Paper detail

Spreading processes in "post-epidemic" environments. II. Safety patterns on scale-free networks

This paper continues our previous study on spreading processes in inhomogeneous populations consisting of susceptible and immune individuals [V. Blavatska, Yu. Holovatch, Physica A 573, 125980 (2021)]. A special role in such populations is played by &#34;safety patterns&#34; of susceptible nodes surrounded by the immune ones. Here, we analyze spreading on scale-free networks, where the distribution of node connectivity $k$ obeys a power-law decay $\sim k^{-λ}$. We assume, that only a fraction $p$ of individual nodes can be affected by spreading process, while remaining $1-p$ are immune. We apply the synchronous cellular automaton algorithm and study the stationary states and spatial patterning in SI, SIS and SIR models in a range $2 < λ< 3 $. Two immunization scenarios, the random immunization and an intentional one, that targets the highest degrees nodes are considered. A distribution of safety patterns is obtained for the case of both scenarios. Estimates for the threshold values of the effective spreading rate $β_c$ as a function of active agents fraction $p$ and parameter $λ$ are obtained and efficiency of both vaccination techniques are analyzed quantitatively. The impact of the underlying network heterogeneous structure is manifest e.g. in decreasing the $β_c$ values within the random scenario as compared to corresponding values in the case of regular latticek. This result quantitatively confirms the compliency of scale-free networks for disease spreading. On contrary, the vaccination within the targeted scenario makes the complex networks much more resistant to epidemic spreading as compared with regular lattice structures.

preprint2021arXivOpen access
0citations
0reviews
0saves
Nocode
Nodataset
0institutions

Next steps

Decide what to do with this paper

Use like or dislike for the fast social read. The more specific scholarly feedback stays available below when needed.

Log in to curate

Reading frame

Keep the important context close to the paper

Keep the important signals around this paper in one place: votes, save state, collection context, reviews and the metadata you need before deciding what to do next.

Institutions

Add specific reaction

Move through the context

Research map

Open full explorer

Move through nearby people, institutions, topics and adjacent work without leaving the paper page.

Building this graph slice

BZPEER is loading the nearby papers, people, topics and institutions for this page.

Structured reviews

0 review(s)

ContributeLeave structured feedbackUse the review template when you have a concrete strength, concern or method question.Open review form

No structured reviews yet. High-signal critique starts here.

Work discussion

0 comment(s)

DiscussAdd a high-signal commentKeep quick notes, caveats and replication pointers separate from formal reviews.Open comment form

No discussion yet. The first strong comment sets the tone.