Evidence map›Paper›PMID 29253379›Full record

SynthesisThe Lancet. Public health2016

Population-level impact, herd immunity, and elimination after human papillomavirus vaccination: a systematic review and meta-analysis of predictions from transmission-dynamic models.

Marc Brisson, Élodie Bénard, Mélanie Drolet, Johannes A Bogaards, Iacopo Baussano, Simopekka Vänskä, Mark Jit, Marie-Claude Boily, Megan A Smith, Johannes Berkhof and 21 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in The Lancet. Public health, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
150citing papers in PubMed, 4 pooled it
23.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

150 citing papers in PubMed, 4 syntheses or guidelines pooled it, 306 citations in OpenAlex.

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90 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

31 authors at 20 institutions in 12 countries.

Marc BrissonCentre de recherche du CHU de Québec-Université Laval, Quebec City, QC, Canada; Département de médecine sociale et préventive, Université Laval, Quebec City, QC, Canada; Department of Infectious Disease Epidemiology, Imperial College, London, UK. Electronic address: marc.brisson@crchudequebec.ulaval.ca.
Élodie BénardCentre de recherche du CHU de Québec-Université Laval, Quebec City, QC, Canada; Département de médecine sociale et préventive, Université Laval, Quebec City, QC, Canada.
Mélanie DroletCentre de recherche du CHU de Québec-Université Laval, Quebec City, QC, Canada.
Johannes A BogaardsCentre for Infectious Disease Control, National Institute of Public Health and the Environment, Bilthoven, Netherlands.
Iacopo BaussanoInfection and Cancer Epidemiology Group, International Agency for Research on Cancer, Lyon, France.
Simopekka VänskäVaccination Programme Unit, National Institute for Health and Welfare, Helsinki, Finland.
Mark JitModelling and Economics Unit, Public Health England, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.
Marie-Claude BoilyDépartement de médecine sociale et préventive, Université Laval, Quebec City, QC, Canada; Department of Infectious Disease Epidemiology, Imperial College, London, UK.
Megan A SmithCancer Research Division, Cancer Council NSW, Sydney, NSW, Australia.
Johannes BerkhofDepartment of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands.
Karen CanfellCancer Research Division, Cancer Council NSW, Sydney, NSW, Australia; Lowy Cancer Research Centre, Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia.
Harrell W ChessonDivision of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Emily A BurgerCenter for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Health Management and Health Economics, University of Oslo, Oslo, Norway.
Yoon H ChoiNational Infection Service, Public Health England, London, UK.
Birgitte Freiesleben De BlasioOslo Centre for Biostatistics and Epidemiology, Division of Infectious Disease Control, Norwegian Institute of Public Health and Oslo Centre for Statistics and Epidemiology, Oslo, Norway; Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway.
Sake J De VlasDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.
Giorgio GuzzettaFondazione Bruno Kessler, Trento, Italy.
Jan A C HontelezDepartment of Global Health and Population, Harvard T H Chan School of Public Health, Boston, MA, USA; Department of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.
Johannes HornEpidemiological and Statistical Methods Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany.
Martin R JepsenSection for Geography, Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
Jane J KimCenter for Health Decision Science, Harvard T H Chan School of Public Health, Boston, MA, USA.
Fulvio LazzaratoInfection and Cancer Epidemiology Group, International Agency for Research on Cancer, Lyon, France; Unit of Cancer Epidemiology, Department of Medical Sciences, University of Turin, Turin, Italy.
Suzette M MatthijsseDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands.
Rafael MikolajczykEpidemiological and Statistical Methods Research Group, Helmholtz Centre for Infection Research, Braunschweig, Germany.
Andrew PavelyevMerck Research Laboratories, Rahway, NJ, USA.
Matthew PillsburyMerck Research Laboratories, Rahway, NJ, USA.
Leigh Anne ShaferDepartment of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada.
Stephen P TullyInfection and Cancer Epidemiology Group, International Agency for Research on Cancer, Lyon, France.
Hugo C TurnerDepartment of Infectious Disease Epidemiology, Imperial College, London, UK.
Cara UsherNational Centre for Pharmacoeconomics (NCPE Ireland), Dublin, Ireland.
Cathal WalshDepartment of Mathematics and Statistics, University of Limerick, Limerick, Ireland.
Université Laval · CACentre International de Recherche sur le Cancer · FRCancer Council NSW · AUErasmus MC · NLHelmholtz Centre for Infection Research · DEMerck & Co., Inc., Rahway, NJ, USA (United States) · USAmsterdam UMC Location VUmc · NLCenters for Disease Control and Prevention · USFinnish Institute for Health and Welfare · FIFondazione Bruno Kessler · ITGeocenter Denmark · DKHarvard Global Health Institute · USImperial College London · GBLondon School of Hygiene & Tropical Medicine · GBNational Centre for Pharmacoeconomics · IENational Institute for Public Health and the Environment · NLNorwegian Institute of Public Health · NOPublic Health England · GBUniversity of Limerick · IEUniversity of Manitoba · CA

Funding

Comparative and Cost-Effectiveness of Preventing HPV-Related DiseasesR01CA160744 · NCI · HARVARD SCHOOL OF PUBLIC HEALTH · PI KIM, JANE JOOYUN · 2012 to 2015
$1.2M
Intramural CDC HHS CC999999NCI NIH HHS R01 CA160744World Health Organization 001
6 · The paper itself

Abstract

backgroundModelling studies have been widely used to inform human papillomavirus (HPV) vaccination policy decisions; however, many models exist and it is not known whether they produce consistent predictions of population-level effectiveness and herd effects. We did a systematic review and meta-analysis of model predictions of the long-term population-level effectiveness of vaccination against HPV 16, 18, 6, and 11 infection in women and men, to examine the variability in predicted herd effects, incremental benefit of vaccinating boys, and potential for HPV-vaccine-type elimination.

methodsWe searched MEDLINE and Embase for transmission-dynamic modelling studies published between Jan 1, 2009, and April 28, 2015, that predicted the population-level impact of vaccination on HPV 6, 11, 16, and 18 infections in high-income countries. We contacted authors to determine whether they were willing to produce new predictions for standardised scenarios. Strategies investigated were girls-only vaccination and girls and boys vaccination at age 12 years. Base-case vaccine characteristics were 100% efficacy and lifetime protection. We did sensitivity analyses by varying vaccination coverage, vaccine efficacy, and duration of protection. For all scenarios we pooled model predictions of relative reductions in HPV prevalence (RR

findings16 of 19 eligible models from ten high-income countries provided predictions. Under base-case assumptions, 40% vaccination coverage and girls-only vaccination, the RR

interpretationAlthough HPV models differ in structure, data used for calibration, and settings, our population-level predictions were generally concordant and suggest that strong herd effects are expected from vaccinating girls only, even with coverage as low as 20%. Elimination of HPV 16, 18, 6, and 11 is possible if 80% coverage in girls and boys is reached and if high vaccine efficacy is maintained over time.

fundingCanadian Institutes of Health Research.

Indexed as

Disease EradicationFemaleHumansImmunity, HerdMaleModels, StatisticalPapillomavirus InfectionsPapillomavirus VaccinesPapillomavirus Vaccines

Identifiers

PMID29253379
PMCPMC6727207
OpenAlexW2528304237

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.