Journal article
Optimizing COVID-19 surveillance in long-term care facilities: a modelling study
- Abstract:
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Background: Long-term care facilities (LTCFs) are vulnerable to outbreaks of coronavirus disease 2019 (COVID-19). Timely epidemiological surveillance is essential for outbreak response, but is complicated by a high proportion of silent (non-symptomatic) infections and limited testing resources.
Methods: We used a stochastic, individual-based model to simulate transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) along detaile...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Version of record, 2.1MB)
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- Publisher copy:
- 10.1186/s12916-020-01866-6
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Authors
Funding
Bibliographic Details
- Publisher:
- BMC Publisher's website
- Journal:
- BMC Medicine Journal website
- Volume:
- 18
- Issue:
- 1
- Pages:
- 386-
- Publication date:
- 2020-12-08
- Acceptance date:
- 2020-11-23
- DOI:
- EISSN:
-
1741-7015
- ISSN:
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1741-7015
- Pmid:
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33287821
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1150328
- Local pid:
- pubs:1150328
- Deposit date:
- 2020-12-29
Terms of use
- Copyright holder:
- Smith et al.
- Copyright date:
- 2020
- Rights statement:
- © The Author(s). 2020 Open Access This 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/. The Creative Commons Public Domain Dedication waiver (http://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
- Licence:
- CC Attribution (CC BY)
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