Projects per year
Abstract
A new epidemic model with two infection periods is developed to account for the human behavior in social network, where newly infected individuals gradually restrict most of future contacts or are quarantined, causing infectivity change from a degree-dependent form to a constant. The corresponding dynamics are formulated by a set of ordinary differential equations (ODEs) via mean-field approximation. The effects of diverse infectivity on the epidemic dynamics are examined, with a behavioral interpretation of the basic reproduction number. Results show that such simple adaptive reactions largely determine the impact of network structure on epidemics. Particularly, a theorem proposed by Lajmanovich and Yorke in 1976 is generalized, so that it can be applied for the analysis of the epidemic models with multi-compartments especially network-coupled ODE systems.
| Original language | English |
|---|---|
| Pages (from-to) | 614-621 |
| Journal | Physica A: Statistical Mechanics and its Applications |
| Volume | 468 |
| Online published | 25 Oct 2016 |
| DOIs | |
| Publication status | Published - 15 Feb 2017 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Research Keywords
- Adaptive behavior
- Basic reproduction number
- Contact network
- Infectivity
RGC Funding Information
- RGC-funded
Policy Impact
- Cited in Policy Documents
Fingerprint
Dive into the research topics of 'Effects of active links on epidemic transmission over social networks'. Together they form a unique fingerprint.Projects
- 1 Finished
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GRF: Pinning Controllability and Observability for Directed Networks of Non-identical Linear Node Systems with Multi-channel Connections
CHEN, G. (Principal Investigator / Project Coordinator)
1/01/16 → 21/11/18
Project: Research
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