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      A conceptual model for the outbreak of Coronavirus disease 2019 (COVID-19) in Wuhan, China with individual reaction and governmental action

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          Highlights

          • •

            For the ongoing novel coronavirus disease (CODID-19) outbreak in Wuhan, China, the Chinese government has implemented control measures such as city lockdown to mitigate the impact of the epidemic.

          • •

            We model the outbreak in Wuhan with individual reaction and governmental action (holiday extension, city lockdown, hospitalisation and quarantine) based on some parameters of the 1918 influenza pandemic in London, United Kingdom.

          • •

            We show the different effects of individual reaction and governmental action and preliminarily estimate the magnitude of these effects.

          • •

            We also preliminarily estimate the time-varying reporting ratio.

          Abstract

          The ongoing Coronavirus Disease 2019 (COVID-19) outbreak, originated in the end of 2019 in Wuhan, China, has claimed more than 2200 lives and posed a huge threat to global public health. The Chinese government has implemented control measures including setting up special hospitals and travel restriction to mitigate the spread. We propose conceptual models for the outbreak in Wuhan with the consideration of individual behavioural reaction and governmental actions, e.g., holiday extension, travel restriction, hospitalisation and quarantine. We employed the estimates of these two key components from the 1918 influenza pandemic in London, United Kingdom, incorporated zoonotic introductions and the emigration, then computed future trends and the reporting ratio. The model is concise in structure, and it successfully captures the course of the COVID-19 outbreak, and thus sheds light on understanding the trends of the outbreak.

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          Most cited references15

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          Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China

          Chaolin Huang, Yeming Wang, Xingwang Li … (2020)
          Summary Background A recent cluster of pneumonia cases in Wuhan, China, was caused by a novel betacoronavirus, the 2019 novel coronavirus (2019-nCoV). We report the epidemiological, clinical, laboratory, and radiological characteristics and treatment and clinical outcomes of these patients. Methods All patients with suspected 2019-nCoV were admitted to a designated hospital in Wuhan. We prospectively collected and analysed data on patients with laboratory-confirmed 2019-nCoV infection by real-time RT-PCR and next-generation sequencing. Data were obtained with standardised data collection forms shared by WHO and the International Severe Acute Respiratory and Emerging Infection Consortium from electronic medical records. Researchers also directly communicated with patients or their families to ascertain epidemiological and symptom data. Outcomes were also compared between patients who had been admitted to the intensive care unit (ICU) and those who had not. Findings By Jan 2, 2020, 41 admitted hospital patients had been identified as having laboratory-confirmed 2019-nCoV infection. Most of the infected patients were men (30 [73%] of 41); less than half had underlying diseases (13 [32%]), including diabetes (eight [20%]), hypertension (six [15%]), and cardiovascular disease (six [15%]). Median age was 49·0 years (IQR 41·0–58·0). 27 (66%) of 41 patients had been exposed to Huanan seafood market. One family cluster was found. Common symptoms at onset of illness were fever (40 [98%] of 41 patients), cough (31 [76%]), and myalgia or fatigue (18 [44%]); less common symptoms were sputum production (11 [28%] of 39), headache (three [8%] of 38), haemoptysis (two [5%] of 39), and diarrhoea (one [3%] of 38). Dyspnoea developed in 22 (55%) of 40 patients (median time from illness onset to dyspnoea 8·0 days [IQR 5·0–13·0]). 26 (63%) of 41 patients had lymphopenia. All 41 patients had pneumonia with abnormal findings on chest CT. Complications included acute respiratory distress syndrome (12 [29%]), RNAaemia (six [15%]), acute cardiac injury (five [12%]) and secondary infection (four [10%]). 13 (32%) patients were admitted to an ICU and six (15%) died. Compared with non-ICU patients, ICU patients had higher plasma levels of IL2, IL7, IL10, GSCF, IP10, MCP1, MIP1A, and TNFα. Interpretation The 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with ICU admission and high mortality. Major gaps in our knowledge of the origin, epidemiology, duration of human transmission, and clinical spectrum of disease need fulfilment by future studies. Funding Ministry of Science and Technology, Chinese Academy of Medical Sciences, National Natural Science Foundation of China, and Beijing Municipal Science and Technology Commission.
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            Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention

            Zunyou Wu, Jennifer M. McGoogan (2020)
            Article 0 comments Cited 8345 times – based on 0 reviews     Review now
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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.)
              Article 0 comments Cited 7047 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Qianying Lin
                Shi Zhao
                Daozhou Gao
                Yijun Lou
                Shu Yang
                Salihu S Musa
                Maggie H Wang
                Yongli Cai
                Weiming Wang
                Lin Yang
                Daihai He
                Journal
                Journal ID (nlm-ta): Int J Infect Dis
                Journal ID (iso-abbrev): Int. J. Infect. Dis
                Title: International Journal of Infectious Diseases
                Publisher: Elsevier
                ISSN (Print): 1201-9712
                ISSN (Electronic): 1878-3511
                Publication date PMC-release: 4 March 2020
                Publication date (Electronic): 4 March 2020
                Electronic Location Identifier:
                Affiliations
                [a ]Michigan Institute for Data Science, University of Michigan, Ann Arbor, Michigan, USA
                [b ]JC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China
                [c ]Shenzhen Research Institute of Chinese University of Hong Kong, Shenzhen, China
                [d ]Mathematics and Science College, Shanghai Normal University, Shanghai, China
                [e ]Department of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China
                [f ]College of Medical Information Engineering, Chengdu University of Traditional Chinese Medicine, Chengdu, China
                [g ]School of Mathematics and Statistics, Huaiyin Normal University, Huai’an, China
                [h ]School of Nursing, Hong Kong Polytechnic University, Hong Kong, China
                Author notes
                [1]

                These authors equally contributed..

                Article
                Publisher ID: S1201-9712(20)30117-X
                DOI: 10.1016/j.ijid.2020.02.058
                PMC ID: 7102659
                PubMed ID: 32145465
                SO-VID: 9d1f7b59-6b9e-4ce4-b619-8f1f6fe1f854
                Copyright © © 2020 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 31 January 2020
                Date revision received : 26 February 2020
                Date accepted : 27 February 2020
                Categories
                Subject: Article

                ScienceOpen disciplines: Infectious disease & Microbiology
                Keywords: covid-19,epidemic,mathematical modelling,individual reaction,governmental action,city lock-down
                Data availability:
                ScienceOpen disciplines: Infectious disease & Microbiology
                Keywords: covid-19, epidemic, mathematical modelling, individual reaction, governmental action, city lock-down

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