Epidemic trajectories and awareness diffusion among unequals in simplicial complexes

Lijin Liu (Author), Meiling Feng (Author), Chengyi Xia (Author), Dawei Zhao (Author), Matjaž Perc (Author)

Abstract

The interplay between awareness diffusion and epidemic spreading has been an active topic of research in recent years. Studies have shown that group interactions are an important consideration in contagion processes, and that thus higher-order interactions should be introduced into epidemic modeling. Research has also shown that individual responses to an unfolding epidemic are often strongly heterogeneous. We therefore present a two-layer network model, where the diffusion of awareness unfolds over 2-simplicial complexes in one layer, and the actual epidemic spreading unfolds over pairwise physical contacts in the other layer. The model takes into account individual differences in the degree of acceptance of information and self-protection measures once the epidemic is perceived. We use the micro Markov chain approach to determine the epidemic threshold of the model, which agrees well with the results obtained by Monte Carlo simulations. We show that the synergistic reinforcement due to 2-simplicial complexes in the virtual layer can restrain epidemic spreading by facilitating awareness diffusion, and moreover, that individual heterogeneity in the physical layer can increase the epidemic threshold and decrease the size of epidemic transmission. However, heterogeneity in the perception can also have the opposite effect because it inhibits the diffusion of awareness. Our results reveal the intricate interplay between awareness diffusion and epidemic spreading, and we hope they can help determine effective control measures.

Keywords

povezave višjega reda;difuzija zavedanja;širjenje epidemije;večplastna omrežja;fizika družbe;ne zaključna dela;higher-order interactions;awareness diffusion;epidemic spreading;multiplex network;social physics;

Data

Language:	English
Year of publishing:	2023
Typology:	1.01 - Original Scientific Article
Organization:	UM FNM - Faculty of Natural Sciences and Mathematics
Publisher:	Elsevier
UDC:	53
COBISS:	155884803
ISSN:	0960-0779
Views:	30
Downloads:	0
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary keywords:	Covid-19;
Type (COBISS):	Article
Pages:	9 str.
Volume:	ǂVol. ǂ173
Issue:	ǂ[article no.] ǂ113657
Chronology:	2023
DOI:	10.1016/j.chaos.2023.113657
ID:	24260416