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The work of Professor Ferguson and colleagues at Imperial College on modelling the effect of different intervention measures on the spread and health impact of a new influenza pandemic has substantially shaped UK and international public policy-making over the last 7 years. Prior to 2009, this work shaped UK policy on antiviral and pre-pandemic vaccine stockpiling and use, and on the potential use of school closure and border restrictions during a pandemic. During the 2009 H1N1 pandemic, real-time research provided the first estimates of key epidemiological parameters of the new pandemic virus, demonstrating the low-to-moderate severity and lower than typical transmissibility. In the UK, US and other countries, these data informed public policy decisions to pull back from use of economically costly interventions (such as reactive school closure or antiviral prophylaxis) and focus on targeted use of vaccination as the principal pandemic mitigation measure.
Research on novel statistical methods for disease surveillance and influenza vaccine effectiveness has led to the development of a suite of automatic systems for detecting outbreaks of infectious diseases at Health Protection Scotland (HPS). This work has improved the public health response and helped to reduce costs in Scotland and also in the wider UK and EU by providing real-time early warning of disease outbreaks and timely estimates of the effectiveness of the influenza vaccine. This research, commissioned by the Scottish Government, through HPS, and also the UK National Institute for Health Research (NIHR) and the European Centres for Disease Control (ECDC), but used in a wider context by many others, formed the basis for the HPS response to the H1N1 Influenza Pandemic and monitoring of the effects of Influenza Vaccines.
Research conducted by LSHTM into how governments and international organisations are preparing for an influenza pandemic has made an important contribution towards efforts to avoid the risks of up to 150m deaths anticipated by WHO in the event of such a pandemic. Governments, including the UK, and global institutions, have made policy changes and resource allocation decisions directly as a result of this research and technical advice.
Research carried out by the Health Protection and Influenza Research Group (HPIRG), Division of Epidemiology and Public Health, impacted directly on the UK Government's response to the 2009 influenza pandemic, feeding directly into policy-making decisions. The group was appointed as an official WHO Collaborating Centre for pandemic influenza in 2010 and through its related research has "reduced the economic impact on Member States for pandemic preparedness" (quote from reference 7, section 5). In 2011, it secured £7M funding from the US Centers for Disease Control and Prevention (CDC) to lead `once only' work to determine the modes of influenza transmission using a human challenge model.
Pioneering interdisciplinary research at the Royal Veterinary College (RVC) has enabled governments internationally and global health authorities to respond swiftly to the outbreak of a disease that causes huge economic losses, threatens the livelihoods of vulnerable populations in the developing world and endangers human lives. Supported by proactive dissemination, it has shaped the control policies and risk management strategies of the United Nations and governments across Asia, Africa and Europe, as well as a national contingency plan for the UK. And it has demonstrated that costly vaccination campaigns and mass culling programmes can be avoided in efforts to bring the disease under control.
Mathematical modelling of livestock infections and disease control policies is an important part of planning for future epidemics and informing policy during an outbreak of infectious disease. Researchers in the Mathematics Institute, University of Warwick, are considered to be at the cutting-edge of developing policy-orientated mathematical modelling for a number of livestock infections. Such models have been used to inform government policy for foot-and-mouth disease (FMD) and a range of other infections including bovine tuberculosis (bTB) and bee infections. From 2008, their work with responsible national and international agencies has focused on statistical inference from early outbreak data, formulating models and inferring parameter values for bTB infection spread within and between farms, developing predictive models of FMD outbreaks in the USA, and extending such models to areas where FMD is endemic. This research has helped to shape policy and determined how policy-makers perceive and use predictive models in real-time.
Research undertaken at UCL's Centre for Infectious Disease Epidemiology has provided evidence about vaccination of different groups against influenza which have influenced policy and practice. In particular, our work underpins the government's ongoing policy on vaccination of healthcare workers, and is cited every year in the Chief Medical Officer's letter to healthcare workers as well as international recommendations on influenza vaccination of healthcare workers, including widespread mandatory vaccination programmes in North America. Research on influenza and acute cardiovascular events has informed US recommendations for prevention of stroke through vaccination. Recent work also informed the decision in the UK to extend regular influenza vaccination to children.
Researchers in the University of Cambridge's Department of Zoology have developed a new methodology to analyse pathogen evolution. This `antigenic cartography' has led to the group becoming integrally involved in the World Health Organisation (WHO) influenza vaccine strain selection process, and has directly contributed to more accurate and appropriate flu vaccine design, with associated international impacts on disease prevention and public health (the flu vaccine is given to ~350 million people annually). The research has directly affected how public health professionals conduct disease surveillance and sampling.
Professor Trevor Bailey of the University of Exeter led the methodological and computational development of new improved mathematical models to more fairly allocate resources, and particularly mental health resources, to GP practices in the UK within an interdisciplinary research team from the universities of Plymouth, Southampton and St Andrews. The mental health services component of NHS Practice based commissioning (PBC) introduced by the Department of Health (DoH) from 2007 onwards, deals with resource allocation for specialist healthcare for some 400,000 patients with severe mental illness. From 2009 to 2011, the team's mental health estimates, based upon the modelling efforts of Bailey, were used to set practice-level PBC budgets accounting for around £8 billion of NHS funding, the DoH describing this as a `step-change improvement' in how mental health needs are modelled.
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).