Evidence map›Paper›PMID 33234065›Full record

ArticleJournal of the Royal Society, Interface2020

Inference of COVID-19 epidemiological distributions from Brazilian hospital data.

Iwona Hawryluk, Thomas A Mellan, Henrique Hoeltgebaum, Swapnil Mishra, Ricardo P Schnekenberg, Charles Whittaker, Harrison Zhu, Axel Gandy, Christl A Donnelly, Seth Flaxman and 1 more

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
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  7. Resolving the enigma of Iquitos and Manaus: A modeling analysis of multiple COVID-19 epidemic waves in two Amazonian cities.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data.International journal of environmental research and public health · 2022
    Article
  13. Fitting the reproduction number from UK coronavirus case data and why it is close to 1.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2022
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Genomics and epidemiology of a novel SARS-CoV-2 lineage in Manaus, Brazil.medRxiv : the preprint server for health sciences · 2021
    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

11 authors.

Iwona HawrylukMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Thomas A MellanMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Henrique HoeltgebaumDepartment of Mathematics, Imperial College London, London SW7 2AZ, UK.
Swapnil MishraMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Ricardo P SchnekenbergNuffield Department of Clinical Neurosciences, Oxford, UK.
Charles WhittakerMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Harrison ZhuDepartment of Mathematics, Imperial College London, London SW7 2AZ, UK.
Axel GandyDepartment of Mathematics, Imperial College London, London SW7 2AZ, UK.
Christl A DonnellyMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.
Seth FlaxmanDepartment of Mathematics, Imperial College London, London SW7 2AZ, UK.
Samir BhattMRC Centre for Global Infectious Disease Analysis, Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA), School of Public Health, Imperial College London, London, UK.

Funding

Medical Research Council MC_PC_19012Medical Research Council MR/R015600/1
6 · The paper itself

Abstract

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (

Indexed as

PandemicsSARS-CoV-2AdolescentAdultAgedAged, 80 and overBayes TheoremBrazilChildChild, PreschoolCOVID-19FemaleHospitalizationHospitalsHumansInfantadmission-to-deathBrazilCOVID-19model selectionsymptom-onset-to-death

Identifiers

PMID33234065
PMCPMC7729050

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.