Source: Massey University
Genome sequencing has become an increasingly important tool in containing and tracing COVID-19. Virus samples taken from a diagnosed patient are sequenced and compared with other cases to identify whether cases are linked. Genomic sequencing allows health authorities to map COVID-19 clusters and matching the genomic findings of a COVID-19 case to epidemiological information can help the government track the source of the virus.
Prior to COVID-19, genomic sequencing has been used in a variety of ways such as tracing the source of outbreaks of food and water-borne bacteria, hospital infections, and Mycoplasma bovis.
Genome sequencing for all SARS-COV-2 positive cases is performed by ESR, where they analyse the virus sample taken from a diagnosed patient and compare it with other cases. The sample [swab] goes through several steps to separate the RNA molecules from other material so they can be captured, then read using sequencing technology. Early on in the pandemic, researchers from Massey University, Olin Silander and Nikki Freed, developed and published novel sequencing protocols that have enabled faster turnaround times.
Professor French says he is working with the genomics team on phylodynamic modelling – an approach that combines the dynamics of epidemiological and evolutionary processes.
“I’m working with a small group to try and use techniques developed by members of the team to inform the response on an ongoing basis. We’re analysing the genome sequence data and using modelling to see if we can identify the source of new infections in the community.
“We receive a number of cases where they’re not quite sure what the origin is, from there we use our models to provide a likely transmission source, which we can then provide to the teams that are directly involved in managing the response, including the contact tracers,” Professor French says.
He says the turnaround time for providing insights on genomic sequencing has improved a lot in this pandemic.
“I think one of the key things is that from the beginning we were able to get a genome sequence from a reasonable number of the cases that were arising – and then being able to analyse them. However, this wasn’t done in ‘real time’ prior to COVID-19.
“What’s happened since the start of the pandemic is that the time span has shortened greatly, and now we’re getting sequences in a short period of time, and able to analyse them and provide information back to the decision makers.
“This has been useful for a whole number of things. One of them is just making sure that you’re still dealing with the same outbreak. You haven’t got a new one coming in. You can assign cases to clusters within them to identify what the likely transmission was.”
Professor French is working alongside scientists; Joep de Ligt and Una Ren from ESR, Jemma Geoghegan from ESR and University of Otago, David Welch and Jordan Douglas from the University of Auckland, and James Hadfield from the Bedford Lab. The team is aiding with the COVID-19 tracing, using genomics and modelling to help identify where and how initially unlinked cases caught COVID in the community, sometimes referred to as mystery cases.
Professor French has recently co-authored a few papers with various teams on COVID-19 – the most recent one ‘Real-Time Genomics for Tracking Severe Acute Respiratory Syndrome Coronavirus 2 Border Incursions after Virus Elimination, New Zealand.’
The genomics team have created a narrative, using the Nextstrain tool developed by James Hadfield, which provides an interactive way of visualising COVID outbreaks in NZ. They have also published an article in the Conversation on why rapid genome sequencing is key to finding out how long Delta has been in NZ. The article can be found here.
In addition to the genomic epidemiology work, Professor French has contributed to other COVID-related research papers. A couple of them include:
- COVID-19 in New Zealand and the impact of the national response: a descriptive epidemiological study. Lancet Public Health 5, e612-e623. doi: 10.1016/S2468-2667(20)30225-5
- COVID-19 vaccine strategies for Aotearoa New Zealand: a mathematical modelling study. Lancet Reg Health West Pac 15, 100256. doi:10.1016/j.lanwpc.2021.100256