Modelling syndemics: hepatitis C virus (HCV) and drug related mortality among people who inject drugs
People who inject drugs have increased risk of hepatitis C virus (HCV) and drug related death (DRD). In the UK, 85% of HCV is transmitted through injecting, and DRD has increased 3-fold in 10 years. This PhD will develop mathematical models to determine the effect of interventions on HCV and DRD to assess which combination is most effective.
Infectious disease (ID) mathematical modelling is a growing research area. ID transmission models can help understand the progression of epidemics, including what the main drivers of infection are, and how a disease may spread in a population. Modelling can also project the likely future epidemic trajectory if everything stays the same or if interventions to reduce incidence of disease are implemented, thereby providing a means to guide policy makers on optimal intervention strategies.
Globally, around 71 million people are chronically infected with hepatitis C virus (HCV). HCV causes significant mortality; however new highly efficacious treatments have made HCV easily curable. In many settings HCV disproportionately affects high-risk populations including people who inject drugs (PWID). PWID are also at risk of drug-related death (DRD) with overdose being the leading cause of avoidable death among PWID. The World Health Organisation (WHO) have set HCV elimination targets for 2030, while in 2012 the Commission on Narcotic Drugs recommended national drug policies include effective measures to prevent and treat drug overdoses. However, in many settings the number of DRDs are still increasing; in Scotland (UK) the number doubled between 2007-2017, and in rural USA it increased 70% between 2005-2015.
Previous modelling to capture HCV epidemics and determine the number of PWID needing treatment to achieve the WHO elimination targets has not explicitly accounted for overdose related death, and potential interventions (e.g. increased opioid substitution treatment and monitoring, particularly during periods known to be higher risk, supervised drug consumption rooms and provision of naloxone (overdose-reversal drug) kits) to reduce this. Therefore, the aims of this PhD will be:
- Use mathematical and statistical ID modelling to develop site-specific models that examine HCV and fatal overdose syndemics.
- Use the models to understand trends in overdose death.
- Evaluate the effect of different strategies to decrease preventable DRD among PWID, including fatal overdose, and their impact on the HCV epidemic.
Through existing collaborations, Scotland, Bristol/South West, Kentucky and Georgia will be modelled, with the student travelling to these sites. Each model will account for differences in population dynamics (e.g. high-risk behaviours such as increased risk of overdose following incarceration) and will incorporate site-specific data on the HCV epidemic and overdose deaths. Outputs will be used to help understand trends in overdose death, the impact of strategies to decrease DRD, and the impact that these will have on the current HCV epidemic.
Prospective students will be highly numerate; the project will include training in modelling, epidemiological analysis and survival analysis. The PhD will result in high impact journal articles, and results being presented at national/international meetings and conferences
Requirements and training
The prospective PhD student will need to be highly numerate, although their current skills may be varied depending on their training and qualifications. Depending on their experience, the student may need to take courses/training in infectious disease modelling, epidemiology, statistics, Stata, R and survival analysis. Many of these courses are available through short courses offered within Population Health Sciences at the University of Bristol, and are free to students. Depending on their current expertise, the student may need to attend a longer course on infectious disease modelling. The student will also benefit from learning from other PhD students and post-doctoral researchers within the infectious disease group.
Environment – Bristol and Bath
The prospective PhD student will be based within Population Health Sciences (PHS) in Bristol Medical School at the University of Bristol – an internationally-leading institution in population health research, shown by the 2014 Research Excellence Framework results. Within the REF, 50% of our population health research was rated as world leading, with 86% world leading or internationally excellent. Furthermore, 100% of the PHS research environment was rated as world-leading. The student will also be linked to the Department of Mathematical Sciences at the University of Bath, through co-supervisor Jane White, where 88% of the research was rated world leading or internationally excellent.
The lead supervisor for this PhD project (Matthew Hickman) is Head of Population Health Sciences and co-director of the NIHR Health Protection Research Unit in Evaluation of Interventions which is based in PHS. The student will also have support and collaboration from the numerous PhD students, post-docs, lecturers and professors working on infectious disease modelling and benefit from attending weekly group meetings as well as courses on the internationally renowned short-course programme that is available within PHS, including on mathematical modelling of infectious diseases. Courses are free of charge to all research students in the school and are essential for improving research skills. Furthermore, there is a wide range of collaborative, multi-disciplinary research taking place in PHS with this wide of expertise making an excellent environment in which to conduct a PhD.
Currently there is little modelling on fatal overdose; therefore, modelling this in synergy with hepatitis C virus (HCV) modelling is novel and will help to advance the research area. The outputs of the project will be used to understand trends in overdose deaths and the impact that decreasing fatal overdose deaths will have on HCV transmission and epidemics among people who inject drugs.
The prospective student will be able to take advantage of the methodological expertise at Bath, attending seminars organised by the Centre for Mathematical Biology, as well as the applied policy expertise at Bristol. Alongside this, the GW4 alliance will mean the prospective student can benefit from accessing skills training from both Bristol and Bath universities.
Focus and collaborations
This proposed project will use the latest mathematical modelling techniques to produce results which are robust and able to guide policy regarding decreasing drug-related death. Epidemiological and statistical methods will be used alongside mathematical modelling to create a project of public health importance. Skills used in the PhD will include data analytics and analysis and interpretation of results, with students being able to take relevant courses to learn these. By developing their skills, the prospective student will finish the PhD with a well-honed skillset that they can use to model not only hepatitis C virus and overdose death, but with the knowledge on how to use these skills and apply them to other infectious diseases to continue with their future progression.
The PhD will foster new collaborations alongside strengthening partnerships and collaborations in Scotland, Kentucky and Georgia. We will use existing links to ensure that the results are able to influence health policy, including engagement with key groups working with people who inject drugs to ensure any interventions modelled are as realistic and accessible as possible. By presenting their research at conferences to a range of audiences we will ensure they are able to share results with non-specialists, thus maximising the policy influence of the work.
How to Apply:
Further information can be obtained at http://www.gw4biomed.ac.uk/available-projects-2/population-health-projects/
To apply, you will need to complete an application to the GW4 BioMed MRC DTP for an ‘offer of funding’. Please complete the online application form https://cardiff.onlinesurveys.ac.uk/gw4-biomed-mrc-dtp-student-2019 by 5pm, 23 November 2018. The Research Theme Panels will complete the shortlisting and inform applicants by 18 December 2018.
If you are shortlisted you will need to;
• contact your chosen supervisor(s) to discuss your application between 3 and 14 January 2019
• submit two references and a copy of your academic transcript(s) by 18 January 2019
• attend an interview in Cardiff on 22 or 23 January 2018
Further details will be included in the shortlisting letter.
- Population Health Sciences, University of Bristol
- Closing date
- November 23rd, 2018
- Posted on
- October 8th, 2018 10:08
- Last updated
- October 8th, 2018 10:08