Journal article
Quantifying previous SARS-CoV-2 infection through mixture modelling of antibody levels
- Abstract:
-
As countries decide on vaccination strategies and how to ease movement restrictions, estimating the proportion of the population previously infected with SARS-CoV-2 is important for predicting the future burden of COVID-19. This proportion is usually estimated from serosurvey data in two steps: first the proportion above a threshold antibody level is calculated, then the crude estimate is adjusted using external estimates of sensitivity and specificity. A drawback of this approach is that the...
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- Publication status:
- Published
- Peer review status:
- Peer reviewed
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Bibliographic Details
- Publisher:
- Springer Nature Publisher's website
- Journal:
- Nature Communications Journal website
- Volume:
- 12
- Article number:
- 6196
- Publication date:
- 2021-10-26
- Acceptance date:
- 2021-09-17
- DOI:
- ISSN:
-
2041-1723
Item Description
- Language:
- English
- Keywords:
- Pubs id:
-
1187584
- Local pid:
- pubs:1187584
- Deposit date:
- 2021-07-27
Terms of use
- Copyright holder:
- Bottomley et al.
- Copyright date:
- 2021
- Rights statement:
- ©2021 The Author(s). 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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