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Fraser Pathogen Dynamics Group

Fraser Group.png

About Us

We are a group of scientists with expertise in infectious disease epidemiology, phylogenetics, mathematical modelling, maths, virology and outbreak response, led by Christophe Fraser. We spent the last few years working on HIV and antibiotics resistance and have now started a new research programme on coronavirus in response to the pandemic.

We are always looking for bright and committed people. If you would like to work with us on one of the projects mentioned below, please check out our vacancies on the right or contact and for further information and upcoming positions.

COVID-19 Contact

Tracing apps





PopART / Inputt




COVID-19 contact tracing apps

Since January 2020, we have been working on COVID-19, trying to find ways to stop the epidemic. We investigated in depth the idea of contact tracing using a mobile phone app and published a paper in Science detailing the maths behind this approach. This led to the development of a contact tracing app by the NHS, the national health service in England and Wales. We went on to develop an individual-based simulation of interventions against COVID-19 including manual and digital contact tracing which is open source and available on Github. We then worked with Google Research to estimate the potential impact of the Google Apple contact tracing system. Currently, we are looking at network effects in COVID-19 epidemiology and contact tracing.

Publications: Ferretti, Wymant et al 2020, Kendall et al 2020, Hinch, Probert et al 2020, Abueg, Hinch et al 2020, Ferretti et al 2020

Further documents on Github:


COVID-19 sequencing

As part of the COVID-19 Genomics UK (COG-UK) consortium, we are helping to deliver large-scale rapid whole-genome virus sequencing to local NHS centres and the UK government. The virus genome data is combined with clinical and epidemiological datasets in order to help guide UK public health interventions and policies. The subsequent analysis will permit evaluation of the effectiveness of novel treatments and non-pharmacological interventions on SARS-CoV-2 populations and spread. It will provide information on whether or not outbreaks are due to introductions from outside or ongoing transmission within the community. The data will also enable researchers to identify and understand genetic changes that affect how easily the virus is passed on and the severity of the symptoms it causes. Finally, the information helps target the development of treatments and vaccines and monitor their impact as they are introduced. In the Fraser group, we have a project on the within-host diversity of SARS-CoV-2 virus.

Publications: Lythgoe, Hall et al


twitter.png @HIVPangea

PANGEA (Phylogenetics and Networks for Generalised HIV Epidemics in Africa) uses modern molecular epidemiology and phylodynamics of HIV sequences to study transmission dynamics in HIV epidemics in Southern Africa. In recent years, anti-retroviral therapy and preventive therapy has become more readily available in Africa, but tools to assess the efficacy of current interventions and improvements in care are missing. Understanding how and in which groups of a population the virus is spreading will not only help to monitor epidemics, but also enable policy makers to design intervention programmes and assess their impact. To collect the data for this ambitious analysis, partners across Africa, the United States and Europe have come together to generate and analyse over 13,000 viral sequences from dried blood spots collected in Uganda, Zambia, Botswana and Uganda. PANGEA was first funded by the Bill and Melinda Gates Foundation in 2013 and was renewed in 2017 to run until the end of 2021. While the first phase of the project centred on sample collection and sequencing, the second phase focusses on data analysis and providing datasets for policy evaluation. The second phase has four themes that provide the umbrella for scientific investigations carried out by the consortium: mobility and migration, clinical science, drug resistance and ethics, molecular epidemiology and mathematical modelling, and phylodynamics.

Publications: Pillay et al 2015Yebra et al 2016Ratmann et al 2017Ratmann, Hotcroft et al 2017Coltart et al 2018Abeler-Dörner et al 2019Ratmann et al 2019Bbosa et al 2019Bbosa et al 2020



PopART (Population Effects of Antiretroviral Therapy to reduce HIV Transmission) is the largest HIV trial conducted to date, with over 1.2 million participants in 21 communities in South Africa and Zambia. In these communities, 15 to 30% of the population is HIV positive, which reflects the fact that despite the availability of antiretroviral therapy (ART), HIV incidence rates remain high in many parts of southern Africa. PopART assessed which treatment strategies are effective and evaluated not only access to ART, but also a package of additional interventions like HIV counselling and home visits by community workers.

Our group was responsible for the mathematical modelling of the epidemic in the study communities. The aim was to assess the effectiveness of the preventions and calculate the costs for rolling them out on a larger scale. The trial is unblinded now and initial analyses are published. The analysis continues in the INPUTT project.

Team: Will Probert, Rob Hinch, Christophe Fraser, previously Mike Pickles, Anne Cori, Rafael Sauter

Publications (selection): Cori et al 2014Hayes, Ayles et al 2015Hayes, Fidler et al 2015Bond et al 2018, Floyd et al 2018Hayes et al 2019, Seeley et al 2019



PopART Phylogenetics is an ancillary study to the main PopART study. It uses phylogenetic techniques to analyse approximately 7800 samples obtained from the PopART patient communities in Zambia. The aims are to estimate the proportion of transmission events that occur during acute and early HIV infection (and therefore before the start of treatment) and identify demographic, clinical and epidemiological factors that contribute to HIV transmission. Using phylogenetic methods will also allow us to estimate the proportion of transmission events that occur within and outside the PopART communities.

Protocol: Study protocol pdf download



AMPHEUS stands for Analytics and Microbiology for Precision Health and Epidemiology - A Unified Solution. Funded by the Bill and Melinda Gates Foundation, AMPHEUS aims to deliver a single integrated platform for clinical microbiology, real-time epidemiology and intervention research to fight infectious pathogens in low income settings. The project will develop a scalable laboratory infrastructure, initially in Zambia, for rapid diagnostics and whole genome viral sequencing. The lab will link to digital technologies to broaden access to molecular diagnostics while informing public health efforts aimed at prevention and improved clinical outcomes.

Publications: Bonsall, Golubchik et al 2019



The 18-month study to measure the prevalence and spread of COVID-19 (SARS-CoV-2) in a community in Zambia will be nested within the ongoing TREATS study. The TREATS study is currently measuring whether HPTN071 PopART reduced the prevalence and incidence of tuberculosis in the study communities in Zambia and South Africa, since persons living with HIV suffer more often from active TB than HIV negative people. The results will be extrapolated to the wider population of Zambia using mathematical modelling, shedding much needed light on the epidemiology of the virus in sub-Saharan Africa, where COVID-19 infections and deaths continue to rise.



The ARTIC project builds on the experience from the 2014 Ebola outbreak in West Africa and the 2016 Zika outbreak and aims to build a response system that spans all the way from acquiring samples in the outbreak area to generating real-time epidemiological information that can be used for decision making by public health bodies. The project has five components: (1) Developing a lab in a suitcase for efficient use in the field, (2) Improving PCR methods to identify the virus causing the epidemic and adopting Oxford Nanopore sequencing technology (“sequencing in a USB stick”) to high-throughput work, (3) Developing an off-line bioinformatics package that can be used by non-expert users without the need of a high-speed internet connection to transfer large sequence data files, (4) Development of a real-time phylodynamics analysis that can incorporate new data as more sequences become available during the epidemic, and (5) Visualisation of the results to make them interpretable for users at public health bodies. We are involved in the phylodynamics analysis of ARTIC.

Publications: Rambaut et al 2020



BEEHIVE (Bridging the Epidemiology and Evolution of HIV in Europe) is a cross-European study of HIV genomics and virulence amongst seroconverters. It builds on the discovery that virus levels found after the infection has become established (set-point viral load) is similar in patients which have been infected by the same source. This suggests that set-point viral load and, by association, severity of disease are at least partly determined by the viral genome. BEEHIVE aims to assemble 4500 viral sequences from HIV patients across Europe and use this data to discover and characterise viral mutations or combinations of mutations that influence the severity of disease. The quality of the sequences will allow us to study viral diversity in single patients while the quality of the associated metadata will allow for the identification of sub-epidemics and risk factors for onward transmission.

Publications: Fraser et al 2014Blanquart et al 2017Wymant, Hall et al 2017, Wymant et al 2018