What is it about?

COVID-19 taught us that we can sequence millions of virus genomes during infectious disease outbreaks - but there might be better ways of tracking the spread and evolution of pathogens. We can't sustainably sequence every genome of SARS-CoV-2 - and even if we could, our models are unable to incorporate that amount of genetic data. In this piece, public health and virus evolution experts discuss how genome surveillance alone may not be sufficient for tracking how pathogens spread and evolve.

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Why is it important?

Public health teams and researchers around the globe used genome data to model SARS-CoV-2 spread to provide estimates that informed outbreak responses in real-time. Phylodynamic modelling has played a major role in the COVID-19 response, utilising epidemiological and genomic data to explore how evolution and epidemiology drive the underlying patterns of SARS-CoV-2. For example, in Australia, genome data traced the majority of cases in a large outbreak to a single hotel quarantine breach, leading to major changes in policy regarding the management of Australian quarantine facilities. However, there are many other sources of data that we could utilise in our phylodynamic models. We call it "metadata", including examples like travel history or vaccination status. We also suggest the establishment of surveillance systems - in particular, wastewater surveillance and tracking zoonotic spillover events in livestock and wildlife.


Phylodynamic modelling has proved immensely useful for understanding how SARS-CoV-2 has spread and evolved during the COVID-19 pandemic. We could use even more complex and informative models if we dedicated some of our resources towards different kinds of metadata, along with a strategic subset of genomic sequence data. We are also missing part of the broader picture of SARS-CoV-2 evolution, as we are lacking surveillance in livestock and wildlife.

Ash Porter
University of Melbourne

Read the Original

This page is a summary of: New rules for genomics-informed COVID-19 responses–Lessons learned from the first waves of the Omicron variant in Australia, PLoS Genetics, October 2022, PLOS,
DOI: 10.1371/journal.pgen.1010415.
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