Modelling the initial epidemic trends of COVID-19 in Italy, Spain, Germany, and France.
Identifieur interne : 000E10 ( Main/Corpus ); précédent : 000E09; suivant : 000E11Modelling the initial epidemic trends of COVID-19 in Italy, Spain, Germany, and France.
Auteurs : Kai Wang ; Lin Ding ; Yu Yan ; Chengguqiu Dai ; Minghan Qu ; Dong Jiayi ; Xingjie HaoSource :
- PloS one [ 1932-6203 ] ; 2020.
English descriptors
- KwdEn :
- Betacoronavirus (isolation & purification), COVID-19 (MeSH), Coronavirus Infections (diagnosis), Coronavirus Infections (epidemiology), Coronavirus Infections (virology), Disease Outbreaks (MeSH), France (epidemiology), Germany (epidemiology), Humans (MeSH), Italy (epidemiology), Models, Theoretical (MeSH), Pandemics (MeSH), Pneumonia, Viral (diagnosis), Pneumonia, Viral (epidemiology), Pneumonia, Viral (virology), SARS-CoV-2 (MeSH), Spain (epidemiology).
- MESH :
- geographic , epidemiology : France, Germany, Italy, Spain.
- diagnosis : Coronavirus Infections, Pneumonia, Viral.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- isolation & purification : Betacoronavirus.
- virology : Coronavirus Infections, Pneumonia, Viral.
- COVID-19, Disease Outbreaks, Humans, Models, Theoretical, Pandemics, SARS-CoV-2.
Abstract
The Coronavirus Disease 2019 (COVID-19) has fast spread to over 200 countries and regions worldwide since its outbreak, while in March, Europe became the emerging epicentre. In this study, we aimed to model the epidemic trends and estimate the essential epidemic features of COVID-19 in Italy, Spain, Germany, and France at the initial stage. The numbers of daily confirmed cases and total confirmed cases were extracted from the Coronavirus disease (COVID-19) situation reports of WHO. We applied an extended Susceptible-Exposed-Infectious-Removed (SEIR) model to fit the epidemic trend and estimated corresponding epidemic features. The transmission rate estimates were 1.67 (95% credible interval (CrI), 1.64-1.71), 2.83 (2.72-2.85), 1.91 (1.84-1.98), and 1.89 (1.82-1.96) for Italy, Spain, Germany, and France, corresponding to the basic reproduction numbers (R0) 3.44 (3.35-3.54), 6.25 (5.97-6.55), 4.03 (3.84-4.23), and 4.00 (3.82-4.19), respectively. We found Spain had the lowest ascertainment rate of 0.22 (0.19-0.25), followed by France, Germany, and Italy of 0.45 (0.40-0.50), 0.46 (0.40-0.52), and 0.59 (0.55-0.64). The peaks of daily new confirmed cases would reach on April 16, April 5, April 21, and April 19 for Italy, Spain, Germany, and France if no action was taken by the authorities. Given the high transmissibility and high covertness of COVID-19, strict countermeasures, such as national lockdown and social distancing, were essential to be implemented to reduce the spread of the disease.
DOI: 10.1371/journal.pone.0241743
PubMed: 33166344
PubMed Central: PMC7652319
Links to Exploration step
pubmed:33166344Le document en format XML
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last="Yan">Yu Yan</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Dai, Chengguqiu" sort="Dai, Chengguqiu" uniqKey="Dai C" first="Chengguqiu" last="Dai">Chengguqiu Dai</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Qu, Minghan" sort="Qu, Minghan" uniqKey="Qu M" first="Minghan" last="Qu">Minghan Qu</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong 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Ding</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Yan, Yu" sort="Yan, Yu" uniqKey="Yan Y" first="Yu" last="Yan">Yu Yan</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Dai, Chengguqiu" sort="Dai, Chengguqiu" uniqKey="Dai C" first="Chengguqiu" last="Dai">Chengguqiu Dai</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Qu, Minghan" sort="Qu, Minghan" uniqKey="Qu M" first="Minghan" last="Qu">Minghan Qu</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Jiayi, Dong" sort="Jiayi, Dong" uniqKey="Jiayi D" first="Dong" last="Jiayi">Dong Jiayi</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author><author><name sortKey="Hao, Xingjie" sort="Hao, Xingjie" uniqKey="Hao X" first="Xingjie" last="Hao">Xingjie Hao</name><affiliation><nlm:affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</nlm:affiliation></affiliation></author></analytic><series><title level="j">PloS one</title><idno type="eISSN">1932-6203</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Betacoronavirus (isolation & purification)</term><term>COVID-19 (MeSH)</term><term>Coronavirus Infections (diagnosis)</term><term>Coronavirus Infections (epidemiology)</term><term>Coronavirus Infections (virology)</term><term>Disease Outbreaks (MeSH)</term><term>France (epidemiology)</term><term>Germany (epidemiology)</term><term>Humans (MeSH)</term><term>Italy (epidemiology)</term><term>Models, Theoretical (MeSH)</term><term>Pandemics (MeSH)</term><term>Pneumonia, Viral (diagnosis)</term><term>Pneumonia, Viral (epidemiology)</term><term>Pneumonia, Viral (virology)</term><term>SARS-CoV-2 (MeSH)</term><term>Spain (epidemiology)</term></keywords><keywords scheme="MESH" type="geographic" qualifier="epidemiology" xml:lang="en"><term>France</term><term>Germany</term><term>Italy</term><term>Spain</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" qualifier="isolation & purification" xml:lang="en"><term>Betacoronavirus</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Coronavirus Infections</term><term>Pneumonia, Viral</term></keywords><keywords scheme="MESH" xml:lang="en"><term>COVID-19</term><term>Disease Outbreaks</term><term>Humans</term><term>Models, Theoretical</term><term>Pandemics</term><term>SARS-CoV-2</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The Coronavirus Disease 2019 (COVID-19) has fast spread to over 200 countries and regions worldwide since its outbreak, while in March, Europe became the emerging epicentre. In this study, we aimed to model the epidemic trends and estimate the essential epidemic features of COVID-19 in Italy, Spain, Germany, and France at the initial stage. The numbers of daily confirmed cases and total confirmed cases were extracted from the Coronavirus disease (COVID-19) situation reports of WHO. We applied an extended Susceptible-Exposed-Infectious-Removed (SEIR) model to fit the epidemic trend and estimated corresponding epidemic features. The transmission rate estimates were 1.67 (95% credible interval (CrI), 1.64-1.71), 2.83 (2.72-2.85), 1.91 (1.84-1.98), and 1.89 (1.82-1.96) for Italy, Spain, Germany, and France, corresponding to the basic reproduction numbers (R0) 3.44 (3.35-3.54), 6.25 (5.97-6.55), 4.03 (3.84-4.23), and 4.00 (3.82-4.19), respectively. We found Spain had the lowest ascertainment rate of 0.22 (0.19-0.25), followed by France, Germany, and Italy of 0.45 (0.40-0.50), 0.46 (0.40-0.52), and 0.59 (0.55-0.64). The peaks of daily new confirmed cases would reach on April 16, April 5, April 21, and April 19 for Italy, Spain, Germany, and France if no action was taken by the authorities. Given the high transmissibility and high covertness of COVID-19, strict countermeasures, such as national lockdown and social distancing, were essential to be implemented to reduce the spread of the disease.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">33166344</PMID><DateCompleted><Year>2020</Year><Month>11</Month><Day>18</Day></DateCompleted><DateRevised><Year>2020</Year><Month>12</Month><Day>18</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><Issue>11</Issue><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS One</ISOAbbreviation></Journal><ArticleTitle>Modelling the initial epidemic trends of COVID-19 in Italy, Spain, Germany, and France.</ArticleTitle><Pagination><MedlinePgn>e0241743</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0241743</ELocationID><Abstract><AbstractText>The Coronavirus Disease 2019 (COVID-19) has fast spread to over 200 countries and regions worldwide since its outbreak, while in March, Europe became the emerging epicentre. In this study, we aimed to model the epidemic trends and estimate the essential epidemic features of COVID-19 in Italy, Spain, Germany, and France at the initial stage. The numbers of daily confirmed cases and total confirmed cases were extracted from the Coronavirus disease (COVID-19) situation reports of WHO. We applied an extended Susceptible-Exposed-Infectious-Removed (SEIR) model to fit the epidemic trend and estimated corresponding epidemic features. The transmission rate estimates were 1.67 (95% credible interval (CrI), 1.64-1.71), 2.83 (2.72-2.85), 1.91 (1.84-1.98), and 1.89 (1.82-1.96) for Italy, Spain, Germany, and France, corresponding to the basic reproduction numbers (R0) 3.44 (3.35-3.54), 6.25 (5.97-6.55), 4.03 (3.84-4.23), and 4.00 (3.82-4.19), respectively. We found Spain had the lowest ascertainment rate of 0.22 (0.19-0.25), followed by France, Germany, and Italy of 0.45 (0.40-0.50), 0.46 (0.40-0.52), and 0.59 (0.55-0.64). The peaks of daily new confirmed cases would reach on April 16, April 5, April 21, and April 19 for Italy, Spain, Germany, and France if no action was taken by the authorities. Given the high transmissibility and high covertness of COVID-19, strict countermeasures, such as national lockdown and social distancing, were essential to be implemented to reduce the spread of the disease.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Kai</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ding</LastName><ForeName>Lin</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Yan</LastName><ForeName>Yu</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Dai</LastName><ForeName>Chengguqiu</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Qu</LastName><ForeName>Minghan</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jiayi</LastName><ForeName>Dong</ForeName><Initials>D</Initials><Identifier Source="ORCID">0000-0002-2735-3653</Identifier><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hao</LastName><ForeName>Xingjie</ForeName><Initials>X</Initials><Identifier Source="ORCID">0000-0003-1535-9860</Identifier><AffiliationInfo><Affiliation>Department of Epidemiology and Biostatistics, Key Laboratory for Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>11</Month><Day>09</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="N">Betacoronavirus</DescriptorName><QualifierName UI="Q000302" MajorTopicYN="N">isolation & purification</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000086382" MajorTopicYN="N">COVID-19</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" MajorTopicYN="N">Coronavirus Infections</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004196" MajorTopicYN="N">Disease Outbreaks</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005602" MajorTopicYN="N" Type="Geographic">France</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N" Type="Geographic">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007558" MajorTopicYN="N" Type="Geographic">Italy</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000175" MajorTopicYN="Y">diagnosis</QualifierName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D000086402" MajorTopicYN="N">SARS-CoV-2</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D013030" MajorTopicYN="N" Type="Geographic">Spain</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading></MeshHeadingList><CoiStatement>The authors have declared that no competing interests exist.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>06</Month><Day>11</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>10</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>9</Day><Hour>17</Hour><Minute>13</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>10</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>20</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33166344</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0241743</ArticleId><ArticleId IdType="pii">PONE-D-20-17911</ArticleId><ArticleId IdType="pmc">PMC7652319</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Comput Methods 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