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      Impact of intervention methods on COVID-19 transmission in Shenzhen

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          Abstract

          By March 31, 2020, COVID-19 had spread to more than 200 countries. Over 750,000 confirmed cases were reported, leading to more than 36,000 deaths. In this study, we analysed the efficiency of various intervention strategies to prevent infection by the virus, SARS-CoV-2, using an agent-based SEIIR model, in the fully urbanised city of Shenzhen, Guangdong Province, China. Shortening the duration from symptom onset to hospital admission, quarantining recent arrivals from Hubei Province, and letting symptomatic individuals stay at home were found to be the three most important interventions to reduce the risk of infection in Shenzhen. The ideal time window for a mandatory quarantine of arrivals from Hubei Province was between 10 January and January 17, 2020, while the ideal time window for local intervention strategies was between 15 and 22 January. The risk of infection could have been reduced by 50% if all symptomatic individuals had immediately gone to hospital for isolation, and by 35% if a 14-day quarantine for arrivals from Hubei Province had been introduced one week earlier. Intervention strategies implemented in Shenzhen were effective, and the spread of infection would be controlled even if the initial basic reproduction number had doubled. Our results may be useful for other cities when choosing their intervention strategies to prevent outbreaks of COVID-19.

          Highlights

          • Shortening the delay to hospital is the most effective intervention in Shenzhen.

          • 10 to 17 January is the best time for a mandatory quarantine of Hubei's arrivals.

          • 15 to 22 January is the best time for local intervention strategy in Shenzhen.

          • Work/school closure and mask wearing are effective interventions in other countries.

          • Airport screening is not very effective.

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          Most cited references27

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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

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            Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia

            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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              The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application

              Background: A novel human coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was identified in China in December 2019. There is limited support for many of its key epidemiologic features, including the incubation period for clinical disease (coronavirus disease 2019 [COVID-19]), which has important implications for surveillance and control activities. Objective: To estimate the length of the incubation period of COVID-19 and describe its public health implications. Design: Pooled analysis of confirmed COVID-19 cases reported between 4 January 2020 and 24 February 2020. Setting: News reports and press releases from 50 provinces, regions, and countries outside Wuhan, Hubei province, China. Participants: Persons with confirmed SARS-CoV-2 infection outside Hubei province, China. Measurements: Patient demographic characteristics and dates and times of possible exposure, symptom onset, fever onset, and hospitalization. Results: There were 181 confirmed cases with identifiable exposure and symptom onset windows to estimate the incubation period of COVID-19. The median incubation period was estimated to be 5.1 days (95% CI, 4.5 to 5.8 days), and 97.5% of those who develop symptoms will do so within 11.5 days (CI, 8.2 to 15.6 days) of infection. These estimates imply that, under conservative assumptions, 101 out of every 10 000 cases (99th percentile, 482) will develop symptoms after 14 days of active monitoring or quarantine. Limitation: Publicly reported cases may overrepresent severe cases, the incubation period for which may differ from that of mild cases. Conclusion: This work provides additional evidence for a median incubation period for COVID-19 of approximately 5 days, similar to SARS. Our results support current proposals for the length of quarantine or active monitoring of persons potentially exposed to SARS-CoV-2, although longer monitoring periods might be justified in extreme cases. Primary Funding Source: U.S. Centers for Disease Control and Prevention, National Institute of Allergy and Infectious Diseases, National Institute of General Medical Sciences, and Alexander von Humboldt Foundation.
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                Author and article information

                Contributors
                Journal
                Build Environ
                Build Environ
                Building and Environment
                Published by Elsevier Ltd.
                0360-1323
                1873-684X
                2 July 2020
                August 2020
                2 July 2020
                : 180
                : 107106
                Affiliations
                [a ]Department of Mechanical Engineering, The University of Hong Kong, Hong Kong SAR, China
                [b ]Zhejiang Institute of Research and Innovation, The University of Hong Kong, Lin An, Zhejiang, China
                [c ]Department of Building Science, Tsinghua University, Beijing, China
                [d ]School of Public Health, Zhejiang University, Hangzhou, China
                [e ]Beijing Baidu Netcom Science Technology Co., Ltd., Baidu Campus, Shangdi 10th Street, Beijing, China
                [f ]China Electric Power Planning & Engineering Institute, Beijing, China
                [g ]School of Energy and Environment, Southeast University, Nanjing, China
                Author notes
                []Corresponding author. Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China. liyg@ 123456hku.hk
                Article
                S0360-1323(20)30481-9 107106
                10.1016/j.buildenv.2020.107106
                7331564
                32834417
                9a159984-d6ba-416a-9364-ee665dc9c633
                © 2020 Published by Elsevier Ltd.

                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
                : 3 May 2020
                : 10 June 2020
                : 26 June 2020
                Categories
                Article

                covid-19,infection spread,close contact,agent-based model,seir model

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