Mathematical modelling of SARS-CoV-2 variant outbreaks reveals their probability of extinction

© 2021. The Author(s)..

When a virus spreads, it may mutate into, e.g., vaccine resistant or fast spreading lineages, as was the case for the Danish Cluster-5 mink variant (belonging to the B.1.1.298 lineage), the British B.1.1.7 lineage, and the South African B.1.351 lineage of the SARS-CoV-2 virus. A way to handle such spreads is through a containment strategy, where the population in the affected area is isolated until the spread has been stopped. Under such circumstances, it is important to monitor whether the mutated virus is extinct via massive testing for the virus sub-type. If successful, the strategy will lead to lower and lower numbers of the sub-type, and it will eventually die out. An important question is, for how long time one should wait to be sure the sub-type is extinct? We use a hidden Markov model for infection spread and an approximation of a two stage sampling scheme to infer the probability of extinction. The potential of the method is illustrated via a simulation study. Finally, the model is used to assess the Danish containment strategy when SARS-CoV-2 spread from mink to man during the summer of 2020, including the Cluster-5 sub-type. In order to avoid further spread and mink being a large animal virus reservoir, this situation led to the isolation of seven municipalities in the Northern part of the country, the culling of the entire Danish 17 million large mink population, and a bill to interim ban Danish mink production until the end of 2021.

Errataetall:

ErratumIn: Sci Rep. 2022 Aug 30;12(1):14782. - PMID 36042342

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:11

Enthalten in:

Scientific reports - 11(2021), 1 vom: 30. Dez., Seite 24498

Sprache:

Englisch

Beteiligte Personen:

Schiøler, Henrik [VerfasserIn]
Knudsen, Torben [VerfasserIn]
Brøndum, Rasmus Froberg [VerfasserIn]
Stoustrup, Jakob [VerfasserIn]
Bøgsted, Martin [VerfasserIn]

Links:

Volltext

Themen:

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

Anmerkungen:

Date Completed 18.01.2022

Date Revised 30.08.2022

published: Electronic

ErratumIn: Sci Rep. 2022 Aug 30;12(1):14782. - PMID 36042342

Citation Status MEDLINE

doi:

10.1038/s41598-021-04108-8

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM335056903