Critically spanning epidemic outbreak cluster in random geometric networks

Dipa Saha, Sayantan Mitra and Ankur Sensharma

Physica A: Statistical Mechanics and its Applications, 2023, vol. 629, issue C

Abstract: The central quantity of interest in the mathematical modeling of infectious diseases is perhaps the epidemic threshold, which indicates the capability of a pathogen to infect a sizable fraction of a population. Depending on the system and the approach, this threshold can be related to different system parameters. In this study, we employ the stochastic, asynchronous susceptible–infected–recovered (SIR) model in a random geometric graph (RGG), which, by virtue of its definition, is a conspicuously suitable spatial network for analyzing epidemic spreading. We adopt a percolation approach to determine the epidemic criterion in terms of a characteristic length scale, namely, the transmission range of the pathogen. In particular, we numerically calculate the critical transmission range for which the eventual outbreak cluster spans the network. This signals a phase transition whose critical behavior suggests that it belongs to the standard percolation universality class. A direct estimate of the fractal dimension of the outbreak cluster agrees well with that obtained from the critical exponents.

Keywords: Random geometric graph; Monte Carlo methods; SIR epidemic model; Critical transmission range; Percolation; Universality class (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437123007811
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:629:y:2023:i:c:s0378437123007811

DOI: 10.1016/j.physa.2023.129226

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().