The role of super-spreaders in modeling of SARS-CoV-2
(2022) In Infectious Disease Modelling 7(4). p.778-794- Abstract
In stochastic modeling of infectious diseases, it has been established that variations in infectivity affect the probability of a major outbreak, but not the shape of the curves during a major outbreak, which is predicted by deterministic models (Diekmann et al., 2012). However, such conclusions are derived under idealized assumptions such as the population size tending to infinity, and the individual degree of infectivity only depending on variations in the infectiousness period. In this paper we show that the same conclusions hold true in a finite population representing a medium size city, where the degree of infectivity is determined by the offspring distribution, which we try to make as realistic as possible for SARS-CoV-2. In... (More)
In stochastic modeling of infectious diseases, it has been established that variations in infectivity affect the probability of a major outbreak, but not the shape of the curves during a major outbreak, which is predicted by deterministic models (Diekmann et al., 2012). However, such conclusions are derived under idealized assumptions such as the population size tending to infinity, and the individual degree of infectivity only depending on variations in the infectiousness period. In this paper we show that the same conclusions hold true in a finite population representing a medium size city, where the degree of infectivity is determined by the offspring distribution, which we try to make as realistic as possible for SARS-CoV-2. In particular, we consider distributions with fat tails, to incorporate the existence of super-spreaders. We also provide new theoretical results on convergence of stochastic models which allows to incorporate any offspring distribution with a finite variance.
(Less)
- author
- Rousse, François ; Carlsson, Marcus LU ; Ögren, Magnus and Wellander, Benjamin Kalischer
- organization
- publishing date
- 2022-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Compartmental models, COVID-19, Offspring distribution for SARS-CoV-2, SEIR, SIR
- in
- Infectious Disease Modelling
- volume
- 7
- issue
- 4
- pages
- 17 pages
- publisher
- KeAi Communications Co.
- external identifiers
-
- pmid:36267691
- scopus:85142435236
- ISSN
- 2468-0427
- DOI
- 10.1016/j.idm.2022.10.003
- language
- English
- LU publication?
- yes
- id
- caf01865-ee3d-4034-ad5e-1524fbd0d914
- date added to LUP
- 2022-12-27 09:45:52
- date last changed
- 2025-03-08 00:26:22
@article{caf01865-ee3d-4034-ad5e-1524fbd0d914,
abstract = {{<p>In stochastic modeling of infectious diseases, it has been established that variations in infectivity affect the probability of a major outbreak, but not the shape of the curves during a major outbreak, which is predicted by deterministic models (Diekmann et al., 2012). However, such conclusions are derived under idealized assumptions such as the population size tending to infinity, and the individual degree of infectivity only depending on variations in the infectiousness period. In this paper we show that the same conclusions hold true in a finite population representing a medium size city, where the degree of infectivity is determined by the offspring distribution, which we try to make as realistic as possible for SARS-CoV-2. In particular, we consider distributions with fat tails, to incorporate the existence of super-spreaders. We also provide new theoretical results on convergence of stochastic models which allows to incorporate any offspring distribution with a finite variance.</p>}},
author = {{Rousse, François and Carlsson, Marcus and Ögren, Magnus and Wellander, Benjamin Kalischer}},
issn = {{2468-0427}},
keywords = {{Compartmental models; COVID-19; Offspring distribution for SARS-CoV-2; SEIR; SIR}},
language = {{eng}},
number = {{4}},
pages = {{778--794}},
publisher = {{KeAi Communications Co.}},
series = {{Infectious Disease Modelling}},
title = {{The role of super-spreaders in modeling of SARS-CoV-2}},
url = {{http://dx.doi.org/10.1016/j.idm.2022.10.003}},
doi = {{10.1016/j.idm.2022.10.003}},
volume = {{7}},
year = {{2022}},
}