Distribution of the COVID-19 epidemic and correlation with population emigration from wuhan, China.
Identifieur interne : 000C67 ( Ncbi/Merge ); précédent : 000C66; suivant : 000C68Distribution of the COVID-19 epidemic and correlation with population emigration from wuhan, China.
Auteurs : Ze-Liang Chen [République populaire de Chine] ; Qi Zhang [République populaire de Chine] ; Yi Lu [États-Unis] ; Zhong-Min Guo [République populaire de Chine] ; Xi Zhang [République populaire de Chine] ; Wen-Jun Zhang [République populaire de Chine] ; Cheng Guo [États-Unis] ; Cong-Hui Liao [République populaire de Chine] ; Qian-Lin Li [République populaire de Chine] ; Xiao-Hu Han [République populaire de Chine] ; Jia-Hai Lu [République populaire de Chine]Source :
- Chinese medical journal [ 2542-5641 ] ; 2020.
Abstract
The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks.
DOI: 10.1097/CM9.0000000000000782
PubMed: 32118644
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<front><div type="abstract" xml:lang="en">The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks.</div>
</front>
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<DateRevised><Year>2020</Year>
<Month>03</Month>
<Day>02</Day>
</DateRevised>
<Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">2542-5641</ISSN>
<JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year>
<Month>Feb</Month>
<Day>28</Day>
</PubDate>
</JournalIssue>
<Title>Chinese medical journal</Title>
<ISOAbbreviation>Chin. Med. J.</ISOAbbreviation>
</Journal>
<ArticleTitle>Distribution of the COVID-19 epidemic and correlation with population emigration from wuhan, China.</ArticleTitle>
<ELocationID EIdType="doi" ValidYN="Y">10.1097/CM9.0000000000000782</ELocationID>
<Abstract><AbstractText Label="BACKGROUND" NlmCategory="BACKGROUND">The ongoing new coronavirus pneumonia (Corona Virus Disease 2019, COVID-19) outbreak is spreading in China, but it has not yet reached its peak. Five million people emigrated from Wuhan before lockdown, potentially representing a source of virus infection. Determining case distribution and its correlation with population emigration from Wuhan in the early stage of the epidemic is of great importance for early warning and for the prevention of future outbreaks.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">The official case report on the COVID-19 epidemic was collected as of January 30, 2020. Time and location information on COVID-19 cases was extracted and analyzed using ArcGIS and WinBUGS software. Data on population migration from Wuhan city and Hubei province were extracted from Baidu Qianxi, and their correlation with the number of cases was analyzed.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">The COVID-19 confirmed and death cases in Hubei province accounted for 59.91% (5806/9692) and 95.77% (204/213) of the total cases in China respectively. Hot spot provinces included Sichuan and Yunnan, which are adjacent to Hubei. The time risk of Hubei province on the following day was 1.960 times that on the previous day. The number of cases in some cities was relatively low, but the time risk appeared to be continuously rising. The correlation coefficient between the provincial number of cases and emigration from Wuhan was up to 0.943. The lockdown of 17 cities in Hubei province and the implementation of nationwide control measures efficiently prevented an exponential growth in the number of cases.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The population that emigrated from Wuhan was the main infection source in other cities and provinces. Some cities with a low number of cases showed a rapid increase in case load. Owing to the upcoming Spring Festival return wave, understanding the risk trends in different regions is crucial to ensure preparedness at both the individual and organization levels and to prevent new outbreaks.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Chen</LastName>
<ForeName>Ze-Liang</ForeName>
<Initials>ZL</Initials>
<AffiliationInfo><Affiliation>One Health Center, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
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<ForeName>Qi</ForeName>
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<AffiliationInfo><Affiliation>Key Laboratory of Livestock Infectious Diseases in Northeast China, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning 110866, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Lu</LastName>
<ForeName>Yi</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Health Law, Policy and Management, School of Public Health, Boston University, Boston, MA, 02215, USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Guo</LastName>
<ForeName>Zhong-Min</ForeName>
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<AffiliationInfo><Affiliation>Animal Experiment Center, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Xi</ForeName>
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<AffiliationInfo><Affiliation>One Health Center, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Zhang</LastName>
<ForeName>Wen-Jun</ForeName>
<Initials>WJ</Initials>
<AffiliationInfo><Affiliation>Department of Biological Science and Technology, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Guo</LastName>
<ForeName>Cheng</ForeName>
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<Author ValidYN="Y"><LastName>Liao</LastName>
<ForeName>Cong-Hui</ForeName>
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<AffiliationInfo><Affiliation>One Health Center, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
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<ForeName>Qian-Lin</ForeName>
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<AffiliationInfo><Affiliation>One Health Center, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Han</LastName>
<ForeName>Xiao-Hu</ForeName>
<Initials>XH</Initials>
<AffiliationInfo><Affiliation>Key Laboratory of Livestock Infectious Diseases in Northeast China, Ministry of Education, Shenyang Agricultural University, Shenyang, Liaoning 110866, China.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Lu</LastName>
<ForeName>Jia-Hai</ForeName>
<Initials>JH</Initials>
<AffiliationInfo><Affiliation>One Health Center, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, China.</Affiliation>
</AffiliationInfo>
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<name sortKey="Liao, Cong Hui" sort="Liao, Cong Hui" uniqKey="Liao C" first="Cong-Hui" last="Liao">Cong-Hui Liao</name>
<name sortKey="Lu, Jia Hai" sort="Lu, Jia Hai" uniqKey="Lu J" first="Jia-Hai" last="Lu">Jia-Hai Lu</name>
<name sortKey="Zhang, Qi" sort="Zhang, Qi" uniqKey="Zhang Q" first="Qi" last="Zhang">Qi Zhang</name>
<name sortKey="Zhang, Wen Jun" sort="Zhang, Wen Jun" uniqKey="Zhang W" first="Wen-Jun" last="Zhang">Wen-Jun Zhang</name>
<name sortKey="Zhang, Xi" sort="Zhang, Xi" uniqKey="Zhang X" first="Xi" last="Zhang">Xi Zhang</name>
</country>
<country name="États-Unis"><noRegion><name sortKey="Lu, Yi" sort="Lu, Yi" uniqKey="Lu Y" first="Yi" last="Lu">Yi Lu</name>
</noRegion>
<name sortKey="Guo, Cheng" sort="Guo, Cheng" uniqKey="Guo C" first="Cheng" last="Guo">Cheng Guo</name>
</country>
</tree>
</affiliations>
</record>
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