How time-scale differences in asymptomatic and symptomatic transmission shape SARS-CoV-2 outbreak dynamics.

Asymptomatic transmission COVID-19 Epidemic dynamics SARS-COV-2

Journal

Epidemics
ISSN: 1878-0067
Titre abrégé: Epidemics
Pays: Netherlands
ID NLM: 101484711

Informations de publication

Date de publication:
03 2023
Historique:
received: 28 06 2022
revised: 07 12 2022
accepted: 24 12 2022
pubmed: 28 1 2023
medline: 3 3 2023
entrez: 27 1 2023
Statut: ppublish

Résumé

Asymptomatic and symptomatic SARS-CoV-2 infections can have different characteristic time scales of transmission. These time-scale differences can shape outbreak dynamics as well as bias population-level estimates of epidemic strength, speed, and controllability. For example, prior work focusing on the initial exponential growth phase of an outbreak found that larger time scales for asymptomatic vs. symptomatic transmission can lead to under-estimates of the basic reproduction number as inferred from epidemic case data. Building upon this work, we use a series of nonlinear epidemic models to explore how differences in asymptomatic and symptomatic transmission time scales can lead to changes in the realized proportion of asymptomatic transmission throughout an epidemic. First, we find that when asymptomatic transmission time scales are longer than symptomatic transmission time scales, then the effective proportion of asymptomatic transmission increases as total incidence decreases. Moreover, these time-scale-driven impacts on epidemic dynamics are enhanced when infection status is correlated between infector and infectee pairs (e.g., due to dose-dependent impacts on symptoms). Next we apply these findings to understand the impact of time-scale differences on populations with age-dependent assortative mixing and in which the probability of having a symptomatic infection increases with age. We show that if asymptomatic generation intervals are longer than corresponding symptomatic generation intervals, then correlations between age and symptoms lead to a decrease in the age of infection during periods of epidemic decline (whether due to susceptible depletion or intervention). Altogether, these results demonstrate the need to explore the role of time-scale differences in transmission dynamics alongside behavioral changes to explain outbreak features both at early stages (e.g., in estimating the basic reproduction number) and throughout an epidemic (e.g., in connecting shifts in the age of infection to periods of changing incidence).

Identifiants

pubmed: 36706626
pii: S1755-4365(22)00104-9
doi: 10.1016/j.epidem.2022.100664
pmc: PMC9830934
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

100664

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Jeremy D Harris (JD)

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA. Electronic address: jeremy.harris@gatech.edu.

Sang Woo Park (SW)

Department of Ecology and Evolutionary Biology, Princeton, NJ, USA. Electronic address: swp2@princeton.edu.

Jonathan Dushoff (J)

Department of Biology, McMaster University, Hamilton, Ontario, Canada; Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, Canada; M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada. Electronic address: dushoff@mcmaster.ca.

Joshua S Weitz (JS)

School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA; School of Physics, Georgia Institute of Technology, Atlanta, GA, USA; Institut de Biologie, École Normale Supérieure, Paris, France. Electronic address: jsweitz@gatech.edu.

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