Evidence map›Paper›PMID 35664221›Full record

ArticleStatistical science : a review journal of the Institute of Mathematical Statistics2022

Interoperability of statistical models in pandemic preparedness: principles and reality.

George Nicholson, Marta Blangiardo, Mark Briers, Peter J Diggle, Tor Erlend Fjelde, Hong Ge, Robert J B Goudie, Radka Jersakova, Ruairidh E King, Brieuc C L Lehmann and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Statistical science : a review journal of the Institute of Mathematical Statistics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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.

George NicholsonUniversity of Oxford, UK.
Marta BlangiardoMRC Centre for Environment and Health, Dept of Epidemiology and Biostatistics, Imperial College London.
Mark BriersUniversity of Oxford, UK.
Peter J DiggleCHICAS, Lancaster Medical School, Lancaster University, UK.
Tor Erlend FjeldeDepartment of Engineering, University of Cambridge, UK.
Hong GeDepartment of Engineering, University of Cambridge, UK.
Robert J B GoudieMRC Biostatistics Unit, University of Cambridge, UK.
Radka JersakovaThe Alan Turing Institute, London, UK.
Ruairidh E KingMRC Harwell Institute, Harwell, UK.
Brieuc C L LehmannUniversity of Oxford, UK.
Ann-Marie MallonMRC Harwell Institute, Harwell, UK.
Tullia PadelliniMRC Centre for Environment and Health, Dept of Epidemiology and Biostatistics, Imperial College London.
Yee Whye TehUniversity of Oxford, UK.
Chris Holmes *University of Oxford, UK.
Sylvia Richardson *The Alan Turing Institute, London, UK.

Funding

Medical Research Council MC_UU_00002/10Medical Research Council MC_UU_00002/2Medical Research Council MR/S019669/1
6 · The paper itself

Abstract

We present

Indexed as

Bayesian graphical modelsCOVID-19Evidence synthesisInteroperabilityModularizationMulti-source inference

Identifiers

PMID35664221
PMCPMC7612804

What OpenQuestion holds

Textmetadata
LicenceTDM
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.