Dynamical SPQEIR model assesses the effectiveness of non-pharmaceutical interventions against COVID-19 epidemic outbreaks.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2021
Historique:
received: 27 08 2020
accepted: 10 05 2021
entrez: 21 5 2021
pubmed: 22 5 2021
medline: 3 6 2021
Statut: epublish

Résumé

Against the current COVID-19 pandemic, governments worldwide have devised a variety of non-pharmaceutical interventions to mitigate it. However, it is generally difficult to estimate the joint impact of different control strategies. In this paper, we tackle this question with an extended epidemic SEIR model, informed by a socio-political classification of different interventions. First, we inquire the conceptual effect of mitigation parameters on the infection curve. Then, we illustrate the potential of our model to reproduce and explain empirical data from a number of countries, to perform cross-country comparisons. This gives information on the best synergies of interventions to control epidemic outbreaks while minimising impact on socio-economic needs. For instance, our results suggest that, while rapid and strong lockdown is an effective pandemic mitigation measure, a combination of social distancing and early contact tracing can achieve similar mitigation synergistically, while keeping lower isolation rates. This quantitative understanding can support the establishment of mid- and long-term interventions, to prepare containment strategies against further outbreaks. This paper also provides an online tool that allows researchers and decision makers to interactively simulate diverse scenarios with our model.

Identifiants

pubmed: 34019589
doi: 10.1371/journal.pone.0252019
pii: PONE-D-20-26921
pmc: PMC8139462
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0252019

Déclaration de conflit d'intérêts

The authors declare no competing interests.

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Auteurs

Daniele Proverbio (D)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Françoise Kemp (F)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Stefano Magni (S)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Andreas Husch (A)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Atte Aalto (A)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Laurent Mombaerts (L)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Alexander Skupin (A)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Jorge Gonçalves (J)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Jose Ameijeiras-Alonso (J)

Department of Mathematics, U Leuven, Leuven, Belgium.

Christophe Ley (C)

Department of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, Belgium.

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