Four-tier response system and spatial propagation of COVID-19 in China by a network model
In order to investigate the effectiveness of lockdown and social distancing restrictions, which have been widely carried out as policy choice to curb the ongoing COVID-19 pandemic around the world, we formulate and discuss a staged and weighted network system based on a classical SEAIR epidemiologic...
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| Veröffentlicht in: | Mathematical biosciences 2020-12, Vol.330, p.108484-108484, Article 108484 |
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| creator | Ge, Jing He, Daihai Lin, Zhigui Zhu, Huaiping Zhuang, Zian |
| description | In order to investigate the effectiveness of lockdown and social distancing restrictions, which have been widely carried out as policy choice to curb the ongoing COVID-19 pandemic around the world, we formulate and discuss a staged and weighted network system based on a classical SEAIR epidemiological model. Five stages have been taken into consideration according to four-tier response to Public Health Crisis, which comes from the National Contingency Plan in China. Staggered basic reproduction number has been derived and we evaluate the effectiveness of lockdown and social distancing policies under different scenarios among 19 cities/regions in mainland China. Further, we estimate the infection risk associated with the sequential release based on population mobility between cities and the intensity of some non-pharmaceutical interventions. Our results reveal that Level I public health emergency response is necessary for high-risk cities, which can flatten the COVID-19 curve effectively and quickly. Moreover, properly designed staggered-release policies are extremely significant for the prevention and control of COVID-19, furthermore, beneficial to economic activities and social stability and development.
•Uses a weighted networked model for COVID-19 with four-tier response to Public Health Crisis.•Analyzes and evaluates the effectiveness of lockdown and social distancing in different levels.•Staggered-release policies should be properly designed for different stages of epidemic. |
| doi_str_mv | 10.1016/j.mbs.2020.108484 |
| format | Article |
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He, Daihai ; Lin, Zhigui ; Zhu, Huaiping ; Zhuang, Zian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c479t-987c6329d29b9bfeb843f48e46c619a6a578fea9b5032abedac4201b48a2fb13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Basic reproduction number</topic><topic>Basic Reproduction Number - statistics & numerical data</topic><topic>Betacoronavirus</topic><topic>Biostatistics</topic><topic>China - epidemiology</topic><topic>Cities</topic><topic>Cities - epidemiology</topic><topic>Cities - statistics & numerical data</topic><topic>Computer Simulation</topic><topic>Contingency</topic><topic>Control stability</topic><topic>Coronavirus Infections - epidemiology</topic><topic>Coronavirus Infections - prevention & control</topic><topic>Coronavirus Infections - transmission</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>COVID-19 pandemic</topic><topic>Disease control</topic><topic>Emergency preparedness</topic><topic>Emergency response</topic><topic>Epidemic models</topic><topic>Epidemiology</topic><topic>Four-tier response system</topic><topic>Graph Laplacian operator</topic><topic>Health risks</topic><topic>Humans</topic><topic>Lockdown</topic><topic>Models, Statistical</topic><topic>Network model</topic><topic>Original</topic><topic>Pandemics</topic><topic>Pandemics - prevention & control</topic><topic>Pandemics - statistics & numerical data</topic><topic>Pneumonia, Viral - epidemiology</topic><topic>Pneumonia, Viral - prevention & control</topic><topic>Pneumonia, Viral - transmission</topic><topic>Policies</topic><topic>Public Health</topic><topic>Public Policy</topic><topic>Quarantine - methods</topic><topic>SARS-CoV-2</topic><topic>Social distancing</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ge, Jing</creatorcontrib><creatorcontrib>He, Daihai</creatorcontrib><creatorcontrib>Lin, Zhigui</creatorcontrib><creatorcontrib>Zhu, Huaiping</creatorcontrib><creatorcontrib>Zhuang, Zian</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Ecology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Mathematical biosciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ge, Jing</au><au>He, Daihai</au><au>Lin, Zhigui</au><au>Zhu, Huaiping</au><au>Zhuang, Zian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Four-tier response system and spatial propagation of COVID-19 in China by a network model</atitle><jtitle>Mathematical biosciences</jtitle><addtitle>Math Biosci</addtitle><date>2020-12-01</date><risdate>2020</risdate><volume>330</volume><spage>108484</spage><epage>108484</epage><pages>108484-108484</pages><artnum>108484</artnum><issn>0025-5564</issn><eissn>1879-3134</eissn><abstract>In order to investigate the effectiveness of lockdown and social distancing restrictions, which have been widely carried out as policy choice to curb the ongoing COVID-19 pandemic around the world, we formulate and discuss a staged and weighted network system based on a classical SEAIR epidemiological model. Five stages have been taken into consideration according to four-tier response to Public Health Crisis, which comes from the National Contingency Plan in China. Staggered basic reproduction number has been derived and we evaluate the effectiveness of lockdown and social distancing policies under different scenarios among 19 cities/regions in mainland China. Further, we estimate the infection risk associated with the sequential release based on population mobility between cities and the intensity of some non-pharmaceutical interventions. Our results reveal that Level I public health emergency response is necessary for high-risk cities, which can flatten the COVID-19 curve effectively and quickly. Moreover, properly designed staggered-release policies are extremely significant for the prevention and control of COVID-19, furthermore, beneficial to economic activities and social stability and development.
•Uses a weighted networked model for COVID-19 with four-tier response to Public Health Crisis.•Analyzes and evaluates the effectiveness of lockdown and social distancing in different levels.•Staggered-release policies should be properly designed for different stages of epidemic.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>33039365</pmid><doi>10.1016/j.mbs.2020.108484</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Mathematical biosciences, 2020-12, Vol.330, p.108484-108484, Article 108484 |
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| subjects | Basic reproduction number Basic Reproduction Number - statistics & numerical data Betacoronavirus Biostatistics China - epidemiology Cities Cities - epidemiology Cities - statistics & numerical data Computer Simulation Contingency Control stability Coronavirus Infections - epidemiology Coronavirus Infections - prevention & control Coronavirus Infections - transmission Coronaviruses COVID-19 COVID-19 pandemic Disease control Emergency preparedness Emergency response Epidemic models Epidemiology Four-tier response system Graph Laplacian operator Health risks Humans Lockdown Models, Statistical Network model Original Pandemics Pandemics - prevention & control Pandemics - statistics & numerical data Pneumonia, Viral - epidemiology Pneumonia, Viral - prevention & control Pneumonia, Viral - transmission Policies Public Health Public Policy Quarantine - methods SARS-CoV-2 Social distancing |
| title | Four-tier response system and spatial propagation of COVID-19 in China by a network model |
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