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Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013732/ https://www.ncbi.nlm.nih.gov/pubmed/36926449 http://dx.doi.org/10.1093/ve/vead007 |
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author | Robert, Alexis Tsui Lok Hei, Joseph Watson, Conall H Gsell, Pierre-Stéphane Hall, Yper Rambaut, Andrew Longini, Ira M Sakoba, Keïta Kucharski, Adam J Touré, Alhassane Danmadji Nadlaou, Sévérine Saidou Barry, Mamadou Fofana, Thierno Oumar Lansana Kaba, Ibrahima Sylla, Lansana Diaby, Mohamed Lamine Soumah, Ousmane Diallo, Abdourahime Niare, Amadou Diallo, Abdourahamane Eggo, Rosalind M Caroll, Miles W Henao-Restrepo, Ana Maria Edmunds, W John Hué, Stéphane |
author_facet | Robert, Alexis Tsui Lok Hei, Joseph Watson, Conall H Gsell, Pierre-Stéphane Hall, Yper Rambaut, Andrew Longini, Ira M Sakoba, Keïta Kucharski, Adam J Touré, Alhassane Danmadji Nadlaou, Sévérine Saidou Barry, Mamadou Fofana, Thierno Oumar Lansana Kaba, Ibrahima Sylla, Lansana Diaby, Mohamed Lamine Soumah, Ousmane Diallo, Abdourahime Niare, Amadou Diallo, Abdourahamane Eggo, Rosalind M Caroll, Miles W Henao-Restrepo, Ana Maria Edmunds, W John Hué, Stéphane |
author_sort | Robert, Alexis |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10013732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100137322023-03-15 Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea Robert, Alexis Tsui Lok Hei, Joseph Watson, Conall H Gsell, Pierre-Stéphane Hall, Yper Rambaut, Andrew Longini, Ira M Sakoba, Keïta Kucharski, Adam J Touré, Alhassane Danmadji Nadlaou, Sévérine Saidou Barry, Mamadou Fofana, Thierno Oumar Lansana Kaba, Ibrahima Sylla, Lansana Diaby, Mohamed Lamine Soumah, Ousmane Diallo, Abdourahime Niare, Amadou Diallo, Abdourahamane Eggo, Rosalind M Caroll, Miles W Henao-Restrepo, Ana Maria Edmunds, W John Hué, Stéphane Virus Evol Research Article 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. Oxford University Press 2023-03-07 /pmc/articles/PMC10013732/ /pubmed/36926449 http://dx.doi.org/10.1093/ve/vead007 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Robert, Alexis Tsui Lok Hei, Joseph Watson, Conall H Gsell, Pierre-Stéphane Hall, Yper Rambaut, Andrew Longini, Ira M Sakoba, Keïta Kucharski, Adam J Touré, Alhassane Danmadji Nadlaou, Sévérine Saidou Barry, Mamadou Fofana, Thierno Oumar Lansana Kaba, Ibrahima Sylla, Lansana Diaby, Mohamed Lamine Soumah, Ousmane Diallo, Abdourahime Niare, Amadou Diallo, Abdourahamane Eggo, Rosalind M Caroll, Miles W Henao-Restrepo, Ana Maria Edmunds, W John Hué, Stéphane Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title | Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title_full | Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title_fullStr | Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title_full_unstemmed | Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title_short | Quantifying the value of viral genomics when inferring who infected whom in the 2014–16 Ebola virus outbreak in Guinea |
title_sort | quantifying the value of viral genomics when inferring who infected whom in the 2014–16 ebola virus outbreak in guinea |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10013732/ https://www.ncbi.nlm.nih.gov/pubmed/36926449 http://dx.doi.org/10.1093/ve/vead007 |
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