Genomics-informed outbreak investigations of SARS-CoV-2 using civet

Áine O'Toole, Verity Hill, Ben Jackson, Rebecca Dewar, Nikita Sahadeo, Rachel Colquhoun, Stefan Rooke, J T McCrone, Kate Duggan, Martin P McHugh, Samuel M Nicholls, Radoslaw Poplawski, David Aanensen, Matt Holden, Tom Connor, Nick Loman, Ian Goodfellow, Christine V F Carrington, Kate Templeton, Andrew Rambaut

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 13 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different 'catchments' and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.

Original languageEnglish
Article numbere0000704
Number of pages15
JournalPLOS Global Public Health
Issue number12
Publication statusPublished - 9 Dec 2022


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