Evidence map›Paper›PMID 39398325›Full record

ArticleGates open research2024

Estimating the impact of vaccination: lessons learned in the first phase of the Vaccine Impact Modelling Consortium.

Katy A M Gaythorpe, Xiang Li, Hannah Clapham, Emily Dansereau, Rich Fitzjohn, Wes Hinsley, Daniel Hogan, Mark Jit, Tewodaj Mengistu, T Alex Perkins and 5 more

Abstract read
In one paragraph

Article in Gates open research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Katy A M GaythorpeMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.ORCID https://orcid.org/0000-0003-3734-9081
Xiang LiMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.
Hannah ClaphamSaw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore.
Emily DansereauBill & Melinda Gates Foundation, Seattle, Washington, USA.
Rich FitzjohnMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.
Wes HinsleyMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.
Daniel HoganGAVI Alliance, Geneva, Geneva, Switzerland.
Mark JitLondon School of Hygiene & Tropical Health, London, UK.
Tewodaj MengistuGAVI Alliance, Geneva, Geneva, Switzerland.ORCID https://orcid.org/0000-0003-3475-3599
T Alex PerkinsDepartment of Biological Sciences, University of Notre Dame, Notre Dame, Indiana, USA.
Allison PortnoyDepartment of Global Health, University School of Public Health, Boston, Massachusetts, USA.
Emilia VynnyckyUnited Kingdom Health Security Agency, London, UK.
Kim WoodruffMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.
Neil M FergusonMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.
Caroline L TrotterMedical Research Council Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, England, UK.ORCID https://orcid.org/0000-0003-4000-2708

Funding

Medical Research Council MR/X020258/1
6 · The paper itself

Abstract

Estimates of the global health impact of immunisation are important for quantifying historical benefits as well as planning future investments and strategy. The Vaccine Impact Modelling Consortium (VIMC) was established in 2016 to provide reliable estimates of the health impact of immunisation. In this article we examine the consortium in its first five-year phase. We detail how vaccine impact was defined and the methods used to estimate it as well as the technical infrastructure required to underpin robust reproducibility of the outputs. We highlight some of the applications of estimates to date, how these were communicated and what their effect were. Finally, we explore some of the lessons learnt and remaining challenges for estimating the impact of vaccines and forming effective modelling consortia then discuss how this may be addressed in the second phase of VIMC. Modelled estimates are not a replacement for surveillance; however, they can examine theoretical counterfactuals and highlight data gaps to complement other activities. VIMC has implemented strategies to produce robust, standardised estimates of immunisation impact. But through the first phase of the consortium, critical lessons have been learnt both on the technical infrastructure and the effective engagement with modellers and stakeholders. To be successful, a productive dialogue with estimate consumers, producers and stakeholders needs to be underpinned by a rigorous and transparent analytical framework as well as an approach for building expertise in the short and long term.

Indexed as

VaccinationGlobal HealthHumansImmunization ProgramsModels, TheoreticalReproducibility of ResultsVaccinesVaccinesimpactmathematical modellingVaccine

Identifiers

PMID39398325
PMCPMC11467163

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.