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Dynamic Analysis of an Epidemic Model Considering Personal Alert on a Complex Network
Fengling Jia1, Ziyu Gu2, Lixin Yang2
1School of Mathematics, Chengdu Normal University, Chengdu 611130, China.
Entropy (Basel, Switzerland)
|October 28, 2023
Summary
This study introduces a network-based SIQRS epidemic model incorporating individual alertness. Increased alertness reduces disease spread, while its impact on infectiousness increases it, affecting epidemic outcomes.
Area of Science:
- Epidemiology
- Mathematical Biology
- Network Science
Background:
- Epidemic modeling is crucial for understanding disease transmission dynamics.
- Complex networks provide realistic structures for studying disease spread.
- Individual behavior significantly influences epidemic trajectories.
Purpose of the Study:
- To propose and analyze a Susceptible-Infectious-Quarantined-Recovered-Susceptible (SIQRS) epidemic model on complex networks.
- To investigate the impact of individual alertness and behavior on epidemic transmission.
- To determine the stability of disease-free and endemic equilibrium points.
Main Methods:
- Development of a SIQRS compartmental model on a complex network.
- Derivation of the basic reproduction number (R0) considering vital dynamics and alertness.
- Application of stability theory to analyze equilibrium points.
- Numerical simulations to validate theoretical findings.
Main Results:
- Individual alertness negatively correlates with the basic reproduction number.
- Alertness's impact on infectiousness positively correlates with the basic reproduction number.
- Disease eradication occurs when R0 < 1; an endemic state exists when R0 > 1.
Conclusions:
- Individual behavior, specifically alertness, plays a significant role in modulating epidemic spread.
- The proposed model provides insights into disease control strategies by considering human behavior.
- Network structure and individual responses are key factors in epidemic dynamics.
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