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Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases
BACKGROUND: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large o...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899797/ https://www.ncbi.nlm.nih.gov/pubmed/35255823 http://dx.doi.org/10.1186/s12879-022-07180-1 |
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author | Abeysuriya, Romesh G. Delport, Dominic Stuart, Robyn M. Sacks-Davis, Rachel Kerr, Cliff C. Mistry, Dina Klein, Daniel J. Hellard, Margaret Scott, Nick |
author_facet | Abeysuriya, Romesh G. Delport, Dominic Stuart, Robyn M. Sacks-Davis, Rachel Kerr, Cliff C. Mistry, Dina Klein, Daniel J. Hellard, Margaret Scott, Nick |
author_sort | Abeysuriya, Romesh G. |
collection | PubMed |
description | BACKGROUND: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. METHODS: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. RESULTS: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. CONCLUSIONS: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07180-1. |
format | Online Article Text |
id | pubmed-8899797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88997972022-03-07 Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases Abeysuriya, Romesh G. Delport, Dominic Stuart, Robyn M. Sacks-Davis, Rachel Kerr, Cliff C. Mistry, Dina Klein, Daniel J. Hellard, Margaret Scott, Nick BMC Infect Dis Research Article BACKGROUND: In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories, but the probability that a large outbreak eventuates is not known. METHODS: We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. RESULTS: We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of > 5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. CONCLUSIONS: Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07180-1. BioMed Central 2022-03-07 /pmc/articles/PMC8899797/ /pubmed/35255823 http://dx.doi.org/10.1186/s12879-022-07180-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Abeysuriya, Romesh G. Delport, Dominic Stuart, Robyn M. Sacks-Davis, Rachel Kerr, Cliff C. Mistry, Dina Klein, Daniel J. Hellard, Margaret Scott, Nick Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title | Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title_full | Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title_fullStr | Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title_full_unstemmed | Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title_short | Preventing a cluster from becoming a new wave in settings with zero community COVID-19 cases |
title_sort | preventing a cluster from becoming a new wave in settings with zero community covid-19 cases |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8899797/ https://www.ncbi.nlm.nih.gov/pubmed/35255823 http://dx.doi.org/10.1186/s12879-022-07180-1 |
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