Evidence map›Paper›PMID 37851661›Full record

ArticlePloS one2023

Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.

Sangeeta Bhatia, Kris V Parag, Jack Wardle, Rebecca K Nash, Natsuko Imai, Sabine L Van Elsland, Britta Lassmann, John S Brownstein, Angel Desai, Mark Herringer and 11 more

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

21 authors.

Sangeeta BhatiaMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0001-6525-101X
Kris V ParagMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Jack WardleMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-5363-1653
Rebecca K NashMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-5213-4364
Natsuko ImaiMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-4218-9716
Sabine L Van ElslandMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Britta LassmannProMED-mail, International Society for Infectious Diseases, Brookline, MA, United States of America.
John S BrownsteinBoston Children's Hospital, Computational Epidemiology Lab, Boston, MA, United States of America.
Angel DesaiProMED-mail, International Society for Infectious Diseases, Brookline, MA, United States of America.
Mark HerringerHealthsites.io, The Global Healthsites Mapping Project, London, United Kingdom.
Kara SewalkBoston Children's Hospital, Computational Epidemiology Lab, Boston, MA, United States of America.ORCID 0000-0002-2917-0869
Sarah Claire LoebProMED-mail, International Society for Infectious Diseases, Brookline, MA, United States of America.
John RamatowskiProMED-mail, International Society for Infectious Diseases, Brookline, MA, United States of America.ORCID 0000-0001-9312-1052
Gina Cuomo-DannenburgMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Elita JauneikaiteMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-7075-6896
H Juliette T UnwinMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.ORCID 0000-0002-9120-4003
Steven RileyMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Neil FergusonMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Christl A DonnellyMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Anne CoriMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.
Pierre NouvelletMRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom.

Funding

Medical Research Council MR/R015600/1Medical Research Council MR/X020258/1Wellcome Trust
6 · The paper itself

Abstract

Since 8th March 2020 up to the time of writing, we have been producing near real-time weekly estimates of SARS-CoV-2 transmissibility and forecasts of deaths due to COVID-19 for all countries with evidence of sustained transmission, shared online. We also developed a novel heuristic to combine weekly estimates of transmissibility to produce forecasts over a 4-week horizon. Here we present a retrospective evaluation of the forecasts produced between 8th March to 29th November 2020 for 81 countries. We evaluated the robustness of the forecasts produced in real-time using relative error, coverage probability, and comparisons with null models. During the 39-week period covered by this study, both the short- and medium-term forecasts captured well the epidemic trajectory across different waves of COVID-19 infections with small relative errors over the forecast horizon. The model was well calibrated with 56.3% and 45.6% of the observations lying in the 50% Credible Interval in 1-week and 4-week ahead forecasts respectively. The retrospective evaluation of our models shows that simple transmission models calibrated using routine disease surveillance data can reliably capture the epidemic trajectory in multiple countries. The medium-term forecasts can be used in conjunction with the short-term forecasts of COVID-19 mortality as a useful planning tool as countries continue to relax public health measures.

Indexed as

COVID-19EpidemicsForecastingHumansRetrospective StudiesSARS-CoV-2Time

Identifiers

PMID37851661
PMCPMC10584190

What OpenQuestion 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 OpenQuestion graph.