A novel epidemic model considering demographics and intercity commuting on complex dynamical networks
Research output: Contribution to journal › Article › Scientific › peer-review
|Number of pages||21|
|Journal||Applied Mathematics and Computation|
|Publication status||Published - 2020|
|Publication type||A1 Journal article-refereed|
In order to characterize the impact of demographics and intercity commuting between cities on epidemic propagation, we propose a novel two-city epidemic model, where the spreading process is depicted by using SIR (susceptible-infected-recovered) model. The infectious diseases can spread in two cities at the same time, and be taken from one city to the other through intercity commuters. Firstly, we take use of the spectral analysis method to obtain the basic reproduction number R0 of the model. Then, the equilibria including the endemic equilibrium and disease-free one of the proposed model are analyzed and calculated, and the results indicate that they are globally asymptotic stable. Moreover, the degree distribution of the population changes over time, forming a complex dynamical networks before the system reaches a steady state. Finally, through a large number of numerical simulations, we show that demographics, intercity commuting rates and exposed individuals during commuting have great effects on the epidemic spreading behavior between two cities. The analysis of the proposed model can further help to understand the transmission behavior of epidemics in reality, and it is also of great practical significance to predict the epidemic trends among cities and design effective measures to curb the infectious diseases.