2019
DOI: 10.1103/physreve.99.022308
|View full text |Cite
|
Sign up to set email alerts
|

Persistent spatial patterns of interacting contagions

Abstract: The spread of infectious diseases, rumors, fashions, and innovations are complex contagion processes, embedded in network and spatial contexts. While the studies in the former context are intensively expanded, the latter remains largely unexplored. In this paper, we investigate the pattern formation of an interacting contagion, where two infections, A and B, interact with each other and diffuse simultaneously in space. The contagion process for each follows the classical susceptible-infected-susceptible kineti… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
11
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 17 publications
(11 citation statements)
references
References 58 publications
0
11
0
Order By: Relevance
“…This results in relaxing of the assumptions in these models, such as disaggregating the population by geography and modeling within-geography and across-geography personal interactions [102]. Martcheva [103] developed a dynamic model from several contagion models and their possible dynamics [104,105]. They are limited to the statistical inference of parameter values from actual data [106].…”
Section: Discussionmentioning
confidence: 99%
“…This results in relaxing of the assumptions in these models, such as disaggregating the population by geography and modeling within-geography and across-geography personal interactions [102]. Martcheva [103] developed a dynamic model from several contagion models and their possible dynamics [104,105]. They are limited to the statistical inference of parameter values from actual data [106].…”
Section: Discussionmentioning
confidence: 99%
“…end if (22) if m A ≥ T and m B ≥ T then (23) Node j adopts information ℓ A with probability m A /(m A + m B ); (24) if Node j adopts information ℓ A then (25) Adding node j into queue Q B ; (26) end if (27) Node j adopts information ℓ B with probability m B /(m A + m B ); (28) if Node j adopts information ℓ B then (29) Adding node j into queue Q B ; (30) end if (31) end if (32) if m A ≥ T and m B < T then (33) Node j adopts information ℓ A with probability 1; (34) Adding node j into queue Q B ; (35) end if (36) if m A < T and m B ≥ T then (37) Node j adopts information ℓ B with probability 1; (38) Adding node j into queue Q B ; (39) end if (40) end for (41) for i � 1 to length(Q A ) do (42) Recovering node i with probability c; (43) if Node i recovers then (44) Delete…”
Section: Theoretical Analysismentioning
confidence: 99%
“…Sahneh and Scoglio [31] investigated two competing information on multiplex networks and computed the absolute-dominance and coexistence regions. When two information collaborate, i.e., if the acceptance probability for another information is enlarged when an individual accepts one information, the system exhibits a discontinuous phase transition [32][33][34]. Scholars considered another situation, asymmetric interacting, i.e., one spreading dynamic promotes the other.…”
Section: Introductionmentioning
confidence: 99%
“…A significant result revealed by Cai et al is that the phase transition may be discontinuous if the cooperative strength is large enough [16]. Chen et al further investigated the effects of network structures and dimensions on the phase diagram of cooperative spreading dynamics [17][18][19].…”
Section: Introductionmentioning
confidence: 99%