Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.
Identifieur interne : 000061 ( Main/Exploration ); précédent : 000060; suivant : 000062Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.
Auteurs : Felix Weidemann [Allemagne] ; Cornelius Remschmidt [Allemagne] ; Silke Buda [Allemagne] ; Udo Buchholz [Allemagne] ; Bernhard Ultsch [Allemagne] ; Ole Wichmann [Allemagne]Source :
- BMC infectious diseases [ 1471-2334 ] ; 2017.
Descripteurs français
- KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Allemagne (épidémiologie), Enfant (MeSH), Enfant d'âge préscolaire (MeSH), Femelle (MeSH), Grippe humaine (prévention et contrôle), Grippe humaine (transmission), Grippe humaine (épidémiologie), Humains (MeSH), Incidence (MeSH), Maladie aigüe (MeSH), Modèles biologiques (MeSH), Mâle (MeSH), Nourrisson (MeSH), Saisons (MeSH), Théorème de Bayes (MeSH), Vaccins antigrippaux (immunologie), Évaluation des impacts sur la santé (MeSH).
- MESH :
- immunologie : Vaccins antigrippaux.
- prévention et contrôle : Grippe humaine.
- épidémiologie : Allemagne, Grippe humaine.
- Adulte, Adulte d'âge moyen, Enfant, Enfant d'âge préscolaire, Femelle, Humains, Incidence, Maladie aigüe, Modèles biologiques, Mâle, Nourrisson, Saisons, Théorème de Bayes, Évaluation des impacts sur la santé.
English descriptors
- KwdEn :
- Acute Disease (MeSH), Adult (MeSH), Bayes Theorem (MeSH), Child (MeSH), Child, Preschool (MeSH), Female (MeSH), Germany (epidemiology), Health Impact Assessment (MeSH), Humans (MeSH), Incidence (MeSH), Infant (MeSH), Influenza Vaccines (immunology), Influenza, Human (epidemiology), Influenza, Human (prevention & control), Influenza, Human (transmission), Male (MeSH), Middle Aged (MeSH), Models, Biological (MeSH), Seasons (MeSH).
- MESH :
- chemical , immunology : Influenza Vaccines.
- epidemiology : Germany, Influenza, Human.
- prevention & control : Influenza, Human.
- transmission : Influenza, Human.
- Acute Disease, Adult, Bayes Theorem, Child, Child, Preschool, Female, Health Impact Assessment, Humans, Incidence, Infant, Male, Middle Aged, Models, Biological, Seasons.
Abstract
BACKGROUND
To reduce the burden of severe influenza, most industrialized countries target specific risk-groups with influenza vaccines, e.g. the elderly or individuals with comorbidities. Since children are the main spreaders, some countries have recently implemented childhood vaccination programs to reduce overall virus transmission and thereby influenza disease in the whole population. The introduction of childhood vaccination programs was often supported by modelling studies that predicted substantial incidence reductions. We developed a mathematical transmission model to examine the potential impact of childhood influenza vaccination in Germany, while also challenging established modelling assumptions.
METHODS
We developed an age-stratified SEIR-type transmission model to reproduce the epidemic influenza seasons between 2003/04 and 2013/14. The model was built upon German population counts, contact patterns, and vaccination history and was fitted to seasonal data on influenza-attributable medically attended acute respiratory infections (I-MAARI) and strain distribution using Bayesian methods. As novelties we (i) implemented a stratified model structure enabling seasonal variability and (ii) deviated from the commonly assumed mass-action-principle by employing a phenomenological transmission rate.
RESULTS
According to the model, by vaccinating primarily the elderly over ten seasons 4 million (95% prediction interval: 3.84 - 4.19) I-MAARI were prevented which corresponds to an 8.6% (8.3% - 8.9%) reduction compared to a no-vaccination scenario and a number-needed-to-vaccinate (NNV) to prevent one I-MAARI of 37.1 (35.5 - 38.7). Additional vaccination of 2-10 year-old children at 40% coverage would have led to an overall I-MAARI reduction of 17.8% (17.1 - 18.7%) mostly due to indirect effects with a NNV of 20.7 (19.6 - 21.6). When employing the traditional mass-action-principle, the model predicted a more than 3-fold higher I-MAARI reduction (55.6%) due to childhood vaccination.
CONCLUSION
In Germany, the introduction of routine childhood influenza vaccination could considerably reduce I-MAARI among all age-groups and improve the NNV. However, the predicted impact is much lower compared to previous studies, which is primarily caused by our phenomenological approach to modelling influenza virus transmission.
DOI: 10.1186/s12879-017-2344-6
PubMed: 28399801
PubMed Central: PMC5387286
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.</title><author><name sortKey="Weidemann, Felix" sort="Weidemann, Felix" uniqKey="Weidemann F" first="Felix" last="Weidemann">Felix Weidemann</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Remschmidt, Cornelius" sort="Remschmidt, Cornelius" uniqKey="Remschmidt C" first="Cornelius" last="Remschmidt">Cornelius Remschmidt</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Buda, Silke" sort="Buda, Silke" uniqKey="Buda S" first="Silke" last="Buda">Silke Buda</name><affiliation wicri:level="3"><nlm:affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Buchholz, Udo" sort="Buchholz, Udo" uniqKey="Buchholz U" first="Udo" last="Buchholz">Udo Buchholz</name><affiliation wicri:level="3"><nlm:affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Ultsch, Bernhard" sort="Ultsch, Bernhard" uniqKey="Ultsch B" first="Bernhard" last="Ultsch">Bernhard Ultsch</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Wichmann, Ole" sort="Wichmann, Ole" uniqKey="Wichmann O" first="Ole" last="Wichmann">Ole Wichmann</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany. wichmanno@rki.de.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2017">2017</date><idno type="RBID">pubmed:28399801</idno><idno type="pmid">28399801</idno><idno type="doi">10.1186/s12879-017-2344-6</idno><idno type="pmc">PMC5387286</idno><idno type="wicri:Area/Main/Corpus">000057</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000057</idno><idno type="wicri:Area/Main/Curation">000057</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000057</idno><idno type="wicri:Area/Main/Exploration">000057</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.</title><author><name sortKey="Weidemann, Felix" sort="Weidemann, Felix" uniqKey="Weidemann F" first="Felix" last="Weidemann">Felix Weidemann</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Remschmidt, Cornelius" sort="Remschmidt, Cornelius" uniqKey="Remschmidt C" first="Cornelius" last="Remschmidt">Cornelius Remschmidt</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Buda, Silke" sort="Buda, Silke" uniqKey="Buda S" first="Silke" last="Buda">Silke Buda</name><affiliation wicri:level="3"><nlm:affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Buchholz, Udo" sort="Buchholz, Udo" uniqKey="Buchholz U" first="Udo" last="Buchholz">Udo Buchholz</name><affiliation wicri:level="3"><nlm:affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Ultsch, Bernhard" sort="Ultsch, Bernhard" uniqKey="Ultsch B" first="Bernhard" last="Ultsch">Bernhard Ultsch</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author><author><name sortKey="Wichmann, Ole" sort="Wichmann, Ole" uniqKey="Wichmann O" first="Ole" last="Wichmann">Ole Wichmann</name><affiliation wicri:level="3"><nlm:affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany. wichmanno@rki.de.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin</wicri:regionArea><placeName><region type="land" nuts="3">Berlin</region><settlement type="city">Berlin</settlement></placeName></affiliation></author></analytic><series><title level="j">BMC infectious diseases</title><idno type="eISSN">1471-2334</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Acute Disease (MeSH)</term><term>Adult (MeSH)</term><term>Bayes Theorem (MeSH)</term><term>Child (MeSH)</term><term>Child, Preschool (MeSH)</term><term>Female (MeSH)</term><term>Germany (epidemiology)</term><term>Health Impact Assessment (MeSH)</term><term>Humans (MeSH)</term><term>Incidence (MeSH)</term><term>Infant (MeSH)</term><term>Influenza Vaccines (immunology)</term><term>Influenza, Human (epidemiology)</term><term>Influenza, Human (prevention & control)</term><term>Influenza, Human (transmission)</term><term>Male (MeSH)</term><term>Middle Aged (MeSH)</term><term>Models, Biological (MeSH)</term><term>Seasons (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term><term>Adulte d'âge moyen (MeSH)</term><term>Allemagne (épidémiologie)</term><term>Enfant (MeSH)</term><term>Enfant d'âge préscolaire (MeSH)</term><term>Femelle (MeSH)</term><term>Grippe humaine (prévention et contrôle)</term><term>Grippe humaine (transmission)</term><term>Grippe humaine (épidémiologie)</term><term>Humains (MeSH)</term><term>Incidence (MeSH)</term><term>Maladie aigüe (MeSH)</term><term>Modèles biologiques (MeSH)</term><term>Mâle (MeSH)</term><term>Nourrisson (MeSH)</term><term>Saisons (MeSH)</term><term>Théorème de Bayes (MeSH)</term><term>Vaccins antigrippaux (immunologie)</term><term>Évaluation des impacts sur la santé (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="immunology" xml:lang="en"><term>Influenza Vaccines</term></keywords><keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>Germany</term><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="immunologie" xml:lang="fr"><term>Vaccins antigrippaux</term></keywords><keywords scheme="MESH" qualifier="prevention & control" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="prévention et contrôle" xml:lang="fr"><term>Grippe humaine</term></keywords><keywords scheme="MESH" qualifier="transmission" xml:lang="en"><term>Influenza, Human</term></keywords><keywords scheme="MESH" qualifier="épidémiologie" xml:lang="fr"><term>Allemagne</term><term>Grippe humaine</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Acute Disease</term><term>Adult</term><term>Bayes Theorem</term><term>Child</term><term>Child, Preschool</term><term>Female</term><term>Health Impact Assessment</term><term>Humans</term><term>Incidence</term><term>Infant</term><term>Male</term><term>Middle Aged</term><term>Models, Biological</term><term>Seasons</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Adulte</term><term>Adulte d'âge moyen</term><term>Enfant</term><term>Enfant d'âge préscolaire</term><term>Femelle</term><term>Humains</term><term>Incidence</term><term>Maladie aigüe</term><term>Modèles biologiques</term><term>Mâle</term><term>Nourrisson</term><term>Saisons</term><term>Théorème de Bayes</term><term>Évaluation des impacts sur la santé</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b></p><p>To reduce the burden of severe influenza, most industrialized countries target specific risk-groups with influenza vaccines, e.g. the elderly or individuals with comorbidities. Since children are the main spreaders, some countries have recently implemented childhood vaccination programs to reduce overall virus transmission and thereby influenza disease in the whole population. The introduction of childhood vaccination programs was often supported by modelling studies that predicted substantial incidence reductions. We developed a mathematical transmission model to examine the potential impact of childhood influenza vaccination in Germany, while also challenging established modelling assumptions.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>We developed an age-stratified SEIR-type transmission model to reproduce the epidemic influenza seasons between 2003/04 and 2013/14. The model was built upon German population counts, contact patterns, and vaccination history and was fitted to seasonal data on influenza-attributable medically attended acute respiratory infections (I-MAARI) and strain distribution using Bayesian methods. As novelties we (i) implemented a stratified model structure enabling seasonal variability and (ii) deviated from the commonly assumed mass-action-principle by employing a phenomenological transmission rate.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>According to the model, by vaccinating primarily the elderly over ten seasons 4 million (95% prediction interval: 3.84 - 4.19) I-MAARI were prevented which corresponds to an 8.6% (8.3% - 8.9%) reduction compared to a no-vaccination scenario and a number-needed-to-vaccinate (NNV) to prevent one I-MAARI of 37.1 (35.5 - 38.7). Additional vaccination of 2-10 year-old children at 40% coverage would have led to an overall I-MAARI reduction of 17.8% (17.1 - 18.7%) mostly due to indirect effects with a NNV of 20.7 (19.6 - 21.6). When employing the traditional mass-action-principle, the model predicted a more than 3-fold higher I-MAARI reduction (55.6%) due to childhood vaccination.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSION</b></p><p>In Germany, the introduction of routine childhood influenza vaccination could considerably reduce I-MAARI among all age-groups and improve the NNV. However, the predicted impact is much lower compared to previous studies, which is primarily caused by our phenomenological approach to modelling influenza virus transmission.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">28399801</PMID><DateCompleted><Year>2017</Year><Month>06</Month><Day>28</Day></DateCompleted><DateRevised><Year>2018</Year><Month>12</Month><Day>02</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1471-2334</ISSN><JournalIssue CitedMedium="Internet"><Volume>17</Volume><Issue>1</Issue><PubDate><Year>2017</Year><Month>04</Month><Day>11</Day></PubDate></JournalIssue><Title>BMC infectious diseases</Title><ISOAbbreviation>BMC Infect. Dis.</ISOAbbreviation></Journal><ArticleTitle>Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.</ArticleTitle><Pagination><MedlinePgn>258</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s12879-017-2344-6</ELocationID><Abstract><AbstractText Label="BACKGROUND">To reduce the burden of severe influenza, most industrialized countries target specific risk-groups with influenza vaccines, e.g. the elderly or individuals with comorbidities. Since children are the main spreaders, some countries have recently implemented childhood vaccination programs to reduce overall virus transmission and thereby influenza disease in the whole population. The introduction of childhood vaccination programs was often supported by modelling studies that predicted substantial incidence reductions. We developed a mathematical transmission model to examine the potential impact of childhood influenza vaccination in Germany, while also challenging established modelling assumptions.</AbstractText><AbstractText Label="METHODS">We developed an age-stratified SEIR-type transmission model to reproduce the epidemic influenza seasons between 2003/04 and 2013/14. The model was built upon German population counts, contact patterns, and vaccination history and was fitted to seasonal data on influenza-attributable medically attended acute respiratory infections (I-MAARI) and strain distribution using Bayesian methods. As novelties we (i) implemented a stratified model structure enabling seasonal variability and (ii) deviated from the commonly assumed mass-action-principle by employing a phenomenological transmission rate.</AbstractText><AbstractText Label="RESULTS">According to the model, by vaccinating primarily the elderly over ten seasons 4 million (95% prediction interval: 3.84 - 4.19) I-MAARI were prevented which corresponds to an 8.6% (8.3% - 8.9%) reduction compared to a no-vaccination scenario and a number-needed-to-vaccinate (NNV) to prevent one I-MAARI of 37.1 (35.5 - 38.7). Additional vaccination of 2-10 year-old children at 40% coverage would have led to an overall I-MAARI reduction of 17.8% (17.1 - 18.7%) mostly due to indirect effects with a NNV of 20.7 (19.6 - 21.6). When employing the traditional mass-action-principle, the model predicted a more than 3-fold higher I-MAARI reduction (55.6%) due to childhood vaccination.</AbstractText><AbstractText Label="CONCLUSION">In Germany, the introduction of routine childhood influenza vaccination could considerably reduce I-MAARI among all age-groups and improve the NNV. However, the predicted impact is much lower compared to previous studies, which is primarily caused by our phenomenological approach to modelling influenza virus transmission.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Weidemann</LastName><ForeName>Felix</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Remschmidt</LastName><ForeName>Cornelius</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Buda</LastName><ForeName>Silke</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Buchholz</LastName><ForeName>Udo</ForeName><Initials>U</Initials><AffiliationInfo><Affiliation>Respiratory Disease Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ultsch</LastName><ForeName>Bernhard</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wichmann</LastName><ForeName>Ole</ForeName><Initials>O</Initials><AffiliationInfo><Affiliation>Immunization Unit, Robert Koch-Institute, Seestr. 10, 13359, Berlin, Germany. wichmanno@rki.de.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>04</Month><Day>11</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>BMC Infect Dis</MedlineTA><NlmUniqueID>100968551</NlmUniqueID><ISSNLinking>1471-2334</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D007252">Influenza Vaccines</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000208" MajorTopicYN="N">Acute Disease</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001499" MajorTopicYN="N">Bayes Theorem</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005858" MajorTopicYN="N">Germany</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D062489" MajorTopicYN="N">Health Impact Assessment</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015994" MajorTopicYN="N">Incidence</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007223" MajorTopicYN="N">Infant</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D007252" MajorTopicYN="N">Influenza Vaccines</DescriptorName><QualifierName UI="Q000276" MajorTopicYN="Y">immunology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D007251" MajorTopicYN="N">Influenza, Human</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName><QualifierName UI="Q000635" MajorTopicYN="N">transmission</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008954" MajorTopicYN="N">Models, Biological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D012621" MajorTopicYN="N">Seasons</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Bayesian inference</Keyword><Keyword MajorTopicYN="Y">Influenza</Keyword><Keyword MajorTopicYN="Y">NNV</Keyword><Keyword MajorTopicYN="Y">childhood vaccination</Keyword><Keyword MajorTopicYN="Y">transmission model</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>10</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>03</Month><Day>25</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2017</Year><Month>4</Month><Day>13</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2017</Year><Month>4</Month><Day>13</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2017</Year><Month>6</Month><Day>29</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">28399801</ArticleId><ArticleId IdType="doi">10.1186/s12879-017-2344-6</ArticleId><ArticleId IdType="pii">10.1186/s12879-017-2344-6</ArticleId><ArticleId IdType="pmc">PMC5387286</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Am J Epidemiol. 2013 Dec 1;178(11):1655-62</Citation><ArticleIdList><ArticleId IdType="pubmed">24100954</ArticleId></ArticleIdList></Reference><Reference><Citation>MMWR Morb Mortal Wkly Rep. 2015 Aug 7;64(30):818-25</Citation><ArticleIdList><ArticleId IdType="pubmed">26247435</ArticleId></ArticleIdList></Reference><Reference><Citation>N Engl J Med. 2001 Mar 22;344(12):889-96</Citation><ArticleIdList><ArticleId IdType="pubmed">11259722</ArticleId></ArticleIdList></Reference><Reference><Citation>BMC Infect Dis. 2014 Jul 03;14:365</Citation><ArticleIdList><ArticleId IdType="pubmed">24993051</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS One. 2013 Jul 16;8(7):e64593</Citation><ArticleIdList><ArticleId IdType="pubmed">23874380</ArticleId></ArticleIdList></Reference><Reference><Citation>Am J Epidemiol. 2009 Sep 15;170(6):679-86</Citation><ArticleIdList><ArticleId IdType="pubmed">19679750</ArticleId></ArticleIdList></Reference><Reference><Citation>Trends Ecol Evol. 2001 Jun 1;16(6):295-300</Citation><ArticleIdList><ArticleId IdType="pubmed">11369107</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS Med. 2015 May 26;12(5):e1001829; discussion e1001829</Citation><ArticleIdList><ArticleId IdType="pubmed">26011712</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS One. 2011;6(11):e27622</Citation><ArticleIdList><ArticleId IdType="pubmed">22110695</ArticleId></ArticleIdList></Reference><Reference><Citation>Euro Surveill. 2015;20(39):null</Citation><ArticleIdList><ArticleId IdType="pubmed">26537222</ArticleId></ArticleIdList></Reference><Reference><Citation>BMC Med. 2013 Jun 25;11:153</Citation><ArticleIdList><ArticleId IdType="pubmed">23800265</ArticleId></ArticleIdList></Reference><Reference><Citation>Wkly Epidemiol Rec. 2005 Aug 19;80(33):279-87</Citation><ArticleIdList><ArticleId IdType="pubmed">16171031</ArticleId></ArticleIdList></Reference><Reference><Citation>Arch Pediatr Adolesc Med. 2002 Oct;156(10):986-91</Citation><ArticleIdList><ArticleId IdType="pubmed">12361443</ArticleId></ArticleIdList></Reference><Reference><Citation>Euro Surveill. 2009 Nov 05;14(44):null</Citation><ArticleIdList><ArticleId IdType="pubmed">19941774</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2012 Feb 1;30(6):1208-24</Citation><ArticleIdList><ArticleId IdType="pubmed">22178725</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2015 Jun 4;33(24):2813-22</Citation><ArticleIdList><ArticleId IdType="pubmed">25936723</ArticleId></ArticleIdList></Reference><Reference><Citation>Hum Vaccin Immunother. 2014;10(2):476-84</Citation><ArticleIdList><ArticleId IdType="pubmed">24192604</ArticleId></ArticleIdList></Reference><Reference><Citation>BMC Infect Dis. 2014 Jan 22;14:40</Citation><ArticleIdList><ArticleId IdType="pubmed">24450996</ArticleId></ArticleIdList></Reference><Reference><Citation>Int J Environ Res Public Health. 2016 Feb 24;13(3):null</Citation><ArticleIdList><ArticleId IdType="pubmed">26927140</ArticleId></ArticleIdList></Reference><Reference><Citation>Am J Epidemiol. 2008 Apr 1;167(7):775-85</Citation><ArticleIdList><ArticleId IdType="pubmed">18230677</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS Med. 2011 Jan;8(1):e1000388</Citation><ArticleIdList><ArticleId IdType="pubmed">21379316</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2008 Sep 26;26(41):5321-30</Citation><ArticleIdList><ArticleId IdType="pubmed">18647634</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2009 Feb 11;27(7):1101-10</Citation><ArticleIdList><ArticleId IdType="pubmed">19095024</ArticleId></ArticleIdList></Reference><Reference><Citation>J Infect Dis. 2013 Aug 15;208(4):544-53</Citation><ArticleIdList><ArticleId IdType="pubmed">23847058</ArticleId></ArticleIdList></Reference><Reference><Citation>JAMA. 2010 Mar 10;303(10):943-50</Citation><ArticleIdList><ArticleId IdType="pubmed">20215608</ArticleId></ArticleIdList></Reference><Reference><Citation>Euro Surveill. 2014 Jan 30;19(4):null</Citation><ArticleIdList><ArticleId IdType="pubmed">24507468</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS Med. 2008 Mar 25;5(3):e74</Citation><ArticleIdList><ArticleId IdType="pubmed">18366252</ArticleId></ArticleIdList></Reference><Reference><Citation>Influenza Other Respir Viruses. 2011 Nov;5(6):e499-503</Citation><ArticleIdList><ArticleId IdType="pubmed">21668675</ArticleId></ArticleIdList></Reference><Reference><Citation>Health Technol Assess. 2010 Dec;14 (55):115-92</Citation><ArticleIdList><ArticleId IdType="pubmed">21208549</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2014 Sep 8;32(40):5250-7</Citation><ArticleIdList><ArticleId IdType="pubmed">25045820</ArticleId></ArticleIdList></Reference><Reference><Citation>Cochrane Database Syst Rev. 2010 Jul 07;(7):CD001269</Citation><ArticleIdList><ArticleId IdType="pubmed">20614424</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2011 Nov 15;29(49):9159-70</Citation><ArticleIdList><ArticleId IdType="pubmed">21840359</ArticleId></ArticleIdList></Reference><Reference><Citation>Cochrane Database Syst Rev. 2008 Apr 16;(2):CD004879</Citation><ArticleIdList><ArticleId IdType="pubmed">18425905</ArticleId></ArticleIdList></Reference><Reference><Citation>Pharmacoeconomics. 2016 Mar;34(3):227-44</Citation><ArticleIdList><ArticleId IdType="pubmed">26477039</ArticleId></ArticleIdList></Reference><Reference><Citation>Epidemiol Infect. 1993 Feb;110(1):145-60</Citation><ArticleIdList><ArticleId IdType="pubmed">8432318</ArticleId></ArticleIdList></Reference><Reference><Citation>Euro Surveill. 2014 Feb 13;19(6):null</Citation><ArticleIdList><ArticleId IdType="pubmed">24556348</ArticleId></ArticleIdList></Reference><Reference><Citation>Health Technol Assess. 2010 Jul;14(34):267-312</Citation><ArticleIdList><ArticleId IdType="pubmed">20630125</ArticleId></ArticleIdList></Reference><Reference><Citation>Epidemics. 2015 Dec;13:1-9</Citation><ArticleIdList><ArticleId IdType="pubmed">26616037</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS Med. 2013 Oct;10(10):e1001527</Citation><ArticleIdList><ArticleId IdType="pubmed">24115913</ArticleId></ArticleIdList></Reference><Reference><Citation>Euro Surveill. 2013 Jan 31;18(5):null</Citation><ArticleIdList><ArticleId IdType="pubmed">23399425</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS One. 2011;6(6):e21340</Citation><ArticleIdList><ArticleId IdType="pubmed">21701598</ArticleId></ArticleIdList></Reference><Reference><Citation>J R Soc Interface. 2016 Oct;13(123):</Citation><ArticleIdList><ArticleId IdType="pubmed">27707909</ArticleId></ArticleIdList></Reference><Reference><Citation>Vaccine. 2009 Mar 18;27(13):1923-7</Citation><ArticleIdList><ArticleId IdType="pubmed">19368772</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Allemagne</li></country><region><li>Berlin</li></region><settlement><li>Berlin</li></settlement></list><tree><country name="Allemagne"><region name="Berlin"><name sortKey="Weidemann, Felix" sort="Weidemann, Felix" uniqKey="Weidemann F" first="Felix" last="Weidemann">Felix Weidemann</name></region><name sortKey="Buchholz, Udo" sort="Buchholz, Udo" uniqKey="Buchholz U" first="Udo" last="Buchholz">Udo Buchholz</name><name sortKey="Buda, Silke" sort="Buda, Silke" uniqKey="Buda S" first="Silke" last="Buda">Silke Buda</name><name sortKey="Remschmidt, Cornelius" sort="Remschmidt, Cornelius" uniqKey="Remschmidt C" first="Cornelius" last="Remschmidt">Cornelius Remschmidt</name><name sortKey="Ultsch, Bernhard" sort="Ultsch, Bernhard" uniqKey="Ultsch B" first="Bernhard" last="Ultsch">Bernhard Ultsch</name><name sortKey="Wichmann, Ole" sort="Wichmann, Ole" uniqKey="Wichmann O" first="Ole" last="Wichmann">Ole Wichmann</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/GrippeAllemagneV4/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000061 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000061 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= GrippeAllemagneV4
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:28399801
|texte= Is the impact of childhood influenza vaccination less than expected: a transmission modelling study.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:28399801" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a GrippeAllemagneV4
| This area was generated with Dilib version V0.6.35. |  |