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How can we track new variants of COVID-19 as they emerge? In this blog, Áine O’Toole and Verity Hill (University of Edinburgh) introduce ‘grinch’ – a new Software Tool which tracks the international spread of new variants of the virus through automated daily reports. Keep reading to find out how collaboration and global teamwork were critical to their research project.

All viruses change over time, and SARS-CoV-2 is no different. Throughout the pandemic the virus has evolved, and new variants have emerged, posing an increased risk to public health. Changes to the virus’s genetic structure can make it easier for a variant of the virus to be transmitted from one person to another, like Delta, which is estimated to be the most contagious variant detected so far. A faster spreading variant could increase hospitalisations and possibly deaths. There is concern that more infectious variants could be resistant to current vaccines.

To help monitor and assess the threat of these developments, the variants are characterised in two groups; Variants of Interest (VOI) and Variants of Concern (VOC). VOCs are defined as a strain that increases transmissibility of COVID-19, increase virulence and/or decrease the effectiveness of public health measures. These variants are more likely to cause severe disease. Alpha, Beta, Gamma, and Delta are all designated VOCs.  VOIs such as Lambda and Mu, are strains where genetic changes affect the characteristic of the virus.

Monitoring the global spread of COVID-19

We developed ‘grinch’, a new software tool to track variants on an international scale. This provides dynamic daily reports for public health bodies and institutions to use around the world. Since the primary way to globally track variants is through viral genomic data, we used this as a baseline in our tool to track the emergence, distribution and arrival of new VOCs.

However, we can’t rely on genomic data alone to assess the spread of a new variant, especially in the early days of its discovery. So, we used travel data. We added passenger flight numbers to our tool from the countries/location where variants, such as Alpha and Beta, were first reported. This data also helps us to predict where variants could appear in the near future.

We decided to strengthen the reports with additional contextual information about the surveillance system in each country, using media reports and metadata published via GISAID. For example, some countries, like Denmark, perform regular population level surveillance, while others, like Australia and New Zealand, focus on data on returning travellers.

All this information is important when trying to estimate the potential downstream implications of new variants (for example, estimating increased transmissibility or severity). 

How to keep up with the evolution of COVID-19   

Information about new variants is changing daily. To keep up, we built grinch to run automatically, processing data every day. This is essential as we anticipated that more variants would be detected, as we’re seeing in this pandemic. Grinch runs custom scripts to summarise data from GISAID, generate the figures, and then update the website. This provides up to date reports, with detailed maps, charts and sequence data.  

We’re all in this together

Variants affect all of us. We can only contain them by working together and identifying, tracking, and responding to them. We made an effort to include all collaborators who have been instrumental in generating the virus genome data necessary to track them globally.

Initially, we were only tracking Alpha (B.1.1.7). Then our collaborators in South Africa got in touch about a new variant that evolved there. We investigated it using flight passenger data and so started to track the spread of Beta (B.1.351) too. This is just one of the great examples of this truly global collaboration. 

It was important for us that all authors were properly credited for this collaborative piece of work, so we chose to publish on Wellcome Open Research, as the platform has no limits on the number of authors we could include. We relied on open data sources to collect our data in real-time to discover and track variants. It was also vital that our article was open access, as we wanted to support truly open and equitable scientific research.

Informing public health interventions

By documenting the occurrence and distribution of variants we hope to raise awareness and increase efforts for molecular surveillance of COVID-19. To further support public health measures, we would like to add more information about the underlying surveillance methods in each country to improve our protocols to collate molecular data to include population-based sampling. Information about human mobility should also enable us to better target surveillance in areas where there is a high degree of mobility but low overall sampling effort.

Next steps

There is a lot more information that we would like to add to our tool. For example, incidence data in origin and destination country to estimate the importation intensity of a new variant to a new location.

At this stage our data is at the country level. In future iterations we may want to include sub-national estimates to provide better information for the communities affected by the emergence of new variants, and ultimately to enable faster responses to support their containment.

The scripts are set up to easily integrate new lineages if required, and that has already been undertaken a few times with VOIs which evolved after the tool was first written.

It’s early days for grinch – we’re excited to see what’s next as the tool evolves!

You can read the Software Tool Article and its peer review reports on Wellcome Open Research here: Tracking the international spread of SARS-CoV-2 lineages B.1.1.7 and B.1.351/501Y-V2 with grinch [version 2; peer review: 3 approved]