The group's research response to COVID-19

This is an update on the group's research response to the COVID-19 pandemic. As an infectious disease group we have been keen to contribute to the international research effort where we could be useful, while recognising the need to continue our research on other important infections where possible.

• Bugbank. Thanks to a pre-existing collaboration between our group, Public Health England and UK Biobank, we were in a position to help rapidly facilitate COVID-19 research via SARS-CoV-2 PCR-based swab test results. Beginning mid-March, we worked to provide regular (usually weekly) updates of tests results, which were made available to all UK Biobank researchers beginning April 17th. This is one of several resources on COVID-19 linked to UK Biobank. Beginning in May we provided feeds to other cohorts: INTERVAL, COMPARE, Genes & Health and the NIHR BioResource. We provide updates on this work through the project website www.bugbank.uk. We have published a paper describing the dynamic data linkage in Microbial Genomics (press release). Key collaborators in this project are Jacob Armstrong (Big Data Institute) Naomi Allen (UK Biobank) and David Wyllie and Anne Marie O'Connell (Public Health England).

• COVID-19 Host Genetics Initiative. Along with groups at McGill and the Broad Institute, I have contributed analyses of UK Biobank to investigate genetic risk factors for COVID-19. The Host Genetics Initiative is drawing on more than 200 cohorts from around the world to conduct meta-analysis to tackle questions such as why some people suffer severe COVID-19 while others get mild or asymptomatic infection (media coverage). The meta-analysis results are publicly released periodically. This led to the independent replication of a genetic risk factor on chromosome 3 discovered by a Spanish-Italian cohort and published in the New England Journal of Medicine.

• Epidemiological risk factors for COVID-19. Graduate student Nicolas Arning and I are developing an approach to quantify the effects of lifestyle and medical risk factors for COVID-19 in the UK Biobank that accounts for inherent uncertainty in which risk factors to consider. The new method employs the harmonic mean p-value, a model-averaging approach for big data that we published previously. We are in the process of evaluating the performance of the approach, comparing it to machine learning, and interpreting the results.

• Antibody testing for the UK Government. Postdoc Justine Rudkin has been working in the lab with Derrick Crook, Sir John Bell and others to measure the efficacy of antibody tests for the UK Government. They have tested many hundreds of kits to establish the sensitivity and specificity of the tests to help evaluate the utility of a national testing programme. This work was crucial in demonstrating the limitations of early blood-spot based tests, and the credibility of subsequent generations of antibody tests. The work has been published in Wellcome Open Research.

• Office of National Statistics Antibody Survey. Justine has also been working in the lab with Sarah Walker to set up robots for her large antibody testing cohort study. Sarah is leading an infection survey with the Office of National Statistics to investigate exposure to SARS-CoV-2 in England and Wales.

Work on other infections that has continued during the lockdown. Postdoc Sarah Earle continues research into pathogen genetic risk factors for diseases including tuberculosis and meningococcal meningitis, while Steven Lin has continued to pursue work on hepatitis C virus genetics and epidemiology. Many of our close collaborators are infection doctors and they have of course been recalled to clinical duties. Laboratory work in the group has been severely disrupted, particularly several of Justine's Staphylococcus aureus projects. We are keen to pick up on those projects where we left off when the chance arrives.

Teaching: Online lectures and practical on Phylogenetics in Practice

On March 16th, we were in the interesting position of running an infectious disease course at the Big Data Institute on the day the national lockdown was announced in response to the COVID-19 pandemic. As a result, we were among the first in the university to do remote teaching, something Katrina Lythgoe and the rest of us had prepared for in anticipation of the lockdown a week earlier that never happened.

These are the two online lectures in the Health Data Sciences CDT that I gave called Phylogenetics in Practice.

The online practical, which applies phylogenetics approaches to understand the Zika virus epidemic, is implemented as a Docker container, and available here.

Coalescent inference for infectious disease

Today my student Bethany Dearlove has her first paper published, called Coalescent inference for infectious disease: meta-analysis of hepatitis C. In this paper, published in Philosophical Transactions of the Royal Society B, we have developed coalescent-based population genetics methods for popular, deterministic, epidemiological models known as SI (susceptible-infectious), SIS (susceptible-infectious-susceptible) and SIR (susceptible-infectious-recovered). By implementing these methods in BEAST, we were able to re-analyse previously published hepatitis C virus datasets and directly estimate epidemiological parameters. Our results show that, in the absence of co-infection, the widely-used exponential growth and logistic growth models of changing population size correspond directly to SI and SIS dynamics. We were also able to examine the limitations to genetic approaches to reconstructing epidemiological dynamics.

This paper appears as part of an issue on Next-generation molecular and evolutionary epidemiology of infectious disease, which accompanies a Royal Society discussion meeting organized by Oli Pybus, Christophe Fraser and Andrew Rambaut. The Royal Society has made audio recordings of the talks at this meeting, and the accompanying satellite meeting, available online, including my talk on Bethany's paper.

Geographical differences in transmission revealed by cryptic population structure

Two papers that I co-authored with colleagues at Lancaster and Massey Universities appear this month in the October 2010 issue of Epidemiology & Infection. The common theme is that cryptic differences in the population structure of the enteric pathogen Campylobacter jejuni, revealed by my method for attributing cases to source populations, suggest subtle differences in transmission between rural and urban districts.

The method, implemented in the software iSource (available on my website), allows strains of campylobacter to be characterized as poultry- or cattle-associated based on their genetic profiles. Interestingly, when the relative incidence of poultry- and cattle-associated strains is plotted on a map, there is a significantly higher occurrence of poultry-related disease in urban areas and cattle-related disease in rural areas. Both studies – one in Lancashire led by Edith Gabriel and one in New Zealand led by Petra Mullner – draw the same conclusion. These findings imply that there are subtle differences in transmission in rural and urban areas. Whether they represent geographical differences in the profile of food pathogens, environmental exposure, resistance to infection or other risk factors is not understood.