SIR epidemics in populations with large sub-communities

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Ball, Frank, Sirl, David, Trapman, Pieter
Format: Preprint
Publié: 2022
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866911828069580800
author Ball, Frank
Sirl, David
Trapman, Pieter
author_facet Ball, Frank
Sirl, David
Trapman, Pieter
contents We investigate final outcome properties of an SIR (susceptible $\to$ infective $\to$ recovered) epidemic model defined on a population of large sub-communities in which there is stronger disease transmission within the communities than between them. Our analysis involves approximation of the epidemic process by a chain of within-community large outbreaks spreading between the communities. We derive law of large numbers and central limit type results for the number of individuals and the number of communities affected and the so-called severity of the outbreak. These results are valid as the size of communities tends to infinity, with the number of communities either fixed or also tending to infinity. The weaker between-community connections lead to randomness even in the law of large numbers type limit. As part of our proofs we also obtain a new result concerning the rate of convergence of the expected fraction infected in a standard SIR epidemic to its large-population limit.
format Preprint
id arxiv_https___arxiv_org_abs_2204_06902
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle SIR epidemics in populations with large sub-communities
Ball, Frank
Sirl, David
Trapman, Pieter
Probability
92D30, 60F99, 60K99
We investigate final outcome properties of an SIR (susceptible $\to$ infective $\to$ recovered) epidemic model defined on a population of large sub-communities in which there is stronger disease transmission within the communities than between them. Our analysis involves approximation of the epidemic process by a chain of within-community large outbreaks spreading between the communities. We derive law of large numbers and central limit type results for the number of individuals and the number of communities affected and the so-called severity of the outbreak. These results are valid as the size of communities tends to infinity, with the number of communities either fixed or also tending to infinity. The weaker between-community connections lead to randomness even in the law of large numbers type limit. As part of our proofs we also obtain a new result concerning the rate of convergence of the expected fraction infected in a standard SIR epidemic to its large-population limit.
title SIR epidemics in populations with large sub-communities
topic Probability
92D30, 60F99, 60K99
url https://arxiv.org/abs/2204.06902