Evidence map›Paper›PMID 28396479›Full record

ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2017

Heterogeneities in the case fatality ratio in the West African Ebola outbreak 2013-2016.

Tini Garske, Anne Cori, Archchun Ariyarajah, Isobel M Blake, Ilaria Dorigatti, Tim Eckmanns, Christophe Fraser, Wes Hinsley, Thibaut Jombart, Harriet L Mills and 11 more

Abstract read
In one paragraph

Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 2 pooled it
–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

60 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. A systematic review and meta-analysis of patient data from the West Africa (2013-16) Ebola virus disease epidemic.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2019
    Pooled it
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  11. Sudan Virus Disease among Health Care Workers, Uganda, 2022.The New England journal of medicine · 2024
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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.

Tini GarskeMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.ORCID http://orcid.org/0000-0002-8952-4710
Anne CoriMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.ORCID http://orcid.org/0000-0002-8443-9162
Archchun AriyarajahWHO, 1211 Geneva, Switzerland.
Isobel M BlakeMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Ilaria DorigattiMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Tim EckmannsWHO, 1211 Geneva, Switzerland.
Christophe FraserMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Wes HinsleyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Thibaut JombartMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Harriet L MillsMRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK.
Gemma Nedjati-GilaniMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.ORCID http://orcid.org/0000-0001-5723-5028
Emily NewtonWHO, 1211 Geneva, Switzerland.
Pierre NouvelletMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Devin PerkinsWHO, 1211 Geneva, Switzerland.
Steven RileyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Dirk SchumacherWHO, 1211 Geneva, Switzerland.
Anita ShahWHO, 1211 Geneva, Switzerland.
Maria D Van KerkhoveMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Christopher DyeWHO, 1211 Geneva, Switzerland.
Neil M FergusonMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK.
Christl A DonnellyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London W2 1PG, UK c.donnelly@imperial.ac.uk.ORCID http://orcid.org/0000-0002-0195-2463

Funding

Models for synthesising molecular, clinical and epidemiological data, and translaU01GM110721 · NIGMS · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI CAUCHEMEZ, SIMON, FERGUSON, NEIL MORRIS · 2014 to 2018
$1.9M
NIGMS NIH HHS U01 GM110721World Health Organization 001
6 · The paper itself

Abstract

The 2013-2016 Ebola outbreak in West Africa is the largest on record with 28 616 confirmed, probable and suspected cases and 11 310 deaths officially recorded by 10 June 2016, the true burden probably considerably higher. The case fatality ratio (CFR: proportion of cases that are fatal) is a key indicator of disease severity useful for gauging the appropriate public health response and for evaluating treatment benefits, if estimated accurately. We analysed individual-level clinical outcome data from Guinea, Liberia and Sierra Leone officially reported to the World Health Organization. The overall mean CFR was 62.9% (95% CI: 61.9% to 64.0%) among confirmed cases with recorded clinical outcomes. Age was the most important modifier of survival probabilities, but country, stage of the epidemic and whether patients were hospitalized also played roles. We developed a statistical analysis to detect outliers in CFR between districts of residence and treatment centres (TCs), adjusting for known factors influencing survival and identified eight districts and three TCs with a CFR significantly different from the average. From the current dataset, we cannot determine whether the observed variation in CFR seen by district or treatment centre reflects real differences in survival, related to the quality of care or other factors or was caused by differences in reporting practices or case ascertainment.This article is part of the themed issue 'The 2013-2016 West African Ebola epidemic: data, decision-making and disease control'.

Indexed as

EpidemicsGuineaHemorrhagic Fever, EbolaHumansLiberiaMortalityPublic HealthSierra LeoneWorld Health Organizationcase fatality ratioEbola virus diseasemortalityoutlier detectionseverityspatial heterogeneity

Identifiers

PMID28396479
PMCPMC5394646

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.