Epidemiology of COVID-19 and Predictors of Recovery in the Republic of Korea.
Identifieur interne : 000731 ( Main/Curation ); précédent : 000730; suivant : 000732Epidemiology of COVID-19 and Predictors of Recovery in the Republic of Korea.
Auteurs : Ashis Kumar Das [États-Unis] ; Saji Saraswathy Gopalan [États-Unis]Source :
- Pulmonary medicine [ 2090-1844 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Enfant (MeSH), Facteurs de risque (MeSH), Facteurs sexuels (MeSH), Facteurs âges (MeSH), Femelle (MeSH), Géographie médicale (MeSH), Humains (MeSH), Infections à coronavirus (mortalité), Infections à coronavirus (épidémiologie), Jeune adulte (MeSH), Modèles logistiques (MeSH), Mâle (MeSH), Pandémies (statistiques et données numériques), Pneumopathie virale (mortalité), Pneumopathie virale (épidémiologie), République de Corée (épidémiologie), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH).
- MESH :
- mortalité : Infections à coronavirus, Pneumopathie virale.
- statistiques et données numériques : Pandémies.
- épidémiologie : Infections à coronavirus, Pneumopathie virale, République de Corée.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Facteurs de risque, Facteurs sexuels, Facteurs âges, Femelle, Géographie médicale, Humains, Jeune adulte, Modèles logistiques, Mâle, Sujet âgé, Sujet âgé de 80 ans ou plus.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Factors (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Child (MeSH), Coronavirus Infections (epidemiology), Coronavirus Infections (mortality), Female (MeSH), Geography, Medical (MeSH), Humans (MeSH), Logistic Models (MeSH), Male (MeSH), Middle Aged (MeSH), Pandemics (statistics & numerical data), Pneumonia, Viral (epidemiology), Pneumonia, Viral (mortality), Republic of Korea (epidemiology), Risk Factors (MeSH), Sex Factors (MeSH), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : Republic of Korea.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- statistics & numerical data : Pandemics.
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Child, Female, Geography, Medical, Humans, Logistic Models, Male, Middle Aged, Risk Factors, Sex Factors, Young Adult.
Abstract
Background
The recent COVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery.
Objectives
To describe the epidemiology of confirmed COVID-19 patients in the Republic of Korea and identify predictors of recovery.
Materials and Methods
Using publicly available data for confirmed COVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020, to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation, and province. Correlation was tested among all predictors (sex, age group, place of exposure, and province) with Pearson's correlation coefficient. Associations between recovery from COVID-19 and predictors were estimated using a multivariable logistic regression model.
Results
Majority of the confirmed cases were females (56%), 20-29 age group (24.3%), and primarily from three provinces-Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%), and Seoul (17.1%). The case fatality ratio was 2.1%, and 41.6% cases recovered. Older patients, patients from provinces such as Daegu, Gyeonggi-do, Gyeongsangbuk-do, Jeju-do, Jeollabuk-do, and Jeollanam-do, and those contracting the disease from healthcare settings had lower recovery.
Conclusions
Our study adds to the very limited evidence base on potential predictors of recovery among confirmed COVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups.
DOI: 10.1155/2020/7291698
PubMed: 32774918
PubMed Central: PMC7395990
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over (MeSH)</term><term>Child (MeSH)</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (mortality)</term><term>Female (MeSH)</term><term>Geography, Medical (MeSH)</term><term>Humans (MeSH)</term><term>Logistic Models (MeSH)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Pandemics (statistics & numerical data)</term><term>Pneumonia, Viral (epidemiology)</term><term>Pneumonia, Viral (mortality)</term><term>Republic of Korea (epidemiology)</term><term>Risk Factors (MeSH)</term><term>Sex Factors (MeSH)</term><term>Young Adult (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent (MeSH)</term><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Enfant (MeSH)</term><term>Facteurs de risque (MeSH)</term><term>Facteurs sexuels (MeSH)</term><term>Facteurs âges (MeSH)</term><term>Femelle (MeSH)</term><term>Géographie médicale (MeSH)</term><term>Humains (MeSH)</term><term>Infections à coronavirus (mortalité)</term><term>Infections à coronavirus (épidémiologie)</term><term>Jeune adulte (MeSH)</term><term>Modèles logistiques (MeSH)</term><term>Mâle (MeSH)</term><term>Pandémies (statistiques et données numériques)</term><term>Pneumopathie virale (mortalité)</term><term>Pneumopathie virale (épidémiologie)</term><term>République de Corée (épidémiologie)</term><term>Sujet âgé (MeSH)</term><term>Sujet âgé de 80 ans ou plus (MeSH)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Republic of Korea</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="mortality" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="mortalité" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Pandemics</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Pandémies</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term><term>Pneumopathie virale</term><term>République de Corée</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Adult</term><term>Age Factors</term><term>Aged</term><term>Aged, 80 and over</term><term>Child</term><term>Female</term><term>Geography, Medical</term><term>Humans</term><term>Logistic Models</term><term>Male</term><term>Middle Aged</term><term>Risk Factors</term><term>Sex Factors</term><term>Young Adult</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adolescent</term><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Facteurs de risque</term><term>Facteurs sexuels</term><term>Facteurs âges</term><term>Femelle</term><term>Géographie médicale</term><term>Humains</term><term>Jeune adulte</term><term>Modèles logistiques</term><term>Mâle</term><term>Sujet âgé</term><term>Sujet âgé de 80 ans ou plus</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>Background</b></p><p>The recent COVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery.</p></div><div type="abstract" xml:lang="en"><p><b>Objectives</b></p><p>To describe the epidemiology of confirmed COVID-19 patients in the Republic of Korea and identify predictors of recovery.</p></div><div type="abstract" xml:lang="en"><p><b>Materials and Methods</b></p><p>Using publicly available data for confirmed COVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020, to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation, and province. Correlation was tested among all predictors (sex, age group, place of exposure, and province) with Pearson's correlation coefficient. Associations between recovery from COVID-19 and predictors were estimated using a multivariable logistic regression model.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>Majority of the confirmed cases were females (56%), 20-29 age group (24.3%), and primarily from three provinces-Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%), and Seoul (17.1%). The case fatality ratio was 2.1%, and 41.6% cases recovered. Older patients, patients from provinces such as Daegu, Gyeonggi-do, Gyeongsangbuk-do, Jeju-do, Jeollabuk-do, and Jeollanam-do, and those contracting the disease from healthcare settings had lower recovery.</p></div><div type="abstract" xml:lang="en"><p><b>Conclusions</b></p><p>Our study adds to the very limited evidence base on potential predictors of recovery among confirmed COVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32774918</PMID><DateCompleted><Year>2020</Year><Month>08</Month><Day>14</Day></DateCompleted><DateRevised><Year>2020</Year><Month>08</Month><Day>14</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">2090-1844</ISSN><JournalIssue CitedMedium="Internet"><Volume>2020</Volume><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>Pulmonary medicine</Title><ISOAbbreviation>Pulm Med</ISOAbbreviation></Journal><ArticleTitle>Epidemiology of COVID-19 and Predictors of Recovery in the Republic of Korea.</ArticleTitle><Pagination><MedlinePgn>7291698</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1155/2020/7291698</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">The recent COVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery.</AbstractText><AbstractText Label="Objectives" NlmCategory="UNASSIGNED">To describe the epidemiology of confirmed COVID-19 patients in the Republic of Korea and identify predictors of recovery.</AbstractText><AbstractText Label="Materials and Methods" NlmCategory="UNASSIGNED">Using publicly available data for confirmed COVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020, to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation, and province. Correlation was tested among all predictors (sex, age group, place of exposure, and province) with Pearson's correlation coefficient. Associations between recovery from COVID-19 and predictors were estimated using a multivariable logistic regression model.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">Majority of the confirmed cases were females (56%), 20-29 age group (24.3%), and primarily from three provinces-Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%), and Seoul (17.1%). The case fatality ratio was 2.1%, and 41.6% cases recovered. Older patients, patients from provinces such as Daegu, Gyeonggi-do, Gyeongsangbuk-do, Jeju-do, Jeollabuk-do, and Jeollanam-do, and those contracting the disease from healthcare settings had lower recovery.</AbstractText><AbstractText Label="Conclusions" NlmCategory="UNASSIGNED">Our study adds to the very limited evidence base on potential predictors of recovery among confirmed COVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups.</AbstractText><CopyrightInformation>Copyright © 2020 Ashis Kumar Das and Saji Saraswathy Gopalan.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Das</LastName><ForeName>Ashis Kumar</ForeName><Initials>AK</Initials><Identifier Source="ORCID">https://orcid.org/0000-0002-7110-9463</Identifier><AffiliationInfo><Affiliation>Research Group, The World Bank, Washington DC, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gopalan</LastName><ForeName>Saji Saraswathy</ForeName><Initials>SS</Initials><Identifier Source="ORCID">https://orcid.org/0000-0003-1766-6135</Identifier><AffiliationInfo><Affiliation>Human Development Department, The World Bank, Washington DC, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>30</Day></ArticleDate></Article><MedlineJournalInfo><Country>Egypt</Country><MedlineTA>Pulm Med</MedlineTA><NlmUniqueID>101558762</NlmUniqueID><ISSNLinking>2090-1844</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000367" MajorTopicYN="N">Age Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D062306" MajorTopicYN="N">Geography, Medical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D016015" MajorTopicYN="N">Logistic Models</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D056910" MajorTopicYN="N" Type="Geographic">Republic of Korea</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D012307" MajorTopicYN="N">Risk Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012737" MajorTopicYN="N">Sex Factors</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><CoiStatement>The authors declare that there is no conflict of interest. This particular work was conducted outside of the authors' organizational affiliations.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>07</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>07</Month><Day>23</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>8</Month><Day>11</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>8</Month><Day>15</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32774918</ArticleId><ArticleId IdType="doi">10.1155/2020/7291698</ArticleId><ArticleId IdType="pmc">PMC7395990</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>N Engl J Med. 2020 Mar 26;382(13):1199-1207</Citation><ArticleIdList><ArticleId IdType="pubmed">31995857</ArticleId></ArticleIdList></Reference><Reference><Citation>N Engl J Med. 2020 Apr 30;382(18):1708-1720</Citation><ArticleIdList><ArticleId IdType="pubmed">32109013</ArticleId></ArticleIdList></Reference><Reference><Citation>Minerva Med. 2020 Jun 02;:</Citation><ArticleIdList><ArticleId IdType="pubmed">32491297</ArticleId></ArticleIdList></Reference><Reference><Citation>Epidemiol Health. 2020;42:e2020006</Citation><ArticleIdList><ArticleId IdType="pubmed">32023775</ArticleId></ArticleIdList></Reference><Reference><Citation>J Med Virol. 2020 Apr 8;:</Citation><ArticleIdList><ArticleId IdType="pubmed">32270521</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet. 2020 Feb 15;395(10223):507-513</Citation><ArticleIdList><ArticleId IdType="pubmed">32007143</ArticleId></ArticleIdList></Reference><Reference><Citation>Osong Public Health Res Perspect. 2020 Apr;11(2):85-90</Citation><ArticleIdList><ArticleId IdType="pubmed">32257774</ArticleId></ArticleIdList></Reference><Reference><Citation>JAMA. 2020 Mar 17;:</Citation><ArticleIdList><ArticleId IdType="pubmed">32181795</ArticleId></ArticleIdList></Reference><Reference><Citation>Emerg Infect Dis. 2020 Aug;26(8):1666-1670</Citation><ArticleIdList><ArticleId IdType="pubmed">32324530</ArticleId></ArticleIdList></Reference><Reference><Citation>J Clin Virol. 2020 Jun;127:104378</Citation><ArticleIdList><ArticleId IdType="pubmed">32353762</ArticleId></ArticleIdList></Reference><Reference><Citation>Allergy. 2020 Jul;75(7):1813-1815</Citation><ArticleIdList><ArticleId IdType="pubmed">32306406</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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