[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].
Identifieur interne : 000074 ( PubMed/Curation ); précédent : 000073; suivant : 000075[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].
Auteurs : X C Dong [République populaire de Chine] ; J M Li [République populaire de Chine] ; J Y Bai [République populaire de Chine] ; Z Q Liu [République populaire de Chine] ; P H Zhou [République populaire de Chine] ; L. Gao [République populaire de Chine] ; X Y Li [République populaire de Chine] ; Y. Zhang [République populaire de Chine]Source :
- Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi [ 0254-6450 ] ; 2020.
Abstract
Objective: To investigate the clinical and epidemiological characteristics of 135 confirmed cases of COVID-19 in Tianjin. Methods: The clinical and epidemiological data of 135 cases of COVID-19 in Tianjin were collected, and the data were analyzed with descriptive method. The factors influencing the severity of the illness were analyzed. Results: Among the 135 COVID-19 cases, 72 were males and 63 were females, the age of the cases was (48.62±16.83) years, and the case fatality rate was 2.22%. Local transmission caused 74.81% of the cases. A total of 33 clusters occurred, involving 85.92% of all COVID-19 cases. The median of the incubation period of COVID-19 was 6.50 days, the average generation interval was 5 days, and the household secondary transmission rate was 20.46%. Fever was the main symptom (78.63%), followed by cough (56.48%). Multivariate regression analysis indicated that age (OR=1.038, 95%CI: 1.010-1.167) and the number of chronic underlying diseases (OR=1.709, 95%CI: 1.052-2.777) were the risk factors of severe illness. Conclusions: Fever was the main symptom at the early phase of COVID-19 in Tianjin, and the local cluster cases accounted for high proportion in confirmed COVID-19 cases reported in Tianjin. Severe illness was prone to occur in people with old age and multi underlying diseases. Strict isolation of close contacts and intensive care of high-risk groups are the main measures to reduce the morbidity and case fatality of COVID-19.
DOI: 10.3760/cma.j.cn112338-20200221-00146
PubMed: 32164400
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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].</title><author><name sortKey="Dong, X C" sort="Dong, X C" uniqKey="Dong X" first="X C" last="Dong">X C Dong</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Li, J M" sort="Li, J M" uniqKey="Li J" first="J M" last="Li">J M Li</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Bai, J Y" sort="Bai, J Y" uniqKey="Bai J" first="J Y" last="Bai">J Y Bai</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Liu, Z Q" sort="Liu, Z Q" uniqKey="Liu Z" first="Z Q" last="Liu">Z Q Liu</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Zhou, P H" sort="Zhou, P H" uniqKey="Zhou P" first="P H" last="Zhou">P H Zhou</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Gao, L" sort="Gao, L" uniqKey="Gao L" first="L" last="Gao">L. Gao</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Li, X Y" sort="Li, X Y" uniqKey="Li X" first="X Y" last="Li">X Y Li</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Zhang, Y" sort="Zhang, Y" uniqKey="Zhang Y" first="Y" last="Zhang">Y. Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32164400</idno><idno type="pmid">32164400</idno><idno type="doi">10.3760/cma.j.cn112338-20200221-00146</idno><idno type="wicri:Area/PubMed/Corpus">000074</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000074</idno><idno type="wicri:Area/PubMed/Curation">000074</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Curation">000074</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].</title><author><name sortKey="Dong, X C" sort="Dong, X C" uniqKey="Dong X" first="X C" last="Dong">X C Dong</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Li, J M" sort="Li, J M" uniqKey="Li J" first="J M" last="Li">J M Li</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Bai, J Y" sort="Bai, J Y" uniqKey="Bai J" first="J Y" last="Bai">J Y Bai</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Liu, Z Q" sort="Liu, Z Q" uniqKey="Liu Z" first="Z Q" last="Liu">Z Q Liu</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Zhou, P H" sort="Zhou, P H" uniqKey="Zhou P" first="P H" last="Zhou">P H Zhou</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Gao, L" sort="Gao, L" uniqKey="Gao L" first="L" last="Gao">L. Gao</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Li, X Y" sort="Li, X Y" uniqKey="Li X" first="X Y" last="Li">X Y Li</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author><author><name sortKey="Zhang, Y" sort="Zhang, Y" uniqKey="Zhang Y" first="Y" last="Zhang">Y. Zhang</name><affiliation wicri:level="1"><nlm:affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011</wicri:regionArea></affiliation></author></analytic><series><title level="j">Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi</title><idno type="ISSN">0254-6450</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"><b>Objective:</b> To investigate the clinical and epidemiological characteristics of 135 confirmed cases of COVID-19 in Tianjin. <b>Methods:</b> The clinical and epidemiological data of 135 cases of COVID-19 in Tianjin were collected, and the data were analyzed with descriptive method. The factors influencing the severity of the illness were analyzed. <b>Results:</b> Among the 135 COVID-19 cases, 72 were males and 63 were females, the age of the cases was (48.62±16.83) years, and the case fatality rate was 2.22%. Local transmission caused 74.81% of the cases. A total of 33 clusters occurred, involving 85.92% of all COVID-19 cases. The median of the incubation period of COVID-19 was 6.50 days, the average generation interval was 5 days, and the household secondary transmission rate was 20.46%. Fever was the main symptom (78.63%), followed by cough (56.48%). Multivariate regression analysis indicated that age (<i>OR</i>=1.038, 95%<i>CI</i>: 1.010-1.167) and the number of chronic underlying diseases (<i>OR</i>=1.709, 95%<i>CI</i>: 1.052-2.777) were the risk factors of severe illness. <b>Conclusions:</b> Fever was the main symptom at the early phase of COVID-19 in Tianjin, and the local cluster cases accounted for high proportion in confirmed COVID-19 cases reported in Tianjin. Severe illness was prone to occur in people with old age and multi underlying diseases. Strict isolation of close contacts and intensive care of high-risk groups are the main measures to reduce the morbidity and case fatality of COVID-19.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32164400</PMID><DateRevised><Year>2020</Year><Month>03</Month><Day>13</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Print">0254-6450</ISSN><JournalIssue CitedMedium="Print"><Volume>41</Volume><Issue>5</Issue><PubDate><Year>2020</Year><Month>Mar</Month><Day>13</Day></PubDate></JournalIssue><Title>Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi</Title><ISOAbbreviation>Zhonghua Liu Xing Bing Xue Za Zhi</ISOAbbreviation></Journal><ArticleTitle>[Epidemiological characteristics of confirmed COVID-19 cases in Tianjin].</ArticleTitle><Pagination><MedlinePgn>638-642</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.3760/cma.j.cn112338-20200221-00146</ELocationID><Abstract><AbstractText><b>Objective:</b> To investigate the clinical and epidemiological characteristics of 135 confirmed cases of COVID-19 in Tianjin. <b>Methods:</b> The clinical and epidemiological data of 135 cases of COVID-19 in Tianjin were collected, and the data were analyzed with descriptive method. The factors influencing the severity of the illness were analyzed. <b>Results:</b> Among the 135 COVID-19 cases, 72 were males and 63 were females, the age of the cases was (48.62±16.83) years, and the case fatality rate was 2.22%. Local transmission caused 74.81% of the cases. A total of 33 clusters occurred, involving 85.92% of all COVID-19 cases. The median of the incubation period of COVID-19 was 6.50 days, the average generation interval was 5 days, and the household secondary transmission rate was 20.46%. Fever was the main symptom (78.63%), followed by cough (56.48%). Multivariate regression analysis indicated that age (<i>OR</i>=1.038, 95%<i>CI</i>: 1.010-1.167) and the number of chronic underlying diseases (<i>OR</i>=1.709, 95%<i>CI</i>: 1.052-2.777) were the risk factors of severe illness. <b>Conclusions:</b> Fever was the main symptom at the early phase of COVID-19 in Tianjin, and the local cluster cases accounted for high proportion in confirmed COVID-19 cases reported in Tianjin. Severe illness was prone to occur in people with old age and multi underlying diseases. Strict isolation of close contacts and intensive care of high-risk groups are the main measures to reduce the morbidity and case fatality of COVID-19.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Dong</LastName><ForeName>X C</ForeName><Initials>XC</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>J M</ForeName><Initials>JM</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bai</LastName><ForeName>J Y</ForeName><Initials>JY</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Z Q</ForeName><Initials>ZQ</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhou</LastName><ForeName>P H</ForeName><Initials>PH</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gao</LastName><ForeName>L</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>X Y</ForeName><Initials>XY</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Y</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Tianjin Centers for Diseases Control and Prevention, Tianjin 300011, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>chi</Language><GrantList CompleteYN="Y"><Grant><GrantID>2017ZX10103007-002</GrantID><Agency>National Science and Technology Major Project of China</Agency><Country></Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D004740">English Abstract</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>13</Day></ArticleDate></Article><MedlineJournalInfo><Country>China</Country><MedlineTA>Zhonghua Liu Xing Bing Xue Za Zhi</MedlineTA><NlmUniqueID>8208604</NlmUniqueID><ISSNLinking>0254-6450</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><OtherAbstract Type="Publisher" Language="chi"><AbstractText><b>目的：</b> 探讨天津市135例新型冠状病毒肺炎（COVID-19）确诊病例临床及流行病学特征。 <b>方法：</b> 收集天津市135例COVID-19确诊病例的临床及流行病学资料，对数据进行描述性分析，并对病情严重程度影响因素进行分析。 <b>结果：</b> 135例病例中，男性72例，女性63例，年龄（48.62±16.83）岁，病死率为2.22%。74.81%的病例感染来源为本地传播。共发生33起聚集性疫情，涉及的病例占全部病例的85.92%。疾病的中位潜伏期为6.50 d，代间距平均为5.00 d，家庭内续发率为20.46%。发热的病例占比78.63%，其次为咳嗽56.48%；多因素回归分析显示年龄（<i>OR</i>＝1.038，95%<i>CI</i>：1.010～1.167）、慢性基础性疾病病种数（<i>OR</i>＝1.709，95%<i>CI</i>：1.052～2.777）是重症的危险因素。 <b>结论：</b> 天津市COVID-19病例早期以发热为主，本地聚集性疫情为确诊病例的主要构成，高年龄、有多种基础性疾病的人群容易转为重症，对密切接触者严格隔离及加强高危人群的救治是降低发病率和病死率的主要措施。.</AbstractText></OtherAbstract><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">COVID-19</Keyword><Keyword MajorTopicYN="N">Epidemiological characteristics</Keyword><Keyword MajorTopicYN="N">Outbreak</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>3</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>3</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>3</Month><Day>14</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32164400</ArticleId><ArticleId IdType="doi">10.3760/cma.j.cn112338-20200221-00146</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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