Evidence map›Paper›PMID 36926449›Full record

ArticleVirus evolution2023

Quantifying the value of viral genomics when inferring who infected whom in the 2014-16 Ebola virus outbreak in Guinea.

Alexis Robert, Joseph Tsui Lok Hei, Conall H Watson, Pierre-Stéphane Gsell, Yper Hall, Andrew Rambaut, Ira M Longini, Keïta Sakoba, Adam J Kucharski, Alhassane Touré and 15 more

Erratum issuedFull text read
In one paragraph

Article in Virus evolution, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors.

Alexis RobertDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.
Joseph Tsui Lok HeiDepartment of Biology, University of Oxford, South Parks Road, Oxford OX1 3RB, UK.
Conall H WatsonCentre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.
Pierre-Stéphane GsellWorld Health Organization, Avenue Appia 20, Geneva 1211, Switzerland.
Yper HallUK Health Security Agency, Manor Farm Rd, Porton Down, Salisbury SP4 0JG, UK.
Andrew RambautInstitute of Evolutionary Biology, University of Edinburgh, Ashworth Laboratories, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK.ORCID https://orcid.org/0000-0003-4337-3707
Ira M LonginiDepartment of Biostatistics, University of Florida, 2004 Mowry Road, 5th Floor CTRB, Gainesville, FL 32611-7450, USA.
Keïta SakobaWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Adam J KucharskiDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.
Alhassane TouréWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Sévérine Danmadji NadlaouWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Mamadou Saidou BarryWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Thierno Oumar FofanaWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Ibrahima Lansana KabaWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Lansana SyllaWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Mohamed Lamine DiabyWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Ousmane SoumahWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Abdourahime DialloWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Amadou NiareWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Abdourahamane DialloWorld Health Organization Ebola Vaccination Team, Sonfonia T.7, Conakry, Guinea.
Rosalind M EggoDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.
Miles W CarollWellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Dr, Headington, Oxford OX3 7BN, UK.
Ana Maria Henao-RestrepoWorld Health Organization, Avenue Appia 20, Geneva 1211, Switzerland.
W John EdmundsDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.
Stéphane HuéDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 6HT, UK.ORCID https://orcid.org/0000-0002-8580-6905

Funding

Wellcome Trust 206250/Z/17/ZWorld Health Organization 001
6 · The paper itself

Abstract

Transmission trees can be established through detailed contact histories, statistical or phylogenetic inference, or a combination of methods. Each approach has its limitations, and the extent to which they succeed in revealing a 'true' transmission history remains unclear. In this study, we compared the transmission trees obtained through contact tracing investigations and various inference methods to identify the contribution and value of each approach. We studied eighty-six sequenced cases reported in Guinea between March and November 2015. Contact tracing investigations classified these cases into eight independent transmission chains. We inferred the transmission history from the genetic sequences of the cases (phylogenetic approach), their onset date (epidemiological approach), and a combination of both (combined approach). The inferred transmission trees were then compared to those from the contact tracing investigations. Inference methods using individual data sources (i.e. the phylogenetic analysis and the epidemiological approach) were insufficiently informative to accurately reconstruct the transmission trees and the direction of transmission. The combined approach was able to identify a reduced pool of infectors for each case and highlight likely connections among chains classified as independent by the contact tracing investigations. Overall, the transmissions identified by the contact tracing investigations agreed with the evolutionary history of the viral genomes, even though some cases appeared to be misclassified. Therefore, collecting genetic sequences during outbreak is key to supplement the information contained in contact tracing investigations. Although none of the methods we used could identify one unique infector per case, the combined approach highlighted the added value of mixing epidemiological and genetic information to reconstruct who infected whom.

Indexed as

contact tracingebola virus (RSV)molecular epidemiologyviral transmission

Identifiers

PMID36926449
PMCPMC10013732

What OpenQuestion holds

Textfull text, public
LicenceCC BY
reference markers read1
measurements read9
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.