2004/02/29 by Jingzhou Liu, Yifa Tang, Zheng Yang
Biochemistry, Genetics and Molecular Biology · Mathematics · Medicine · Physics and Astronomy · #BETA (programming language) #COVID-19 epidemiological studies #Combinatorics #Complex Network Analysis Techniques #Complex network #Computer science #Cure rate #Degree distribution #Demography #Disease #Epidemic model #Infection rate #Infectious disease (medical specialty) #Internal medicine #Lambda #Limit (mathematics) #Mathematical analysis #Mathematics #Medicine #Mortality rate #Opinion Dynamics and Social Influence #Physics #Population #Power law #Quantum mechanics #Sociology #Statistical physics #Statistics #q-bio.PE
paper · pdf · doi:10.1088/1742-5468/2004/08/p08008
8 pages, submitted
arxiv created 2004/06/29 · openalex publication_date 2004/08/26 · arxiv updated 2013/02/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
We introduce a modified epidemic model on regular and scale-free networks. In this model, we consider the birth rate δ, cure rate γ, infection rate λ, and death rates α and β. Through mean-field analysis, we find that on a regular network there is an epidemic threshold λ c dependent on the parameters δ, γ, α, and β, while for a power law degree distribution network the epidemic threshold is absent in the thermodynamic limit. The result is the same as that of the standard SIS model. This reminds us that the structure of the networks plays a very important role in the spreading properties of infectious disease.