Analyzing the epidemiological outbreak of COVID-19: A visual exploratory data analysis approach.
Identifieur interne : 000713 ( PubMed/Curation ); précédent : 000712; suivant : 000714Analyzing the epidemiological outbreak of COVID-19: A visual exploratory data analysis approach.
Auteurs : Samrat K. Dey [Bangladesh] ; Md Mahbubur Rahman [Bangladesh] ; Umme R. Siddiqi [Bangladesh] ; Arpita Howlader [Bangladesh]Source :
- Journal of medical virology [ 1096-9071 ] ; 2020.
Abstract
There is an obvious concern globally regarding the fact about the emerging coronavirus 2019 novel coronavirus (2019-nCoV) as a worldwide public health threat. As the outbreak of COVID-19 causes by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) progresses within China and beyond, rapidly available epidemiological data are needed to guide strategies for situational awareness and intervention. The recent outbreak of pneumonia in Wuhan, China, caused by the SARS-CoV-2 emphasizes the importance of analyzing the epidemiological data of this novel virus and predicting their risks of infecting people all around the globe. In this study, we present an effort to compile and analyze epidemiological outbreak information on COVID-19 based on the several open datasets on 2019-nCoV provided by the Johns Hopkins University, World Health Organization, Chinese Center for Disease Control and Prevention, National Health Commission, and DXY. An exploratory data analysis with visualizations has been made to understand the number of different cases reported (confirmed, death, and recovered) in different provinces of China and outside of China. Overall, at the outset of an outbreak like this, it is highly important to readily provide information to begin the evaluation necessary to understand the risks and begin containment activities.
DOI: 10.1002/jmv.25743
PubMed: 32124990
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Dey</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Dhaka International University (DIU), Dhaka, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Computer Science and Engineering, Dhaka International University (DIU), Dhaka</wicri:regionArea></affiliation></author><author><name sortKey="Rahman, Md Mahbubur" sort="Rahman, Md Mahbubur" uniqKey="Rahman M" first="Md Mahbubur" last="Rahman">Md Mahbubur Rahman</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Military Institute of Science and Technology (MIST), Mirpur Cantonment, Dhaka, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Computer Science and Engineering, Military Institute of Science and Technology (MIST), Mirpur Cantonment, Dhaka</wicri:regionArea></affiliation></author><author><name sortKey="Siddiqi, Umme R" sort="Siddiqi, Umme R" uniqKey="Siddiqi U" first="Umme R" last="Siddiqi">Umme R. 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Dey</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Dhaka International University (DIU), Dhaka, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Computer Science and Engineering, Dhaka International University (DIU), Dhaka</wicri:regionArea></affiliation></author><author><name sortKey="Rahman, Md Mahbubur" sort="Rahman, Md Mahbubur" uniqKey="Rahman M" first="Md Mahbubur" last="Rahman">Md Mahbubur Rahman</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer Science and Engineering, Military Institute of Science and Technology (MIST), Mirpur Cantonment, Dhaka, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Computer Science and Engineering, Military Institute of Science and Technology (MIST), Mirpur Cantonment, Dhaka</wicri:regionArea></affiliation></author><author><name sortKey="Siddiqi, Umme R" sort="Siddiqi, Umme R" uniqKey="Siddiqi U" first="Umme R" last="Siddiqi">Umme R. Siddiqi</name><affiliation wicri:level="1"><nlm:affiliation>Department of Physiology, Shaheed Suhrawardy Medical College (ShSMC), Dhaka, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Physiology, Shaheed Suhrawardy Medical College (ShSMC), Dhaka</wicri:regionArea></affiliation></author><author><name sortKey="Howlader, Arpita" sort="Howlader, Arpita" uniqKey="Howlader A" first="Arpita" last="Howlader">Arpita Howlader</name><affiliation wicri:level="1"><nlm:affiliation>Department of Computer and Communication Engineering, Patuakhali Science and Technology University (PSTU), Dumki, Bangladesh.</nlm:affiliation><country xml:lang="fr">Bangladesh</country><wicri:regionArea>Department of Computer and Communication Engineering, Patuakhali Science and Technology University (PSTU), Dumki</wicri:regionArea></affiliation></author></analytic><series><title level="j">Journal of medical virology</title><idno type="eISSN">1096-9071</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">There is an obvious concern globally regarding the fact about the emerging coronavirus 2019 novel coronavirus (2019-nCoV) as a worldwide public health threat. As the outbreak of COVID-19 causes by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) progresses within China and beyond, rapidly available epidemiological data are needed to guide strategies for situational awareness and intervention. The recent outbreak of pneumonia in Wuhan, China, caused by the SARS-CoV-2 emphasizes the importance of analyzing the epidemiological data of this novel virus and predicting their risks of infecting people all around the globe. In this study, we present an effort to compile and analyze epidemiological outbreak information on COVID-19 based on the several open datasets on 2019-nCoV provided by the Johns Hopkins University, World Health Organization, Chinese Center for Disease Control and Prevention, National Health Commission, and DXY. An exploratory data analysis with visualizations has been made to understand the number of different cases reported (confirmed, death, and recovered) in different provinces of China and outside of China. Overall, at the outset of an outbreak like this, it is highly important to readily provide information to begin the evaluation necessary to understand the risks and begin containment activities.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32124990</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>11</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1096-9071</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Mar</Month><Day>03</Day></PubDate></JournalIssue><Title>Journal of medical virology</Title><ISOAbbreviation>J. Med. Virol.</ISOAbbreviation></Journal><ArticleTitle>Analyzing the epidemiological outbreak of COVID-19: A visual exploratory data analysis approach.</ArticleTitle><ELocationID EIdType="doi" ValidYN="Y">10.1002/jmv.25743</ELocationID><Abstract><AbstractText>There is an obvious concern globally regarding the fact about the emerging coronavirus 2019 novel coronavirus (2019-nCoV) as a worldwide public health threat. As the outbreak of COVID-19 causes by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) progresses within China and beyond, rapidly available epidemiological data are needed to guide strategies for situational awareness and intervention. The recent outbreak of pneumonia in Wuhan, China, caused by the SARS-CoV-2 emphasizes the importance of analyzing the epidemiological data of this novel virus and predicting their risks of infecting people all around the globe. In this study, we present an effort to compile and analyze epidemiological outbreak information on COVID-19 based on the several open datasets on 2019-nCoV provided by the Johns Hopkins University, World Health Organization, Chinese Center for Disease Control and Prevention, National Health Commission, and DXY. An exploratory data analysis with visualizations has been made to understand the number of different cases reported (confirmed, death, and recovered) in different provinces of China and outside of China. 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A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382:727-733. https://doi.org/10.1056/NEJMoa2001017</Citation></Reference><Reference><Citation>Drosten C, Günther S, Preiser W, et al. Identification of a novel coronavirus associated with severe acute respiratory syndrome. N Engl J Med. 2003;348:1967-1976.</Citation></Reference><Reference><Citation>Chen Y, Liu Q, Guo D. Emerging coronaviruses: genome structure, replication, and pathogenesis. J Med Virol. 2020;92:418-423. https://doi.org/10.1002/jmv.25681</Citation></Reference><Reference><Citation>WHO. Novel Coronavirus-China January 12, 2020. http://www.who.int/csr/don/12-january-2020-novel-coronavirus-china/en/. Accessed 19 January 2020.</Citation></Reference><Reference><Citation>Hui DS, I Azhar E, Madani TA, et al. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health-the latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis. 2020;2020(91):264-266.</Citation></Reference><Reference><Citation>Lu H, Stratton CW, Tang YW. Outbreak of pneumonia of unknown etiology in Wuhan China: the mystery and the miracle. J Med Virol. 2020;92:401-402. https://doi.org/10.1002/jmv.25678</Citation></Reference><Reference><Citation>Centers for Disease Control and Prevention. 2019 Novel Coronavirus (2019-nCoV), Wuhan, China. 2019. https://www.cdc.gov/coronavirus/2019-nCoV/summary.html</Citation></Reference><Reference><Citation>Ji W, Wang W, Zhao X, Zai J, Li X. Cross-species transmission of the newly identified coronavirus 2019-nCoV. J Med Virol. 2020;92:433-440. https://doi.org/10.1002/jmv.25682</Citation></Reference><Reference><Citation>Yoo JH. The fight against the 2019-nCoV outbreak: an arduous march has just begun. J Korean Med Sci. 2020;35:e56. https://doi.org/10.3346/jkms.2020.35.e56</Citation></Reference><Reference><Citation>Gorbalenya AE, Baker SC, Baric RS, et al. Acute respiratory syndrome-related coronavirus: the species and its viruses-a statement of the Coronavirus Study Group [published online ahead of print February 11, 2020]. bioRxiv. 2020. https://doi.org/10.1101/2020.02.07.937862</Citation></Reference><Reference><Citation>Lauren G. Coronavirus COVID-19 Global Cases by Johns Hopkins CSSE January 23, 2020. https://gisanddata.maps.arcgis.com/apps/opsdashboard/index.html. Accessed 16 February 2020.</Citation></Reference></ReferenceList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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