High performance compute for CVR Preparedness platform

A high-performance computing system will support the work of the MRC-University of Glasgow Centre for Virus Research in the area of pandemic and outbreak preparedness with focus on virus threats. This is aligned with the ongoing need for research and surveillance to understand new and emerging threats from viral illness, and to optimise the public health response to these concerns.

Research in virology is becoming increasingly data-driven, with the SARS-CoV-2 pandemic having led to the generation of approaching 15 million viral genome sequences. At the same time research is becoming more and more interdisciplinary, with mathematicians, statisticians, computer scientists and computational biologists working alongside experimental research groups to make progress.

Our preparedness theme is highly integrated with national efforts in public health, and with international research efforts in Malawi, Tanzania and Uganda. Communication between researchers and public health experts is vital in making the best possible response to new threats to human health.

The new computing system will allow the large amounts of data necessary for research to be stored and rapidly shared between researchers in the CVR and with partners. It will enable researchers with expertise in different research disciplines to share ideas and work together more effectively. The computing power provided by the system will enable the use of new methods to analyse data and increase the speed with which results can be generated and passed on to public health agencies.

Research facilitated by the computing system will be focused in the area of virus preparedness and surveillance, studying the impact of both novel viruses and new variants of known viruses. We will continue to monitor the impact of SARS-CoV-2 upon human health, linking viral genome sequence data with healthcare outcomes. As the SARS-CoV-2 virus evolves in response to vaccination and acquired human immunity, we will monitor the biological consequences of genetic changes in the virus.

We will extend work begun in the early phases of the pandemic to track and prevent the spread of viral infection in hospitals and other public health settings, working on the integration of statistical tools with electronic patient record systems; our vision is that viral genome sequence data could be used in real time to inform the work of infection prevention and control. We will look into the causes of unexplained cases of severe respiratory infection in hospitals.

Further work will aim to predict the evolution of SARS-CoV-2. We will assess the extent of the threat posed by new variants of the virus escaping the protection provided by acquired immunity and vaccination. Experimental techniques will be combined with machine learning to evaluate whether previous patterns of evolution, observed as the virus has spread to infect people worldwide, can be repeated in the lab.

The observation of repeatable patterns would suggest that future changes in the virus might be possible to predict.

Additionally, the computing system will provide facilities for work to identify outbreaks of highly pathogenic viruses at the earliest possible stage and contribute to research in a timely manner. The system will facilitate the identification of undiagnosed cases of infection among travellers returning to the UK, and the investigation of potential outbreaks spreading from animal populations into humans in Uganda.

Overall the high performance computing system will provide the computational backbone for an essential area of research within the scientific portfolio of the Centre for Virus Research, supporting research of national and international importance and empowering a broad range of collaborations with researchers and public health experts in the UK and overseas.