From severe acute respiratory syndrome-associated coronavirus to 2019 novel coronavirus outbreak: similarities in the early epidemics and prediction of future trends

Several days later, seven medical staff members in the department that treated these patients developed symptoms. The incidence among medical staff in the respiratory care department of a university affiliated hospital in Guangzhou was 61.7% (29/47), that is, more than half of the medical staff were...

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Bibliographic Details
Published in:Chinese medical journal 2020-05, Vol.133 (9), p.1112-1114
Main Authors: Chen, Ze-Liang, Zhang, Wen-Jun, Lu, Yi, Guo, Cheng, Guo, Zhong-Min, Liao, Cong-Hui, Zhang, Xi, Zhang, Yi, Han, Xiao-Hu, Li, Qian-Lin, Lu, Jia-Hai
Format: Article
Language:English
Subjects:
Betacoronavirus
Coronavirus Infections - epidemiology
Coronavirus Infections - transmission
Coronaviruses
COVID-19
Disease Outbreaks
Disease transmission
Epidemics
Festivals
Hospitals
Humans
Infections
Infectious diseases
Medical personnel
Pandemics
Pathogens
Patients
Pneumonia
Pneumonia, Viral - epidemiology
Pneumonia, Viral - transmission
SARS-CoV-2
Severe Acute Respiratory Syndrome - epidemiology
Trends
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Summary:Several days later, seven medical staff members in the department that treated these patients developed symptoms. The incidence among medical staff in the respiratory care department of a university affiliated hospital in Guangzhou was 61.7% (29/47), that is, more than half of the medical staff were infected while treating their patients. According to the case numbers and the developmental characteristics, the SARS epidemic can be roughly divided into four stages: stage 1, from November 16, 2002 to January 31, 2003; stage 2, from February 1 to March 2, 2003; stage 3, from March 3 to April 2; and stage 4, after April 4 [Supplementary Figure 2D, http://links.lww.com/CM9/A209]. Because we are now in the early stage of the outbreak, we must be prepared for subsequent larger-scale outbreaks and predict the scale of the outbreak. Since 2019-nCoV is highly similar to SARS-CoV, some important characteristics of SARS-CoV could be used for this prediction.
ISSN:0366-6999
2542-5641
DOI:10.1097/CM9.0000000000000776