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Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection

HAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. Aim: We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbrea...

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Autores principales: Kroneman, Annelies, de Sousa, Rita, Verhoef, Linda, Koopmans, Marion P G, Vennema, Harry
Formato: Online Artículo Texto
Lenguaje:English
Publicado: European Centre for Disease Prevention and Control (ECDC) 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6144472/
https://www.ncbi.nlm.nih.gov/pubmed/30229723
http://dx.doi.org/10.2807/1560-7917.ES.2018.23.37.1700802
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author Kroneman, Annelies
de Sousa, Rita
Verhoef, Linda
Koopmans, Marion P G
Vennema, Harry
author_facet Kroneman, Annelies
de Sousa, Rita
Verhoef, Linda
Koopmans, Marion P G
Vennema, Harry
author_sort Kroneman, Annelies
collection PubMed
description HAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. Aim: We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbreak detection. Methods: A descriptive analysis was performed on the timeliness, completeness, epidemiological data and geographic coverage of the dataset. Length and genomic region of the sequences were reviewed as well as the numerical and geographical distribution of the genotypes. The geographical signal in the sequences was assessed based on a short common nt stretch using a 100% identity analysis. Results: The 9,211 reports were heterogeneous for completeness and timeliness, and for length and genomic region of the sequences. Some parts of the world were not represented by the sequences. Geographical differences in prevalence of HAV genotypes described previously could be confirmed with this dataset and for a third (1,075/3,124) of the included sequences, 100% identity of the short common sequence coincided with an identical country of origin. Conclusion: Analysis of a subset of short, shared sequences indicates that a geographical annotation on the level of individual countries is possible with the HAVNet data. If the current incompleteness and heterogeneity of the data can be improved on, HAVNet could become very useful as a worldwide reference set for geographical annotation and for backtracing and outbreak detection.
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spelling pubmed-61444722018-09-27 Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection Kroneman, Annelies de Sousa, Rita Verhoef, Linda Koopmans, Marion P G Vennema, Harry Euro Surveill Research Article HAVNet is an international laboratory network sharing sequences and corresponding metadata on hepatitis A virus in an online database. Aim: We give an overview of the epidemiological and genetic data and assess the usability of the present dataset for geographical annotation, backtracing and outbreak detection. Methods: A descriptive analysis was performed on the timeliness, completeness, epidemiological data and geographic coverage of the dataset. Length and genomic region of the sequences were reviewed as well as the numerical and geographical distribution of the genotypes. The geographical signal in the sequences was assessed based on a short common nt stretch using a 100% identity analysis. Results: The 9,211 reports were heterogeneous for completeness and timeliness, and for length and genomic region of the sequences. Some parts of the world were not represented by the sequences. Geographical differences in prevalence of HAV genotypes described previously could be confirmed with this dataset and for a third (1,075/3,124) of the included sequences, 100% identity of the short common sequence coincided with an identical country of origin. Conclusion: Analysis of a subset of short, shared sequences indicates that a geographical annotation on the level of individual countries is possible with the HAVNet data. If the current incompleteness and heterogeneity of the data can be improved on, HAVNet could become very useful as a worldwide reference set for geographical annotation and for backtracing and outbreak detection. European Centre for Disease Prevention and Control (ECDC) 2018-09-13 /pmc/articles/PMC6144472/ /pubmed/30229723 http://dx.doi.org/10.2807/1560-7917.ES.2018.23.37.1700802 Text en This article is copyright of The Authors, 2018. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0) Licence. You may share and adapt the material, but must give appropriate credit to the source, provide a link to the licence, and indicate if changes were made.
spellingShingle Research Article
Kroneman, Annelies
de Sousa, Rita
Verhoef, Linda
Koopmans, Marion P G
Vennema, Harry
Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title_full Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title_fullStr Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title_full_unstemmed Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title_short Usability of the international HAVNet hepatitis A virus database for geographical annotation, backtracing and outbreak detection
title_sort usability of the international havnet hepatitis a virus database for geographical annotation, backtracing and outbreak detection
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6144472/
https://www.ncbi.nlm.nih.gov/pubmed/30229723
http://dx.doi.org/10.2807/1560-7917.ES.2018.23.37.1700802
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