networks
  • Data-driven model for epidemic spreading on temporal networks
  • Source identification on temporal networks
  • Influential maximization on temporal networks
  • New theoretical approaches for epidemic spreading on temporal networks
  • Critical phenomena and phase transitions of epidemic spreading on temporal networks
  • Dynamical analysis of epidemic spreading on temporal networks
  • Optimal temporal network topology for epidemic spreading
  • Controlling epidemic spreading on temporal networks
  • Modelling epidemic spreading on temporal networks with distinct mechanisms

Articles

  • Special Issue
  • - Volume 2022
  • - Article ID 6221181
  • - Research Article

Quantitative Analysis of COVID-19 Pandemic Responses Based on an Improved SEIR-SD Model

Yang Liu | Bingrui Liu | ... | Jia Liu
  • Special Issue
  • - Volume 2022
  • - Article ID 6176451
  • - Research Article

Analysis of Factors Influencing Stock Market Volatility Based on GARCH-MIDAS Model

Dan Ma | Tianxing Yang | ... | Yi He
  • Special Issue
  • - Volume 2021
  • - Article ID 2069010
  • - Research Article

A Study on the Topic-Sentiment Evolution and Diffusion in Time Series of Public Opinion Derived from Emergencies

Meng Cai | Han Luo | Ying Cui
  • Special Issue
  • - Volume 2021
  • - Article ID 1015049
  • - Research Article

The Evolution Model of Public Risk Perception Based on Pandemic Spreading Theory under Perspective of COVID-19

Yi-Cheng Zhang | Zhi Li | ... | Jia-Bao Liu
  • Special Issue
  • - Volume 2021
  • - Article ID 1805651
  • - Research Article

Analysis of a Tuberculosis Infection Model considering the Influence of Saturated Recovery (Treatment)

Fatima Sulayman | Farah Aini Abdullah
  • Special Issue
  • - Volume 2021
  • - Article ID 7181431
  • - Research Article

Cascading Failure Dynamics against Intentional Attack for Interdependent Industrial Internet of Things

Hao Peng | Zhen Qian | ... | Jianmin Han
  • Special Issue
  • - Volume 2021
  • - Article ID 8015191
  • - Research Article

Information Spreading on Memory Activity-Driven Temporal Networks

Linfeng Zhong | Yu Bai | ... | Weijun Pan
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Acceptance rate28%
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Article of the Year Award: Outstanding research contributions of 2021, as selected by our Chief Editors. Read the winning articles.