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: Data infrastructure; Genomic epidemiology; Microservices; Relational database; SARS-CoV-2.
【저자키워드】 SARS-CoV-2., Genomic epidemiology, Data infrastructure, Microservices, Relational database, 【초록키워드】 public health, SARS-CoV-2, pandemic, Epidemiology, SARS-CoV-2 pandemic, COVID-19 pandemic, variants of concern, variants, Outbreaks, Genome sequencing, pathogen, implementation, Transmission dynamics, genomic, Microservices, Relational database, Threats, help, MONITOR, highlight, resulting, detect, example, exacerbated, increase in, respond, increasingly, Improving, 【제목키워드】 Epidemiology, bioinformatics, genomic, example, Advancing,