It can be dangerous to take epidemic curves of COVID-19 at face value-Reference-Cited by-同舟云学术

It can be dangerous to take epidemic curves of COVID-19 at face value

Published:2020-06 Issue:3 Volume:111 Page:397-400
ISSN:0008-4263
Container-title:Canadian Journal of Public Health
language:en
Short-container-title:Can J Public Health

Author:

Burstyn Igor^ORCID,Goldstein Neal D.,Gustafson Paul

Publisher

Springer Science and Business Media LLC

Subject

Public Health, Environmental and Occupational Health,General Medicine

Link

https://link.springer.com/content/pdf/10.17269/s41997-020-00367-6.pdf

Reference12 articles.

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2. Binsaeed, A. A., Al-Khedhairy, A. A., Mandil, et al. (2011). A validation study comparing the sensitivity and specificity of the new Dr. KSU H1N1 RT-PCR kit with real-time RT-PCR for diagnosing influenza A (H1N1). Annals of Saudi Medicine, 31(4), 351–355. https://doi.org/10.4103/0256-4947.83212.

3. Burstyn, I. Goldstein, N., Gustafson, P. (2020). Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: case study of COVID-19 in Alberta, Canada and Philadelphia, USA. BMC Medical Research Methdology (in press); OSF Preprints, doi:https://doi.org/10.31219/osf.io/qpgbk.

4. Core Team, R. (2019). R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing https://www.R-project.org/.

5. Corman, V. M., Olfert, L., Marco, K., et al. (2020). Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill, 25(3), 2000045. https://doi.org/10.2807/1560-7917.ES.2020.25.3.2000045.

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