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UOA05-11: BEAST and Phylogenetic inference in viral disease epidemiology

Summary of the impact

Research at the University of Oxford into molecular evolution led to the development of BEAST, a powerful suite of computer programs for evolutionary analysis. Viral genome sequences from infected populations can be analysed to infer both viral population history and epidemiological parameters. This approach has been used to track and predict the transmission and evolution of pathogens, particularly viral infections of humans such as influenza and HIV. BEAST was used alongside traditional epidemiological methods by the World Health Organization to rapidly assess and identify the origins of the 2009 H1N1 `Swine Flu' pandemic; immediate recommendations for necessary international action followed. This approach is now widely adopted by health protection agencies and health ministries around the world and is being applied to understand viral diseases of both humans and animals.

Submitting Institution

University of Oxford

Unit of Assessment

Biological Sciences

Summary Impact Type

Health

Research Subject Area(s)

Mathematical Sciences: Statistics
Biological Sciences: Genetics
Medical and Health Sciences: Medical Microbiology

Out of Africa

Summary of the impact

Research in the School of Mathematics & Statistics in the University of Glasgow has been influential in answering a long-standing question: where do we come from? The fleshing-out of the 'out of Africa' theory has been the focus of two documentary series, The Incredible Human Journey and Meet the Izzards, and has generated income for DNA testing companies in the UK and US by enabling them to offer `deep DNA' tests revealing one's roots from far back in history. The Incredible Human Journey aired on BBC 2 in 2009, reaching 10.2 million viewers altogether, has been watched 100,000 times on YouTube and was broadcast in shorter format in Australia and Canada before being released as a DVD. Meet the Izzards was broadcast on BBC 1 in 2013 to over 3 million people.

Submitting Institution

University of Glasgow

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Cultural

Research Subject Area(s)

Mathematical Sciences: Statistics
Biological Sciences: Genetics

C4 - BUGS (Bayesian inference using Gibbs sampling)

Summary of the impact

The WinBUGS software (and now OpenBUGS software), developed initially at Cambridge from 1989-1996 and then further at Imperial from 1996-2007, has made practical MCMC Bayesian methods readily available to applied statisticians and data analysts. The software has been instrumental in facilitating routine Bayesian analysis of a vast range of complex statistical problems covering a wide spectrum of application areas, and over 20 years after its inception, it remains the leading software tool for applied Bayesian analysis among both academic and non-academic communities internationally. WinBUGS had over 30,000 registered users as of 2009 (the software is now open-source and users are no longer required to register) and a Google search on the term `WinBUGS' returns over 205,000 hits (over 42,000 of which are since 2008) with applications as diverse as astrostatistics, solar radiation modelling, fish stock assessments, credit risk assessment, production of disease maps and atlases, drug development and healthcare provider profiling.

Submitting Institution

Imperial College London

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics

SBML, the Systems Biology Markup Language

Summary of the impact

Research into the operational characteristics and applicability of biological reaction networks, carried out at the university in collaboration with groups at Caltech and Sony Systems, revealed the pressing need for a standard format that could be used for storage and exchange of mathematical models of such systems. Hertfordshire researchers played a crucial role in the initial design, dissemination and early exploitation of the Systems Biology Markup Language, SBML, now recognised as the de facto standard format for this purpose. Several major scientific publishers operating across academic boundaries require their authors to use SBML, and 254 software tools, including MATLAB and Mathematica, are now SBML-compliant. Online forums testify to a sizeable, international user-developer community that encompasses engineers, biologists, mathematicians and software developers.

Submitting Institution

University of Hertfordshire

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Computation Theory and Mathematics, Computer Software, Information Systems

01_Phylogenetic analysis software BEAST informs public health responses to infection.

Summary of the impact

Impact: BEAST software has widespread applications with impacts on public health policy, service provision and awareness, and in other contexts such as commercial disputes and criminal cases.

Beneficiaries: Public agencies such as health bodies and criminal courts; ultimately, global and local populations subject to infectious disease epidemic and pandemic outbreaks in which BEAST is used to inform the response.

Significance and Reach: BEAST is critical software that has been used to understand the spread of and to inform the response to global pandemics such as H1N1 swine-flu. It is also used to determine disease origin and transmission issues in specific situations (e.g. in criminal cases). The reach of this software is therefore both global and local.

Attribution: Rambaut (UoE) co-led the phylogenetic research and developed BEAST with Drummond (Auckland, NZ). The subsequent epidemic and pandemic analyses were variously led by Rambaut and Pybus (Oxford) and by Ferguson (Imperial College London).

Submitting Institution

University of Edinburgh

Unit of Assessment

Biological Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Biological Sciences: Genetics
Medical and Health Sciences: Medical Microbiology

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