Advancing genomic epidemiology by addressing the bioinformatics bottleneck: Challenges, design principles, and a Swiss example.
Epidemics
; 39: 100576, 2022 06.
Article
in English
| MEDLINE | ID: covidwho-1851042
ABSTRACT
The SARS-CoV-2 pandemic led to a huge increase in global pathogen genome sequencing efforts, and the resulting data are becoming increasingly important to detect variants of concern, monitor outbreaks, and quantify transmission dynamics. However, this rapid up-scaling in data generation brought with it many IT infrastructure challenges. In this paper, we report about developing an improved system for genomic epidemiology. We (i) highlight key challenges that were exacerbated by the pandemic situation, (ii) provide data infrastructure design principles to address them, and (iii) give an implementation example developed by the Swiss SARS-CoV-2 Sequencing Consortium (S3C) in response to the COVID-19 pandemic. Finally, we discuss remaining challenges to data infrastructure for genomic epidemiology. Improving these infrastructures will help better detect, monitor, and respond to future public health threats.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Computational Biology
/
Genomics
/
Pandemics
/
SARS-CoV-2
/
COVID-19
Type of study:
Observational study
Topics:
Variants
Limits:
Humans
Country/Region as subject:
Europa
Language:
English
Journal:
Epidemics
Year:
2022
Document Type:
Article
Affiliation country:
J.epidem.2022.100576
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