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SARS to novel coronavirus – old lessons and new lessons
Open accessAbstract
The response to the novel coronavirus outbreak in China suggests that many of the lessons from the 2003 SARS epidemic have been implemented and the response improved as a consequence. Nevertheless some questions remain and not all lessons have been successful. The national and international response demonstrates the complex link between public health, science and politics when an outbreak threatens to impact on global economies and reputations. The unprecedented measures implemented in China are a bold attempt to control the outbreak – we need to understand their effectiveness to balance costs and benefits for similar events in the future.
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Citations
Cited by
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Environmental perspective of COVID-19
Saadat, S., Rawtani, D., & Hussain, C. M. (2020) · Science of The Total Environment · doi:10.1016/j.scitotenv.2020.138870 · Cited by 980
Can we contain the COVID-19 outbreak with the same measures as for SARS?
Wilder-Smith, A., Chiew, C. J., & Lee, V. J. (2020) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(20)30129-8 · Cited by 954
False negative of RT‐PCR and prolonged nucleic acid conversion in COVID‐19: Rather than recurrence
Xiao, A. T., Tong, Y. X., & Zhang, S. (2020) · Journal of Medical Virology · doi:10.1002/jmv.25855 · Cited by 522
D-dimer level in COVID-19 infection: a systematic review
Rostami, M., & Mansouritorghabeh, H. (2020) · Expert Review of Hematology · doi:10.1080/17474086.2020.1831383 · Cited by 382
Metadata
- Authors
- McCloskey, B., & Heymann, D. L.
- Venue
- Epidemiology and Infection
- Publisher
- Cambridge University Press (CUP)
- Published
- 2020
- Volume
- 148
- Pages
- e22-e22
- ISSN
- 0950-2688 (ISSN-L)
- 1469-4409
- OpenAlex
- W3004434564
- Cited by
- 238
- References
- 0
- FWCI
- 8.85
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
