A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic.
Identifieur interne : 000443 ( PubMed/Checkpoint ); précédent : 000442; suivant : 000444A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic.
Auteurs : Ka Chun Chong [République populaire de Chine] ; Benny Chung Ying Zee [République populaire de Chine] ; Maggie Haitian Wang [République populaire de Chine]Source :
- BMC medical research methodology [ 1471-2288 ] ; 2017.
Descripteurs français
- KwdFr :
- MESH :
- physiologie : Sous-type H1N1 du virus de la grippe A.
- virologie : Grippe humaine.
- épidémiologie : Grippe humaine, Mexique.
- Algorithmes, Fonctions de vraisemblance, Humains, Modèles statistiques, Pandémies, Voyage.
English descriptors
- KwdEn :
- MESH :
- epidemiology : Influenza, Human, Mexico.
- physiology : Influenza A Virus, H1N1 Subtype.
- transmission : Influenza, Human.
- virology : Influenza, Human.
- Algorithms, Humans, Likelihood Functions, Models, Statistical, Pandemics, Travel.
Abstract
In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R 0 ), a key indicator of disease transmissibility.
DOI: 10.1186/s12874-017-0300-1
PubMed: 28222682
Affiliations:
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Ying" uniqKey="Zee B" first="Benny Chung Ying" last="Zee">Benny Chung Ying Zee</name><affiliation wicri:level="4"><nlm:affiliation>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong</wicri:regionArea><orgName type="university">Université chinoise de Hong Kong</orgName><placeName><settlement type="city">Sha Tin</settlement></placeName></affiliation></author><author><name sortKey="Wang, Maggie Haitian" sort="Wang, Maggie Haitian" uniqKey="Wang M" first="Maggie Haitian" last="Wang">Maggie Haitian Wang</name><affiliation wicri:level="4"><nlm:affiliation>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. haitian.wang@gmail.com.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong</wicri:regionArea><orgName type="university">Université chinoise de Hong Kong</orgName><placeName><settlement type="city">Sha Tin</settlement></placeName></affiliation></author></analytic><series><title level="j">BMC medical research methodology</title><idno type="eISSN">1471-2288</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Humans</term><term>Influenza A Virus, H1N1 Subtype (physiology)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (transmission)</term><term>Influenza, Human (virology)</term><term>Likelihood Functions</term><term>Mexico (epidemiology)</term><term>Models, Statistical</term><term>Pandemics</term><term>Travel</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Algorithmes</term><term>Fonctions de vraisemblance</term><term>Grippe humaine (transmission)</term><term>Grippe humaine (virologie)</term><term>Grippe humaine (épidémiologie)</term><term>Humains</term><term>Mexique (épidémiologie)</term><term>Modèles statistiques</term><term>Pandémies</term><term>Sous-type H1N1 du virus de la grippe A (physiologie)</term><term>Voyage</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Influenza, Human</term><term>Mexico</term></keywords><keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Sous-type H1N1 du virus de la grippe A</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Influenza A Virus, H1N1 Subtype</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="virologie" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Grippe humaine</term><term>Mexique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Humans</term><term>Likelihood Functions</term><term>Models, Statistical</term><term>Pandemics</term><term>Travel</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Algorithmes</term><term>Fonctions de vraisemblance</term><term>Humains</term><term>Modèles statistiques</term><term>Pandémies</term><term>Voyage</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R <sub>0</sub> ), a key indicator of disease transmissibility.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">28222682</PMID><DateCompleted><Year>2017</Year><Month>11</Month><Day>06</Day></DateCompleted><DateRevised><Year>2018</Year><Month>11</Month><Day>13</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2288</ISSN><JournalIssue CitedMedium="Internet"><Volume>17</Volume><Issue>1</Issue><PubDate><Year>2017</Year><Month>02</Month><Day>21</Day></PubDate></JournalIssue><Title>BMC medical research methodology</Title><ISOAbbreviation>BMC Med Res Methodol</ISOAbbreviation></Journal><ArticleTitle>A statistical method utilizing information of imported cases to estimate the transmissibility for an influenza pandemic.</ArticleTitle><Pagination><MedlinePgn>31</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12874-017-0300-1</ELocationID><Abstract><AbstractText Label="BACKGROUND">In a new influenza pandemic, travel data such as arrival times of cases seeded by the originating country can be regarded as a combination of the epidemic size and the mobility networks of infections connecting the originating country with other regions. It can be a complete and timely source for estimating the basic reproduction number (R <sub>0</sub> ), a key indicator of disease transmissibility.</AbstractText><AbstractText Label="METHOD">In this study, we developed a likelihood-based method using arrival times of infected cases in different countries to estimate R <sub>0</sub> for influenza pandemics. A simulation was conducted to assess the performance of the proposed method. We further applied the method to the outbreak of the influenza pandemic A/H1N1 in Mexico.</AbstractText><AbstractText Label="RESULTS">In the numerical application, the estimated R <sub>0</sub> was equal to 1.69 with a 95% confidence interval (1.65, 1.73). For the simulation results, the estimations were robust to the decline of travel rate and other parameter assumptions. Nevertheless, the estimates were moderately sensitive to the assumption of infectious duration. Generally, the findings were in line with other relevant studies.</AbstractText><AbstractText Label="CONCLUSIONS">Our approach as well as the estimate is potential to assist officials in planning control and prevention measures. Improved coordination to streamline or even centralize surveillance of imported cases among countries will thus be beneficial to public health.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Chong</LastName><ForeName>Ka Chun</ForeName><Initials>KC</Initials><Identifier Source="ORCID">0000-0001-5610-1298</Identifier><AffiliationInfo><Affiliation>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zee</LastName><ForeName>Benny Chung Ying</ForeName><Initials>BC</Initials><AffiliationInfo><Affiliation>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Maggie Haitian</ForeName><Initials>MH</Initials><AffiliationInfo><Affiliation>Division of Biostatistics, JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. haitian.wang@gmail.com.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Clinical Trials and Biostatistics Laboratory, Shenzhen Research Institute, The Chinese University of Hong Kong, Hong Kong, China. haitian.wang@gmail.com.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. 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MajorTopicYN="Y">transmission</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016013" MajorTopicYN="N">Likelihood Functions</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008800" MajorTopicYN="N">Mexico</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015233" MajorTopicYN="Y">Models, Statistical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="Y">Pandemics</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014195" MajorTopicYN="N">Travel</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Basic reproduction number</Keyword><Keyword MajorTopicYN="Y">Epidemic models</Keyword><Keyword MajorTopicYN="Y">Influenza pandemic</Keyword><Keyword MajorTopicYN="Y">SIR model</Keyword><Keyword MajorTopicYN="Y">Travel 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IdType="pubmed">19643059</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country><settlement><li>Sha Tin</li></settlement><orgName><li>Université chinoise de Hong Kong</li></orgName></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Chong, Ka Chun" sort="Chong, Ka Chun" uniqKey="Chong K" first="Ka Chun" last="Chong">Ka Chun Chong</name></noRegion><name sortKey="Wang, Maggie Haitian" sort="Wang, Maggie Haitian" uniqKey="Wang M" first="Maggie Haitian" last="Wang">Maggie Haitian Wang</name><name sortKey="Zee, Benny Chung Ying" sort="Zee, Benny Chung Ying" uniqKey="Zee B" first="Benny Chung Ying" last="Zee">Benny Chung Ying Zee</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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