SrasV1, Main, Exploration, bibRecord, 000856

Characteristics of COVID-19 infection in Beijing

Identifieur interne : 000856 ( Main/Exploration ); précédent : 000855; suivant : 000857

Characteristics of COVID-19 infection in Beijing

Source :

The Journal of Infection [ 0163-4453 ] ; 2020.

RBID : PMC:7102527

Descripteurs français

KwdFr :
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Enfant d'âge préscolaire, Fatigue, Femelle, Fièvre, Flambées de maladies, Humains, Infections à coronavirus (physiopathologie), Infections à coronavirus (épidémiologie), Jeune adulte, Mâle, Nourrisson, Pandémies, Pneumopathie virale (physiopathologie), Pneumopathie virale (épidémiologie), Pékin (épidémiologie), Sujet âgé, Sujet âgé de 80 ans ou plus, Syndrome respiratoire aigu sévère (épidémiologie), Toux, Études rétrospectives.
MESH :
- physiopathologie : Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Infections à coronavirus, Pneumopathie virale, Pékin, Syndrome respiratoire aigu sévère.
- Adolescent, Adulte, Adulte d'âge moyen, Enfant, Enfant d'âge préscolaire, Fatigue, Femelle, Fièvre, Flambées de maladies, Humains, Jeune adulte, Mâle, Nourrisson, Pandémies, Sujet âgé, Sujet âgé de 80 ans ou plus, Toux, Études rétrospectives.

English descriptors

KwdEn :
- Adolescent, Adult, Aged, Aged, 80 and over, Beijing (epidemiology), Betacoronavirus, Child, Child, Preschool, Coronavirus Infections (epidemiology), Coronavirus Infections (physiopathology), Cough, Disease Outbreaks, Fatigue, Female, Fever, Humans, Infant, Male, Middle Aged, Pandemics, Pneumonia, Viral (epidemiology), Pneumonia, Viral (physiopathology), Retrospective Studies, Severe Acute Respiratory Syndrome (epidemiology), Travel-Related Illness, Young Adult.
MESH :
- geographic , epidemiology : Beijing.
- epidemiology : Coronavirus Infections, Pneumonia, Viral, Severe Acute Respiratory Syndrome.
- physiopathology : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Aged, Aged, 80 and over, Betacoronavirus, Child, Child, Preschool, Cough, Disease Outbreaks, Fatigue, Female, Fever, Humans, Infant, Male, Middle Aged, Pandemics, Retrospective Studies, Travel-Related Illness, Young Adult.

Abstract

Background

Since the first case of a novel coronavirus (COVID-19) infection pneumonia was detected in Wuhan, China, a series of confirmed cases of the COVID-19 were found in Beijing. We analyzed the data of 262 confirmed cases to determine the clinical and epidemiological characteristics of COVID-19 in Beijing.

Methods

We collected patients who were transferred by Beijing Emergency Medical Service to the designated hospitals. The information on demographic, epidemiological, clinical, laboratory test for the COVID-19 virus, diagnostic classification, cluster case and outcome were obtained. Furthermore we compared the characteristics between severe and common confirmed cases which including mild cases, no-pneumonia cases and asymptomatic cases, and we also compared the features between COVID-19 and 2003 SARS.

Findings

By Feb 10, 2020, 262 patients were transferred from the hospitals across Beijing to the designated hospitals for special treatment of the COVID-19 infected by Beijing emergency medical service. Among of 262 patients, 46 (17.6%) were severe cases, 216 (82.4%) were common cases, which including 192 (73.3%) mild cases, 11(4.2%) non-pneumonia cases and 13 (5.0%) asymptomatic cases respectively. The median age of patients was 47.5 years old and 48.5% were male. 192 (73.3%) patients were residents of Beijing, 50 (26.0%) of which had been to Wuhan, 116 (60.4%) had close contact with confirmed cases, 21 (10.9%) had no contact history. The most common symptoms at the onset of illness were fever (82.1%), cough (45.8%), fatigue (26.3%), dyspnea (6.9%) and headache (6.5%). The median incubation period was 6.7 days, the interval time from between illness onset and seeing a doctor was 4.5 days. As of Feb 10, 17.2% patients have discharged and 81.7% patients remain in hospital in our study, the fatality of COVID-19 infection in Beijing was 0.9%.

Interpretation

On the basis of this study, we provided the ratio of the COVID-19 infection on the severe cases to the mild, asymptomatic and non-pneumonia cases in Beijing. Population was generally susceptible, and with a relatively low fatality rate. The measures to prevent transmission was very successful at early stage, the next steps on the COVID-19 infection should be focused on early isolation of patients and quarantine for close contacts in families and communities in Beijing.

Funding

Beijing Municipal Science and Technology Commission and Ministry of Science and Technology.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7102527

DOI: 10.1016/j.jinf.2020.02.018
PubMed: 32112886
PubMed Central: 7102527

Affiliations:

Le document en format XML

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<author><name sortKey="Zhang, Jinjun" sort="Zhang, Jinjun" uniqKey="Zhang J" first="Jinjun" last="Zhang">Jinjun Zhang</name>
<affiliation wicri:level="3"><nlm:aff id="aff0001">Beijing Emergency Medicine Research Institute, Beijing Emergency Medical Center, Beijing, China</nlm:aff>
<country xml:lang="fr">République populaire de Chine</country>
<wicri:regionArea>Beijing Emergency Medicine Research Institute, Beijing Emergency Medical Center, Beijing</wicri:regionArea>
<placeName><settlement type="city">Pékin</settlement>
</placeName>
</affiliation>
</author>
</analytic>
<series><title level="j">The Journal of Infection</title>
<idno type="ISSN">0163-4453</idno>
<idno type="eISSN">1532-2742</idno>
<imprint><date when="2020">2020</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Beijing (epidemiology)</term>
<term>Betacoronavirus</term>
<term>Child</term>
<term>Child, Preschool</term>
<term>Coronavirus Infections (epidemiology)</term>
<term>Coronavirus Infections (physiopathology)</term>
<term>Cough</term>
<term>Disease Outbreaks</term>
<term>Fatigue</term>
<term>Female</term>
<term>Fever</term>
<term>Humans</term>
<term>Infant</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
<term>Pneumonia, Viral (epidemiology)</term>
<term>Pneumonia, Viral (physiopathology)</term>
<term>Retrospective Studies</term>
<term>Severe Acute Respiratory Syndrome (epidemiology)</term>
<term>Travel-Related Illness</term>
<term>Young Adult</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adolescent</term>
<term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Enfant</term>
<term>Enfant d'âge préscolaire</term>
<term>Fatigue</term>
<term>Femelle</term>
<term>Fièvre</term>
<term>Flambées de maladies</term>
<term>Humains</term>
<term>Infections à coronavirus (physiopathologie)</term>
<term>Infections à coronavirus (épidémiologie)</term>
<term>Jeune adulte</term>
<term>Mâle</term>
<term>Nourrisson</term>
<term>Pandémies</term>
<term>Pneumopathie virale (physiopathologie)</term>
<term>Pneumopathie virale (épidémiologie)</term>
<term>Pékin (épidémiologie)</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
<term>Syndrome respiratoire aigu sévère (épidémiologie)</term>
<term>Toux</term>
<term>Études rétrospectives</term>
</keywords>
<keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>Beijing</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
<term>Severe Acute Respiratory Syndrome</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathologie" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
</keywords>
<keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Coronavirus Infections</term>
<term>Pneumonia, Viral</term>
</keywords>
<keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Infections à coronavirus</term>
<term>Pneumopathie virale</term>
<term>Pékin</term>
<term>Syndrome respiratoire aigu sévère</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adolescent</term>
<term>Adult</term>
<term>Aged</term>
<term>Aged, 80 and over</term>
<term>Betacoronavirus</term>
<term>Child</term>
<term>Child, Preschool</term>
<term>Cough</term>
<term>Disease Outbreaks</term>
<term>Fatigue</term>
<term>Female</term>
<term>Fever</term>
<term>Humans</term>
<term>Infant</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Pandemics</term>
<term>Retrospective Studies</term>
<term>Travel-Related Illness</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>Enfant d'âge préscolaire</term>
<term>Fatigue</term>
<term>Femelle</term>
<term>Fièvre</term>
<term>Flambées de maladies</term>
<term>Humains</term>
<term>Jeune adulte</term>
<term>Mâle</term>
<term>Nourrisson</term>
<term>Pandémies</term>
<term>Sujet âgé</term>
<term>Sujet âgé de 80 ans ou plus</term>
<term>Toux</term>
<term>Études rétrospectives</term>
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<front><div type="abstract" xml:lang="en"><sec><title>Background</title>
<p>Since the first case of a novel coronavirus (COVID-19) infection pneumonia was detected in Wuhan, China, a series of confirmed cases of the COVID-19 were found in Beijing. We analyzed the data of 262 confirmed cases to determine the clinical and epidemiological characteristics of COVID-19 in Beijing.</p>
</sec>
<sec><title>Methods</title>
<p>We collected patients who were transferred by Beijing Emergency Medical Service to the designated hospitals. The information on demographic, epidemiological, clinical, laboratory test for the COVID-19 virus, diagnostic classification, cluster case and outcome were obtained. Furthermore we compared the characteristics between severe and common confirmed cases which including mild cases, no-pneumonia cases and asymptomatic cases, and we also compared the features between COVID-19 and 2003 SARS.</p>
</sec>
<sec><title>Findings</title>
<p>By Feb 10, 2020, 262 patients were transferred from the hospitals across Beijing to the designated hospitals for special treatment of the COVID-19 infected by Beijing emergency medical service. Among of 262 patients, 46 (17.6%) were severe cases, 216 (82.4%) were common cases, which including 192 (73.3%) mild cases, 11(4.2%) non-pneumonia cases and 13 (5.0%) asymptomatic cases respectively. The median age of patients was 47.5 years old and 48.5% were male. 192 (73.3%) patients were residents of Beijing, 50 (26.0%) of which had been to Wuhan, 116 (60.4%) had close contact with confirmed cases, 21 (10.9%) had no contact history. The most common symptoms at the onset of illness were fever (82.1%), cough (45.8%), fatigue (26.3%), dyspnea (6.9%) and headache (6.5%). The median incubation period was 6.7 days, the interval time from between illness onset and seeing a doctor was 4.5 days. As of Feb 10, 17.2% patients have discharged and 81.7% patients remain in hospital in our study, the fatality of COVID-19 infection in Beijing was 0.9%.</p>
</sec>
<sec><title>Interpretation</title>
<p>On the basis of this study, we provided the ratio of the COVID-19 infection on the severe cases to the mild, asymptomatic and non-pneumonia cases in Beijing. Population was generally susceptible, and with a relatively low fatality rate. The measures to prevent transmission was very successful at early stage, the next steps on the COVID-19 infection should be focused on early isolation of patients and quarantine for close contacts in families and communities in Beijing.</p>
</sec>
<sec><title>Funding</title>
<p>Beijing Municipal Science and Technology Commission and Ministry of Science and Technology.</p>
</sec>
</div>
</front>
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</biblStruct>
</listBibl>
</div1>
</back>
</TEI>
<affiliations><list><country><li>République populaire de Chine</li>
</country>
<settlement><li>Pékin</li>
</settlement>
</list>
<tree><country name="République populaire de Chine"><noRegion><name sortKey="Tian, Sijia" sort="Tian, Sijia" uniqKey="Tian S" first="Sijia" last="Tian">Sijia Tian</name>
</noRegion>
<name sortKey="Chen, Gang" sort="Chen, Gang" uniqKey="Chen G" first="Gang" last="Chen">Gang Chen</name>
<name sortKey="Chen, Hui" sort="Chen, Hui" uniqKey="Chen H" first="Hui" last="Chen">Hui Chen</name>
<name sortKey="Chen, Kun" sort="Chen, Kun" uniqKey="Chen K" first="Kun" last="Chen">Kun Chen</name>
<name sortKey="Hu, Nan" sort="Hu, Nan" uniqKey="Hu N" first="Nan" last="Hu">Nan Hu</name>
<name sortKey="Kang, Xuqin" sort="Kang, Xuqin" uniqKey="Kang X" first="Xuqin" last="Kang">Xuqin Kang</name>
<name sortKey="Li, Dou" sort="Li, Dou" uniqKey="Li D" first="Dou" last="Li">Dou Li</name>
<name sortKey="Li, Jianren" sort="Li, Jianren" uniqKey="Li J" first="Jianren" last="Li">Jianren Li</name>
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<name sortKey="Liu, Dong" sort="Liu, Dong" uniqKey="Liu D" first="Dong" last="Liu">Dong Liu</name>
<name sortKey="Liu, Ning" sort="Liu, Ning" uniqKey="Liu N" first="Ning" last="Liu">Ning Liu</name>
<name sortKey="Lou, Jing" sort="Lou, Jing" uniqKey="Lou J" first="Jing" last="Lou">Jing Lou</name>
<name sortKey="Niu, Shengmei" sort="Niu, Shengmei" uniqKey="Niu S" first="Shengmei" last="Niu">Shengmei Niu</name>
<name sortKey="Wang, Dali" sort="Wang, Dali" uniqKey="Wang D" first="Dali" last="Wang">Dali Wang</name>
<name sortKey="Xiang, Zhenjun" sort="Xiang, Zhenjun" uniqKey="Xiang Z" first="Zhenjun" last="Xiang">Zhenjun Xiang</name>
<name sortKey="Zhang, Jinjun" sort="Zhang, Jinjun" uniqKey="Zhang J" first="Jinjun" last="Zhang">Jinjun Zhang</name>
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</country>
</tree>
</affiliations>
</record>

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Characteristics of COVID-19 infection in Beijing

Characteristics of COVID-19 infection in Beijing

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