Fleeing lockdown and its impact on the size of epidemic outbreaks in the source and target regions - a COVID-19 lesson.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
29 04 2021
Historique:
received: 14 09 2020
accepted: 08 04 2021
entrez: 30 4 2021
pubmed: 1 5 2021
medline: 8 5 2021
Statut: epublish

Résumé

The COVID-19 pandemic forced authorities worldwide to implement moderate to severe restrictions in order to slow down or suppress the spread of the disease. It has been observed in several countries that a significant number of people fled a city or a region just before strict lockdown measures were implemented. This behavior carries the risk of seeding a large number of infections all at once in regions with otherwise small number of cases. In this work, we investigate the effect of fleeing on the size of an epidemic outbreak in the region under lockdown, and also in the region of destination. We propose a mathematical model that is suitable to describe the spread of an infectious disease over multiple geographic regions. Our approach is flexible to characterize the transmission of different viruses. As an example, we consider the COVID-19 outbreak in Italy. Projection of different scenarios shows that (i) timely and stricter intervention could have significantly lowered the number of cumulative cases in Italy, and (ii) fleeing at the time of lockdown possibly played a minor role in the spread of the disease in the country.

Identifiants

pubmed: 33927224
doi: 10.1038/s41598-021-88204-9
pii: 10.1038/s41598-021-88204-9
pmc: PMC8085000
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

9233

Subventions

Organisme : Hessisches Ministerium für Wissenschaft und Kunst (Hessen State Ministry of Higher Education, Research and the Arts)
ID : CMMS
Organisme : Emberi Eroforrások Minisztériuma (Ministry of Human Capacities)
ID : EFOP-3.6.2-16-2017- 00015
Organisme : Nemzeti Kutatási, Fejlesztésiés Innovációs Hivatal (NKFI Office)
ID : NKFIH PD 128363
Organisme : Nemzeti Kutatási, Fejlesztésiés Innovációs Hivatal (NKFI Office)
ID : FK 124016
Organisme : Nemzeti Kutatási, Fejlesztésiés Innovációs Hivatal (NKFI Office)
ID : KKP 129877

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Auteurs

Maria Vittoria Barbarossa (MV)

Frankfurt Institute for Advanced Studies, 60438, Frankfurt, Germany. barbarossa@fias.uni-frankfurt.de.
Interdisciplinary Center for Scientific Computing, 69120, Heidelberg, Germany. barbarossa@fias.uni-frankfurt.de.

Norbert Bogya (N)

Bolyai Institute, University of Szeged, Szeged, 6720, Hungary.

Attila Dénes (A)

Bolyai Institute, University of Szeged, Szeged, 6720, Hungary.

Gergely Röst (G)

Bolyai Institute, University of Szeged, Szeged, 6720, Hungary.

Hridya Vinod Varma (HV)

Interdisciplinary Center for Scientific Computing, 69120, Heidelberg, Germany.

Zsolt Vizi (Z)

Bolyai Institute, University of Szeged, Szeged, 6720, Hungary.

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