Rapid assessment of the risk of SARS-CoV-2 importation: case study and lessons learned.


Journal

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

Informations de publication

Date de publication:
03 2022
Historique:
received: 20 04 2020
revised: 18 12 2021
accepted: 09 02 2022
pubmed: 8 3 2022
medline: 29 3 2022
entrez: 7 3 2022
Statut: ppublish

Résumé

During the early stages of an emerging disease outbreak, governments are required to make critical decisions on how to respond, despite limited data being available to inform these decisions. Analytical risk assessment is a valuable approach to guide decision-making on travel restrictions and border measures during the early phase of an outbreak. Here we describe a rapid risk assessment framework that was developed in February 2020 to support time-critical decisions on the risk of SARS-CoV-2 importation into Australia. We briefly describe the context in which our framework was developed, the framework itself, and provide an example of the type of decision support provided to the Australian government. We then report a critical evaluation of the modelling choices made in February 2020, assessing the impact of our assumptions on estimated rates of importation, and provide a summary of "lessons learned". The framework presented and evaluated here provides a flexible approach to rapid assessment of importation risk, of relevance to current and future pandemic scenarios.

Identifiants

pubmed: 35255398
pii: S1755-4365(22)00010-X
doi: 10.1016/j.epidem.2022.100549
pmc: PMC8865958
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

100549

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

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Auteurs

Freya M Shearer (FM)

Melbourne School of Population and Global Health, The University of Melbourne, Australia.

James Walker (J)

School of Mathematical Sciences, The University of Adelaide, Australia.

Nefel Tellioglu (N)

School of Computing and Information Systems, The University of Melbourne, Australia.

James M McCaw (JM)

Melbourne School of Population and Global Health, The University of Melbourne, Australia; Peter Doherty Institute for Infection and Immunity, The Royal Melbourne Hospital and The University of Melbourne, Australia; School of Mathematics and Statistics, The University of Melbourne, Australia.

Jodie McVernon (J)

Melbourne School of Population and Global Health, The University of Melbourne, Australia; Peter Doherty Institute for Infection and Immunity, The Royal Melbourne Hospital and The University of Melbourne, Australia; Murdoch Childrens Research Institute, The Royal Children's Hospital, Australia.

Andrew Black (A)

School of Mathematical Sciences, The University of Adelaide, Australia.

Nicholas Geard (N)

School of Computing and Information Systems, The University of Melbourne, Australia; Peter Doherty Institute for Infection and Immunity, The Royal Melbourne Hospital and The University of Melbourne, Australia. Electronic address: ngeard@unimelb.edu.au.

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Classifications MeSH