A Two-Layer Network Propagation Model of Awareness Diffusion and SEIR Epidemic

doi:10.16182/j.issn1004731x.joss.21-0734

Abstract

Abstract:

In order to understand the transmission characteristics of epidemics similar to COVID-19 (coronavirus disease 2019) with obvious expose period, a two-layer network transmission model considering time-varying factors is proposed to make corresponding predictions and measures. The UAU (unaware-aware-unaware) information transmission model is used to represent the diffusion process of conscious information about epidemic. In the underlying network, the susceptible-exposed-infected- recovered (SEIR) epidemic-like transmission model with latent state is used to describe the epidemic transmission process affected by conscious information. The MMCA (microscopic Markov chain approach) is used to deduce the transmission threshold of epidemics diseases. By analyzing the key factors such as forgetting factors and infection attenuation factors, the simulation results demonstrate the effectiveness of proposed the two-layer network transmission model considering time-varying factors proposed.

Key words: two-layer network, time-varying forgetting probability, epidemic propagation, propagation threshold, awareness diffusion

CLC Number:

TP391.9

Yurong Song, Yulin Bao, Ruqi Li. A Two-Layer Network Propagation Model of Awareness Diffusion and SEIR Epidemic[J]. Journal of System Simulation, 2022, 34(11): 2437-2447.

Figures/Tables 10

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