Evidence map›Paper›PMID 35180542›Full record

ArticleEpidemics2022

Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.

Ben Swallow, Paul Birrell, Joshua Blake, Mark Burgman, Peter Challenor, Luc E Coffeng, Philip Dawid, Daniela De Angelis, Michael Goldstein, Victoria Hemming and 9 more

Open access · goldAbstract read
In one paragraph

Article in Epidemics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
6.3field-weighted citation impact, top 2% 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

22 citing papers in PubMed, 53 citations in OpenAlex.

  1. Article
  2. Review
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  7. TheCommunications physics · 2026
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  9. Article
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  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Tracking the national and regional COVID-19 epidemic status in the UK using weighted principal component analysis.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
    Article
  18. Review
  19. Article
  20. 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

19 authors at 15 institutions in 5 countries.

Ben SwallowSchool of Mathematics and Statistics, University of Glasgow, Glasgow, UK; Scottish COVID-19 Response Consortium, UK. Electronic address: ben.swallow@glasgow.ac.uk.
Paul BirrellAnalytics & Data Science, UKHSA, UK; MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Joshua BlakeMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Mark BurgmanCentre for Environmental Policy, Imperial College London, London, UK.
Peter ChallenorThe Alan Turing Institute, London, UK; College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK.
Luc E CoffengDepartment of Public Health, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Philip DawidStatistical Laboratory, University of Cambridge, Cambridge, UK.
Daniela De AngelisMRC Biostatistics Unit, University of Cambridge, Cambridge, UK; Joint UNIversities Pandemic and Epidemiological Research, UK.
Michael GoldsteinDepartment of Mathematical Sciences, Durham University, Stockton Road, Durham, UK.
Victoria HemmingDepartment of Forest and Conservation Sciences, University of British Columbia, Vancouver, Canada.
Glenn MarionScottish COVID-19 Response Consortium, UK; Biomathematics and Statistics Scotland, Edinburgh, UK.
Trevelyan J McKinleyCollege of Medicine and Health, University of Exeter, Exeter, UK; Joint UNIversities Pandemic and Epidemiological Research, UK.
Christopher E OvertonDepartment of Mathematics, University of Manchester, Manchester, UK; Clinical Data Science Unit, Manchester University NHS Foundation Trust, Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK.
Jasmina Panovska-GriffithsThe Big Data Institute, University of Oxford, Oxford, UK; The Queen's College, University of Oxford, Oxford, UK.
Lorenzo PellisDepartment of Mathematics, University of Manchester, Manchester, UK; Joint UNIversities Pandemic and Epidemiological Research, UK; The Alan Turing Institute, London, UK.
Will ProbertThe Big Data Institute, University of Oxford, Oxford, UK.
Katriona SheaDepartment of Biology and Centre for Infectious Disease Dynamics, The Pennsylvania State University, PA 16802, USA.
Daniel VillelaProgram of Scientific Computing, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil.
Ian VernonDepartment of Mathematical Sciences, Durham University, Stockton Road, Durham, UK.
University of Cambridge · GBDurham University · GBUniversity of Exeter · GBBiomathematics and Statistics Scotland · GBCenter for Disease Dynamics, Economics & Policy · USErasmus MC · NLFundação Oswaldo Cruz · BRHealth Data Research UK · GBImperial College London · GBManchester University NHS Foundation Trust · GBOpen Data Institute · GBThe Alan Turing Institute · GBUniversity of British Columbia · CAUniversity of Glasgow · GBUniversity of Oxford · GB

Funding

Medical Research Council MC_UU_00002/11Medical Research Council MR/V038613/1Wellcome TrustWellcome Trust 202562/Z/16/Z
6 · The paper itself

Abstract

The estimation of parameters and model structure for informing infectious disease response has become a focal point of the recent pandemic. However, it has also highlighted a plethora of challenges remaining in the fast and robust extraction of information using data and models to help inform policy. In this paper, we identify and discuss four broad challenges in the estimation paradigm relating to infectious disease modelling, namely the Uncertainty Quantification framework, data challenges in estimation, model-based inference and prediction, and expert judgement. We also postulate priorities in estimation methodology to facilitate preparation for future pandemics.

Indexed as

PandemicsForecastingUncertaintyExpert elicitationPandemic modellingStatistical estimationUncertainty quantification

Identifiers

PMID35180542
PMCPMC7612598
OpenAlexW4211173190

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.