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      Epidemiology and transmission of COVID-19 in 391 cases and 1286 of their close contacts in Shenzhen, China: a retrospective cohort study.

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          Abstract

          Rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, prompted heightened surveillance in Shenzhen, China. The resulting data provide a rare opportunity to measure key metrics of disease course, transmission, and the impact of control measures.

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          Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus–Infected Pneumonia in Wuhan, China

          Dawei Wang, Bo Hu, Fangfang Zhu … (2020)
          In December 2019, novel coronavirus (2019-nCoV)-infected pneumonia (NCIP) occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of affected patients is limited.
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            Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study

            Nanshan Chen, Min Zhou, Xuan Dong … (2022)
            Summary Background In December, 2019, a pneumonia associated with the 2019 novel coronavirus (2019-nCoV) emerged in Wuhan, China. We aimed to further clarify the epidemiological and clinical characteristics of 2019-nCoV pneumonia. Methods In this retrospective, single-centre study, we included all confirmed cases of 2019-nCoV in Wuhan Jinyintan Hospital from Jan 1 to Jan 20, 2020. Cases were confirmed by real-time RT-PCR and were analysed for epidemiological, demographic, clinical, and radiological features and laboratory data. Outcomes were followed up until Jan 25, 2020. Findings Of the 99 patients with 2019-nCoV pneumonia, 49 (49%) had a history of exposure to the Huanan seafood market. The average age of the patients was 55·5 years (SD 13·1), including 67 men and 32 women. 2019-nCoV was detected in all patients by real-time RT-PCR. 50 (51%) patients had chronic diseases. Patients had clinical manifestations of fever (82 [83%] patients), cough (81 [82%] patients), shortness of breath (31 [31%] patients), muscle ache (11 [11%] patients), confusion (nine [9%] patients), headache (eight [8%] patients), sore throat (five [5%] patients), rhinorrhoea (four [4%] patients), chest pain (two [2%] patients), diarrhoea (two [2%] patients), and nausea and vomiting (one [1%] patient). According to imaging examination, 74 (75%) patients showed bilateral pneumonia, 14 (14%) patients showed multiple mottling and ground-glass opacity, and one (1%) patient had pneumothorax. 17 (17%) patients developed acute respiratory distress syndrome and, among them, 11 (11%) patients worsened in a short period of time and died of multiple organ failure. Interpretation The 2019-nCoV infection was of clustering onset, is more likely to affect older males with comorbidities, and can result in severe and even fatal respiratory diseases such as acute respiratory distress syndrome. In general, characteristics of patients who died were in line with the MuLBSTA score, an early warning model for predicting mortality in viral pneumonia. Further investigation is needed to explore the applicability of the MuLBSTA score in predicting the risk of mortality in 2019-nCoV infection. Funding National Key R&D Program of China.
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              Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

              Qun Li, Xuhua Guan, Peng Wu … (2020)
              Abstract Background The initial cases of novel coronavirus (2019-nCoV)–infected pneumonia (NCIP) occurred in Wuhan, Hubei Province, China, in December 2019 and January 2020. We analyzed data on the first 425 confirmed cases in Wuhan to determine the epidemiologic characteristics of NCIP. Methods We collected information on demographic characteristics, exposure history, and illness timelines of laboratory-confirmed cases of NCIP that had been reported by January 22, 2020. We described characteristics of the cases and estimated the key epidemiologic time-delay distributions. In the early period of exponential growth, we estimated the epidemic doubling time and the basic reproductive number. Results Among the first 425 patients with confirmed NCIP, the median age was 59 years and 56% were male. The majority of cases (55%) with onset before January 1, 2020, were linked to the Huanan Seafood Wholesale Market, as compared with 8.6% of the subsequent cases. The mean incubation period was 5.2 days (95% confidence interval [CI], 4.1 to 7.0), with the 95th percentile of the distribution at 12.5 days. In its early stages, the epidemic doubled in size every 7.4 days. With a mean serial interval of 7.5 days (95% CI, 5.3 to 19), the basic reproductive number was estimated to be 2.2 (95% CI, 1.4 to 3.9). Conclusions On the basis of this information, there is evidence that human-to-human transmission has occurred among close contacts since the middle of December 2019. Considerable efforts to reduce transmission will be required to control outbreaks if similar dynamics apply elsewhere. Measures to prevent or reduce transmission should be implemented in populations at risk. (Funded by the Ministry of Science and Technology of China and others.)
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                Author and article information

                Journal
                Journal ID (iso-abbrev): Lancet Infect Dis
                Title: The Lancet. Infectious diseases
                Publisher: Elsevier BV
                ISSN (Electronic): 1474-4457
                ISSN (Print): 1473-3099
                Publication date (Electronic): August 2020
                Volume: 20
                Issue: 8
                Affiliations
                [1 ] Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
                [2 ] Department of Public Health Information, Shenzhen, China.
                [3 ] Department of Communicable Diseases Control and Prevention, Shenzhen, China.
                [4 ] School of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Artificial Intelligence Research Center, Peng Cheng Laboratory, Shenzhen, China.
                [5 ] Shenzhen Center for Disease Control and Prevention, Shenzhen, China.
                [6 ] Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
                [7 ] Artificial Intelligence Research Center, Peng Cheng Laboratory, Shenzhen, China.
                [8 ] Department of School Health, Shenzhen, China.
                [9 ] School of Computer Science, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Artificial Intelligence Research Center, Peng Cheng Laboratory, Shenzhen, China.
                [10 ] Department of Environment and Health, Shenzhen, China.
                [11 ] School of Electronic and Information Engineering, Harbin Institute of Technology at Shenzhen, Shenzhen, China; Artificial Intelligence Research Center, Peng Cheng Laboratory, Shenzhen, China. Electronic address: tma@hit.edu.cn.
                [12 ] Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: justin@jhu.edu.
                [13 ] Shenzhen Center for Disease Control and Prevention, Shenzhen, China. Electronic address: fengtiej@126.com.
                Article
                Publisher Item ID: S1473-3099(20)30287-5
                DOI: 10.1016/S1473-3099(20)30287-5
                PMC ID: 7185944
                PubMed ID: 32353347
                SO-VID: c7022eac-3965-4af6-95ea-e0ad13ec7939
                Copyright © Copyright © 2020 Elsevier Ltd. All rights reserved.
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