<scp>SARS</scp> ‐CoV‐2, the medical profession, ventilator beds, and mortality predictions: personal reflections of an Australian clinician
Nicholas J. Talley
Abstract
Medical Journal of AustraliaVolume 212, Issue 7 p. 302-303 Editorials SARS-CoV-2, the medical profession, ventilator beds, and mortality predictions: personal reflections of an Australian clinician Nicholas J Talley, Corresponding Author Nicholas J Talley Editor-in-Chief, Medical Journal of Australia [email protected] [email protected]Search for more papers by this author Nicholas J Talley, Corresponding Author Nicholas J Talley Editor-in-Chief, Medical Journal of Australia [email protected] [email protected]Search for more papers by this author First published: 03 April 2020 https://doi.org/10.5694/mja2.50579Citations: 10Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References 1Ferguson NM, Laydon D, Nedjati-Gilani G, et al; Imperial College COVID-19 Response Team. Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand. 16 Mar 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf (viewed Mar 2020). Google Scholar 2Hicks JL, Biddinger PD. Novel coronavirus and old lessons: preparing the health system for the pandemic. N Engl J Med 2020; https://doi.org/10.1056/nejmp2005118 [EPub ahead of print]. 10.1056/NEJMp2005118 Web of Science®Google Scholar 3Meares HDD, Jones MP. When a system breaks: a queuing theory model for the number of intensive care beds needed during the COVID-19 pandemic. Med J Aust 2020; https://www.mja.com.au/journal/2020/212/10/when-system-breaks-queuing-theory-model-number-intensive-care-beds-needed [unrevised preprint version, 26 March 2020]. 10.5694/mja2.50605 PubMedWeb of Science®Google Scholar 4Steyerberg EW. Clinical prediction models : a practical approach to development, validation, and updating. Second edition. Cham: Springer International, 2019. 10.1007/978-3-030-16399-0 Google Scholar 5Hastie T, Tibshirani R, Friedman JH. The elements of statistical learning: data mining, inference, and prediction. New York: Springer, 2001. 10.1007/978-0-387-21606-5 Google Scholar 6Steyerberg EW, Bleeker SE, Moll HA, Grobbee DE, Moons KGM. Internal and external validation of predictive models: a simulation study of bias and precision in small samples. J Clin Epidemiol 2003; 56: 441–444. 10.1016/S0895-4356(03)00047-7 PubMedWeb of Science®Google Scholar 7Beggs PJ, Zhang Y, Bambrick H, et al. The 2019 report of the MJA–Lancet Countdown on health and climate change: a turbulent year with mixed progress. Med J Aust 2019; 211: 490–491.e21. https://www.mja.com.au/journal/2019/211/11/2019-report-mja-lancet-countdown-health-and-climate-change-turbulent-year-mixed 10.5694/mja2.50405 PubMedWeb of Science®Google Scholar Citing Literature Volume212, Issue7April 2020Pages 302-303 ReferencesRelatedInformation