A change in vaccine efficacy and duration of protection explains recent rises in pertussis incidence in the United States.
Identifieur interne : 003025 ( PubMed/Checkpoint ); précédent : 003024; suivant : 003026A change in vaccine efficacy and duration of protection explains recent rises in pertussis incidence in the United States.
Auteurs : Manoj Gambhir [États-Unis] ; Thomas A. Clark [États-Unis] ; Simon Cauchemez [France] ; Sara Y. Tartof [États-Unis] ; David L. Swerdlow [États-Unis] ; Neil M. Ferguson [Royaume-Uni]Source :
- PLoS computational biology [ 1553-7358 ] ; 2015.
Descripteurs français
- KwdFr :
- Adolescent, Adulte, Calendrier vaccinal, Coqueluche (), Coqueluche (épidémiologie), Efficacité du vaccin, Enfant, Enfant d'âge préscolaire, Femelle, Humains, Incidence, Jeune adulte, Modèles statistiques, Mâle, Nourrisson, Nouveau-né, Répartition par âge, Résultat thérapeutique, Simulation numérique, Surveillance de la population, Vaccin diphtérie-tétanos-coqueluche (usage thérapeutique), Vaccination (utilisation), États-Unis d'Amérique (épidémiologie), Évaluation des risques ().
- MESH :
- usage thérapeutique : Vaccin diphtérie-tétanos-coqueluche.
- utilisation : Vaccination.
- épidémiologie : Coqueluche, États-Unis d'Amérique.
- Adolescent, Adulte, Calendrier vaccinal, Coqueluche, Efficacité du vaccin, Enfant, Enfant d'âge préscolaire, Femelle, Humains, Incidence, Jeune adulte, Modèles statistiques, Mâle, Nourrisson, Nouveau-né, Répartition par âge, Résultat thérapeutique, Simulation numérique, Surveillance de la population, Évaluation des risques.
- Wicri :
- geographic : États-Unis.
English descriptors
- KwdEn :
- Adolescent, Adult, Age Distribution, Child, Child, Preschool, Computer Simulation, Diphtheria-Tetanus-Pertussis Vaccine (therapeutic use), Female, Humans, Immunization Schedule, Incidence, Infant, Infant, Newborn, Male, Models, Statistical, Population Surveillance, Risk Assessment (methods), Treatment Outcome, United States (epidemiology), Vaccination (utilization), Vaccine Potency, Whooping Cough (epidemiology), Whooping Cough (prevention & control), Young Adult.
- MESH :
- chemical , therapeutic use : Diphtheria-Tetanus-Pertussis Vaccine.
- geographic , epidemiology : United States.
- epidemiology : Whooping Cough.
- methods : Risk Assessment.
- prevention & control : Whooping Cough.
- utilization : Vaccination.
- Adolescent, Adult, Age Distribution, Child, Child, Preschool, Computer Simulation, Female, Humans, Immunization Schedule, Incidence, Infant, Infant, Newborn, Male, Models, Statistical, Population Surveillance, Treatment Outcome, Vaccine Potency, Young Adult.
Abstract
Over the past ten years the incidence of pertussis in the United States (U.S.) has risen steadily, with 2012 seeing the highest case number since 1955. There has also been a shift over the same time period in the age group reporting the largest number of cases (aside from infants), from adolescents to 7-11 year olds. We use epidemiological modelling and a large case incidence dataset to explain the upsurge. We investigate several hypotheses for the upsurge in pertussis cases by fitting a suite of dynamic epidemiological models to incidence data from the National Notifiable Disease Surveillance System (NNDSS) between 1990-2009, as well as incidence data from a variety of sources from 1950-1989. We find that: the best-fitting model is one in which vaccine efficacy and duration of protection of the acellular pertussis (aP) vaccine is lower than that of the whole-cell (wP) vaccine, (efficacy of the first three doses 80% [95% CI: 78%, 82%] versus 90% [95% CI: 87%, 94%]), increasing the rate at which disease is reported to NNDSS is not sufficient to explain the upsurge and 3) 2010-2012 disease incidence is predicted well. In this study, we use all available U.S. surveillance data to: 1) fit a set of mathematical models and determine which best explains these data and 2) determine the epidemiological and vaccine-related parameter values of this model. We find evidence of a difference in efficacy and duration of protection between the two vaccine types, wP and aP (aP efficacy and duration lower than wP). Future refinement of the model presented here will allow for an exploration of alternative vaccination strategies such as different age-spacings, further booster doses, and cocooning.
DOI: 10.1371/journal.pcbi.1004138
PubMed: 25906150
Affiliations:
- France, Royaume-Uni, États-Unis
- Angleterre, Californie, Grand Londres, Géorgie (États-Unis), Île-de-France
- Londres, Paris
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There has also been a shift over the same time period in the age group reporting the largest number of cases (aside from infants), from adolescents to 7-11 year olds. We use epidemiological modelling and a large case incidence dataset to explain the upsurge. We investigate several hypotheses for the upsurge in pertussis cases by fitting a suite of dynamic epidemiological models to incidence data from the National Notifiable Disease Surveillance System (NNDSS) between 1990-2009, as well as incidence data from a variety of sources from 1950-1989. We find that: the best-fitting model is one in which vaccine efficacy and duration of protection of the acellular pertussis (aP) vaccine is lower than that of the whole-cell (wP) vaccine, (efficacy of the first three doses 80% [95% CI: 78%, 82%] versus 90% [95% CI: 87%, 94%]), increasing the rate at which disease is reported to NNDSS is not sufficient to explain the upsurge and 3) 2010-2012 disease incidence is predicted well. In this study, we use all available U.S. surveillance data to: 1) fit a set of mathematical models and determine which best explains these data and 2) determine the epidemiological and vaccine-related parameter values of this model. We find evidence of a difference in efficacy and duration of protection between the two vaccine types, wP and aP (aP efficacy and duration lower than wP). Future refinement of the model presented here will allow for an exploration of alternative vaccination strategies such as different age-spacings, further booster doses, and cocooning.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">25906150</PMID><DateCreated><Year>2015</Year><Month>04</Month><Day>24</Day></DateCreated><DateCompleted><Year>2016</Year><Month>01</Month><Day>11</Day></DateCompleted><DateRevised><Year>2016</Year><Month>10</Month><Day>19</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1553-7358</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>4</Issue><PubDate><Year>2015</Year><Month>Apr</Month></PubDate></JournalIssue><Title>PLoS computational biology</Title><ISOAbbreviation>PLoS Comput. Biol.</ISOAbbreviation></Journal><ArticleTitle>A change in vaccine efficacy and duration of protection explains recent rises in pertussis incidence in the United States.</ArticleTitle><Pagination><MedlinePgn>e1004138</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pcbi.1004138</ELocationID><Abstract><AbstractText>Over the past ten years the incidence of pertussis in the United States (U.S.) has risen steadily, with 2012 seeing the highest case number since 1955. There has also been a shift over the same time period in the age group reporting the largest number of cases (aside from infants), from adolescents to 7-11 year olds. We use epidemiological modelling and a large case incidence dataset to explain the upsurge. We investigate several hypotheses for the upsurge in pertussis cases by fitting a suite of dynamic epidemiological models to incidence data from the National Notifiable Disease Surveillance System (NNDSS) between 1990-2009, as well as incidence data from a variety of sources from 1950-1989. We find that: the best-fitting model is one in which vaccine efficacy and duration of protection of the acellular pertussis (aP) vaccine is lower than that of the whole-cell (wP) vaccine, (efficacy of the first three doses 80% [95% CI: 78%, 82%] versus 90% [95% CI: 87%, 94%]), increasing the rate at which disease is reported to NNDSS is not sufficient to explain the upsurge and 3) 2010-2012 disease incidence is predicted well. In this study, we use all available U.S. surveillance data to: 1) fit a set of mathematical models and determine which best explains these data and 2) determine the epidemiological and vaccine-related parameter values of this model. We find evidence of a difference in efficacy and duration of protection between the two vaccine types, wP and aP (aP efficacy and duration lower than wP). Future refinement of the model presented here will allow for an exploration of alternative vaccination strategies such as different age-spacings, further booster doses, and cocooning.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Gambhir</LastName><ForeName>Manoj</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia; Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America; IHRC, Inc., Atlanta, Georgia, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Clark</LastName><ForeName>Thomas A</ForeName><Initials>TA</Initials><AffiliationInfo><Affiliation>Meningitis and Vaccine Preventable Diseases Branch, Division of Bacterial Diseases, NCIRD, CDC, Atlanta, Georgia, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cauchemez</LastName><ForeName>Simon</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom; Mathematical Modelling of Infectious Diseases Unit, Institut Pasteur, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tartof</LastName><ForeName>Sara Y</ForeName><Initials>SY</Initials><AffiliationInfo><Affiliation>Kaiser Permanente Southern California, Kaiser Permanente Research, Department of Research & Evaluation, Pasadena, California, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Swerdlow</LastName><ForeName>David L</ForeName><Initials>DL</Initials><AffiliationInfo><Affiliation>Modeling Unit, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, United States of America; Office of Science and Integrative Programs, NCIRD, CDC, Atlanta, Georgia, United States of America.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Ferguson</LastName><ForeName>Neil M</ForeName><Initials>NM</Initials><AffiliationInfo><Affiliation>Medical Research Council Centre for Outbreak Analysis and Modelling, Imperial College London, London, United Kingdom.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>U01 GM110721</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>1U01GM110721-01</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>MR/K010174/1</GrantID><Agency>Medical Research Council</Agency><Country>United Kingdom</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>04</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS Comput Biol</MedlineTA><NlmUniqueID>101238922</NlmUniqueID><ISSNLinking>1553-734X</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D015721">Diphtheria-Tetanus-Pertussis Vaccine</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>MMWR Morb Mortal Wkly Rep. 1991 Dec 20;40(50):881-2</RefSource><PMID Version="1">1749373</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Pediatrics. 2003 Aug;112(2):405-6</RefSource><PMID 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MajorTopicYN="Y">utilization</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D064166" MajorTopicYN="Y">Vaccine Potency</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D014917" MajorTopicYN="N">Whooping Cough</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4408109</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2014</Year><Month>07</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>01</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>4</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>4</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>1</Month><Day>12</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">25906150</ArticleId><ArticleId IdType="doi">10.1371/journal.pcbi.1004138</ArticleId><ArticleId IdType="pii">PCOMPBIOL-D-14-01245</ArticleId><ArticleId IdType="pmc">PMC4408109</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>France</li><li>Royaume-Uni</li><li>États-Unis</li></country><region><li>Angleterre</li><li>Californie</li><li>Grand Londres</li><li>Géorgie (États-Unis)</li><li>Île-de-France</li></region><settlement><li>Londres</li><li>Paris</li></settlement></list><tree><country name="États-Unis"><region name="Géorgie (États-Unis)"><name sortKey="Gambhir, Manoj" sort="Gambhir, Manoj" uniqKey="Gambhir M" first="Manoj" last="Gambhir">Manoj Gambhir</name></region><name sortKey="Clark, Thomas A" sort="Clark, Thomas A" uniqKey="Clark T" first="Thomas A" last="Clark">Thomas A. Clark</name><name sortKey="Swerdlow, David L" sort="Swerdlow, David L" uniqKey="Swerdlow D" first="David L" last="Swerdlow">David L. Swerdlow</name><name sortKey="Tartof, Sara Y" sort="Tartof, Sara Y" uniqKey="Tartof S" first="Sara Y" last="Tartof">Sara Y. Tartof</name></country><country name="France"><region name="Île-de-France"><name sortKey="Cauchemez, Simon" sort="Cauchemez, Simon" uniqKey="Cauchemez S" first="Simon" last="Cauchemez">Simon Cauchemez</name></region></country><country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Ferguson, Neil M" sort="Ferguson, Neil M" uniqKey="Ferguson N" first="Neil M" last="Ferguson">Neil M. Ferguson</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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