Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study
Objective To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.Design Descriptive and modelling study based on surveillance data of COVID-19 in Beijing.Setting Outbreak in Be...
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| Format: | Article |
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BMJ Publishing Group
2021-09-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/11/9/e047227.full |
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| author | Ke Ma Xin Lin Lin Zhao Na Jia Jingyuan Wang Xiaoming Cui Yuhao Zhou Runze Ye Jia-Fu Jiang Baogui Jiang Zhang Xiong HongHao Shi Wuchun Cao |
| author_facet | Ke Ma Xin Lin Lin Zhao Na Jia Jingyuan Wang Xiaoming Cui Yuhao Zhou Runze Ye Jia-Fu Jiang Baogui Jiang Zhang Xiong HongHao Shi Wuchun Cao |
| author_sort | Ke Ma |
| collection | DOAJ |
| description | Objective To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.Design Descriptive and modelling study based on surveillance data of COVID-19 in Beijing.Setting Outbreak in Beijing.Participants The database included 335 confirmed cases of COVID-19.Methods To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.Results We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.Conclusions The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection. |
| format | Article |
| id | doaj-art-a15d688fa09e4a2693a8e5d1c33c3b88 |
| institution | OA Journals |
| issn | 2044-6055 |
| language | English |
| publishDate | 2021-09-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-a15d688fa09e4a2693a8e5d1c33c3b882025-08-20T02:18:27ZengBMJ Publishing GroupBMJ Open2044-60552021-09-0111910.1136/bmjopen-2020-047227Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling studyKe Ma0Xin Lin1Lin Zhao2Na Jia3Jingyuan Wang4Xiaoming Cui5Yuhao Zhou6Runze Ye7Jia-Fu Jiang8Baogui Jiang9Zhang Xiong10HongHao Shi11Wuchun Cao12State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaMenzies Institute for Medical Research, University of Tasmania, Hobart, Tasmania, AustraliaDepartment of Pharmacology, School of Pharmacy, China Medical University, Shenyang, ChinaState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaPeng Cheng Laboratory, Shenzhen, ChinaState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaInstitute of EcoHealth, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, ChinaepidemiologistState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaMOE Engineering Research Center of ACAT, School of Computer Science and Engineering, Beihang University, Beijing, ChinaSchool of Computer Science and Engineering, Beihang University, Beijing, ChinaState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Academy of Military Medical Sciences, Beijing, ChinaObjective To evaluate epidemiological characteristics and transmission dynamics of COVID-19 outbreak resurged in Beijing and to assess the effects of three non-pharmaceutical interventions.Design Descriptive and modelling study based on surveillance data of COVID-19 in Beijing.Setting Outbreak in Beijing.Participants The database included 335 confirmed cases of COVID-19.Methods To conduct spatiotemporal analyses of the outbreak, we collected individual records on laboratory-confirmed cases of COVID-19 from 11 June 2020 to 5 July 2020 in Beijing, and visitor flow and products transportation data of Xinfadi Wholesale Market. We also built a modified susceptible-exposed-infected-removed model to investigate the effect of interventions deployed in Beijing.Results We found that the staff working in the market (52.2%) and the people around 10 km to this epicentre (72.5%) were most affected, and the population mobility entering-exiting Xinfadi Wholesale Market significantly contributed to the spread of COVID-19 (p=0.021), but goods flow of the market had little impact on the virus spread (p=0.184). The prompt identification of Xinfadi Wholesale Market as the infection source could have avoided a total of 25 708 (95% CI 13 657 to 40 625) cases if unnoticed transmission lasted for a month. Based on the model, we found that active screening on targeted population by nucleic acid testing alone had the most significant effect.Conclusions The non-pharmaceutical interventions deployed in Beijing, including localised lockdown, close-contact tracing and community-based testing, were proved to be effective enough to contain the outbreak. Beijing has achieved an optimal balance between epidemic containment and economic protection.https://bmjopen.bmj.com/content/11/9/e047227.full |
| spellingShingle | Ke Ma Xin Lin Lin Zhao Na Jia Jingyuan Wang Xiaoming Cui Yuhao Zhou Runze Ye Jia-Fu Jiang Baogui Jiang Zhang Xiong HongHao Shi Wuchun Cao Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study BMJ Open |
| title | Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study |
| title_full | Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study |
| title_fullStr | Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study |
| title_full_unstemmed | Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study |
| title_short | Transmission dynamics and the effects of non-pharmaceutical interventions in the COVID-19 outbreak resurged in Beijing, China: a descriptive and modelling study |
| title_sort | transmission dynamics and the effects of non pharmaceutical interventions in the covid 19 outbreak resurged in beijing china a descriptive and modelling study |
| url | https://bmjopen.bmj.com/content/11/9/e047227.full |
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