Dr Daniela De Angelis and colleagues at the Medical Research Council Biostatistics Unit, based at the University of Cambridge, use statistical methods to understand how diseases spread and how interventions impact them. Their novel approach to estimating the HIV burden is used to obtain UK official annual HIV prevalence estimates, which help inform national policy.
Human immunodeficiency virus (HIV) has been a serious public health concern in the UK, and continues to be one of the biggest epidemics of our time. It is estimated that in 2014, over 100,000 people living in the UK had HIV, 1 and that 36.7 million individuals were living with HIV globally in 2015. 2 The disease, which attacks the body’s immune system and compromises its ability to combat infections and diseases, 3 is associated with serious morbidity, and high costs of treatment and care. Though there is no cure, early diagnosis and treatment can prevent HIV from moving into the advanced stage (acquired immune deficiency syndrome [AIDS]), in which the body is unable to fight off life-threatening infections. 4
Robust monitoring of the disease burden is crucial in order to effectively plan care provision and the implementation and evaluation of public health policies, which seek to reduce the transmission of the disease. The disease burden includes the proportion (prevalence) of individuals living with HIV, and the number of infections remaining undiagnosed, in both the general population, and within specific groups at high risk of infection. Quantifying the size of the infected and undiagnosed portion of the epidemic is particularly important as undiagnosed individuals cannot benefit from the highly effective treatments available and they can unknowingly spread the disease, which will impact the need for HIV services.
As a statistician, it is very interesting to be involved in substantive public health research and to make a real difference to HIV policies. There is a continued need for statisticians to provide important quantitative evidence in support of a range of public health decisions.
–Dr De Angelis
Dr De Angelis and her team at the Medical Research Council’s (MRC) Biostatistics Unit (BSU) provide much needed estimates on the HIV burden. Their novel Multi-Parameter Evidence Synthesis (MPES) approach to estimating the HIV burden 5 has been, and continues to be, the chosen method to obtain UK official annual HIV prevalence estimates. 6 For over a decade BSU has worked with Public Health England (PHE) to provide evidence for the annual reports on the state of the HIV epidemic in the UK. 7
The philosophy underlying the MPES approach is that estimation of epidemiological quantities of interest on which direct information is unavailable or inadequate, such as the HIV burden, can be informed by the combination of disparate and imperfect sources of evidence. Data are combined through a statistical model that exploits data fully, typically leading to more precise and less biased estimates than approaches that rely on selected “best quality” information.
BSU’s work on HIV for policy guidelines in the UK is the result of a long-standing collaboration between PHE and BSU, which started in the 1990s through Dr De Angelis’ work on projection of AIDS cases. Since then, the partnership has expanded to working on Hepatitis C and B, as well as to respiratory infections.
The specific work on the MPES approach to HIV prevalence was initiated by a jointly funded collaboration between the MRC, the University of Bristol and PHE in the early 2000s. It progressed through BSU supporting methodological capacity at PHE and assisting with the application and development of the method over the years.
Because they recognise how critical these statistics are to health policy, Dr De Angelis and her team engage in regular workshops with PHE and key stakeholders. These include the House of Commons All Party Parliamentary Group on HIV & AIDS and the “Halve It” campaign – a coalition of member organisations including the National Institute for Health and Care Excellence, the Department of Health and the Local Government Association. These relationships help keep the team updated on new developments in this evolving area of research, and contribute to discussions on future plans for methodological support of HIV.
The Unit’s MPES work has directly influenced policy. The MPES approach has been regularly implemented since 2005 and further developed to accommodate new information and important changes in data collection. 8 Since 2010, estimates of the number of undiagnosed HIV infections have underpinned public initiatives to encourage HIV testing, for example, working with the “Halve It” campaign to half the proportion of undiagnosed infections by 2020.
In 2011, the MPES prevalence and incidence estimates were presented as evidence to the House of Lords Select Committee on HIV and AIDS in the UK, 9 helping to motivate major charity and publicly funded testing campaigns. The Terence Higgins’ Trust’s “It Starts with Me” campaign and the more recent National HIV prevention Programme for England both rely on the group’s findings.
BSU’s HIV prevalence estimates have also been employed in other public health settings. For example, they are used to help inform the evaluation of deferral criteria for homosexual men wishing to donate blood, 10 which in turn informed the recent decision to change the length of the donor deferral period for men who have sex with men. 11 12
Similarly to HIV, the MPES approach has been used to quantify flu severity, both in the UK and the USA, 16 17 and to produce estimates of Hepatitis C prevalence, 18 19 20 21 which have also become the official estimates in the UK and form the basis for a commissioning template, informing policy. 22
Continued research into HIV is vital to continue to understand how many people are being affected by the disease in the UK, including in minority population groups, such as Black African and Black Caribbean groups.
The MPES estimates on prevalence are continuing to generate debates over testing for HIV, currently focusing on different ethnic groups affected by HIV in the UK.
Estimates of the HIV burden have and will go on to contribute to HIV policy guidelines in the UK. Dr De Angelis’ team is extending its international collaborations to develop and apply their MPES methodology to low income countries, such as Uganda and Kazakhstan, in order to improve their understanding of the key populations at risk for HIV and the magnitude of their HIV burden.
Key learnings for researchers
• Establish and develop relationships with policymakers, through regular contact
• Attend relevant policy meetings and events where there might be opportunities to communicate with policymakers and contribute to key decision making
• Communicate key findings in a style and format that is easy to understand
- “No vaccine, no cure: HIV and AIDS in the United Kingdom Report.” House of Lords. 1 September 2011, accessed 9 May 2017. http://www.publications.parliament.uk/pa/ld201012/ldselect/ldaids/188/188.pdf.
- The UK Collaborative Group for HIV and STI surveillance. “Mapping the Issues: HIV and other Sexually Transmitted infections in the United Kingdom.” Health Protection Agency Centre for Infections, 2005.
- The UK Collaborative Group for HIV and STI Surveillance. “A complex picture: HIV and other sexually transmitted infections in the United Kingdom.” Health Protection Agency Centre for Infections, 2006.
- The UK Collaborative Group for HIV and STI Surveillance, “Testing Times: HIV and other Sexually Transmitted Infections in the United Kingdom.” Health Protection Agency Centre for Infections, 2007.
- “Living with HIV,” National Aids Trust, 2017, accessed 9 May 2017, http://www.nat.org.uk/HIV-in-the-UK/HIV-Statistics/Latest-UK-statistics.aspx. ↩
- “WHO Director-General hails progress in HIV and hepatitis,” World Health Organization, 4 May 2017, accessed 9 May 2017, http://www.who.int/hiv/en/. ↩
- “HIV and AIDS,” NHS Choices. 8 September 2014, accessed 9 May 2017, http://www.nhs.uk/Conditions/HIV/Pages/Introduction.aspx. ↩
- Ibid. ↩
- A Gouber et al, “Bayesian multi-parameter synthesis of HIV surveillance data in England and Wales, 2001. Technical Report,” J. Roy. Statist. Soc. A, 171 (2006): 541-580. ↩
- D De Angelis et al, “Estimation of HIV burden through Bayesian evidence synthesis,” Statistical Science 29, no 1 (2014): 9-17, https://projecteuclid.org/download/pdfview_1/euclid.ss/1399645723. ↩
- “HIV in the UK – Situation Report 2015: Incidence, prevalence and prevention,” Public Health England, November 2015, https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/477702/HIV_in_the_UK_2015_report.pdf. ↩
- A Presanis et al, “Conflicting evidence in a Bayesian synthesis of surveillance data to estimate human immunodeficiency virus prevalence,” J. Roy. Statist. Soc. A 171, (2008: 915-937. ↩
- “House of Lords Select Committee on HIV and AIDs in the United Kingdom,” House of Lords, 2011, http://www.parliament.uk/business/committees/committees-a-z/lords-select/hiv-select-committee/publications/. ↩
- KL Davison et al, “A re-evaluation of the risk of transfusion-transmitted HIV prevented by the exclusion of men who have sex with men from blood donation in England and Wales, 2005-2007,” Vox Sang 101, no. 4 (2011): 291-302, doi: 10.1111/j.1423-0410.2011.01491.x. ↩
- “SaBTO Advisory Committee on the Safety of Blood, Tissues and Organs,” Blood Donor Selection Steering Group, April 2011, https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/216109/dh_129909.pdf. ↩
- P Birrell et al, “HIV incidence in men who have sex with men in England and Wales 2001–10: a nationwide population study,” Lancet Infect Dis 13, no. 4 (2013): 313–318, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3610092/. ↩
- S Conti et al, “Modelling the HIV epidemic in the Netherlands: a Bayesian multi-parameter evidence synthesis approach,” The Ann. of App. Stats 5, no. 4 (2011): 2359-2384. ↩
- MG van Veen et al, “National estimates of HIV prevalence in the Netherlands: comparison and applicability of different estimation tools,” AIDS 25, no. 2 (2011): 229-37. ↩
- M Rosinska et al, “Bayesian evidence synthesis to estimate HIV prevalence in men who have sex with men in Poland at the end of 2009,” Epidemiol Infect (2015). ↩
- A Presanis et al, “The Severity of Pandemic H1N1 Influenza in the United States from April to July 2009: A Bayesian Analysis,” PLoS Medicine (2009), doi:10.1371/journal.pmed.1000207. ↩
- A Presanis et al, “A Changes in severity of pandemic (H1N1) influenza in England: a Bayesian evidence synthesis,” BMJ (2011): 343. doi: 10.1136/bmj.d5408. ↩
- MJ Sweeting et al, “Estimating Hepatitis C Prevalence by synthesising evidence from multiple data sources. Assessing data conflict and model fit,” Biostatistics 9, (2008): 715-734. ↩
- D De Angelis et al, “An evidence synthesis approach to estimating Hepatitis C Prevalence in England and Wales,” Statistical Methods in Medical Research 18 (2009): 381-395. ↩
- RJ Harris et al, “Hepatitis C prevalence in England remains low and varies by ethnicity: an updated evidence synthesis,” European Journal of Public Health 22, no. 2 (2012): 187–192. ↩
- T C Prevost et al, “Estimating the number of people with hepatitis C virus who have ever injected drugs and have yet to be diagnosed: an evidence synthesis approach for Scotland,” Addiction 110 (2015): 1287–1300.
H Harris et al, “Hepatitis C in the UK: 2016 report,” Public Health England, 2016, https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/541317/Hepatitis_C_in_the_UK_2016_report.pdf. ↩
- H Harris et al, “Hepatitis C in the UK: 2016 report,” Public Health England, 2016, https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/541317/Hepatitis_C_in_the_UK_2016_report.pdf. ↩