As part of the ARC Webinar Series 2021, this webinar will review the work of the UEA/Aviva research team over the last four years on a major research programme funded by the IFoA’s Actuarial Research Centre. The research concentrated on the longevity of people with major long term medical conditions such as diabetes, transient ischaemic attack, stroke and heart attack, and assessed the effects of key treatments such as statins, blood pressure drugs and hormone replacement therapy. Analyses were based on electronic primary health care records of 3.4M patients born before 1960, extracted from The Health Improvement (THIN) data-base. Professor Elena Kulinskaya and her team will describe the approaches used, lessons learned, and their main results, including development of their innovative MyLongevity app to calculate life expectancy
Presenters:
Prof. Elena Kulinskaya
Elena Kulinskaya is Professor in Statistics (Aviva Chair in Statistics) at the University of East Anglia in Norwich. Prof Kulinskaya is an academic statistician with strong research interests in meta-analysis and research synthesis, statistical methods for Big Data, and their applications in insurance, health and environmental sciences. She is the Principal Investigator on the IFoA-ARC funded research programme; Use of Big Health and Actuarial Data for Understanding Longevity and Morbidity Risks. She is also working on methodology for Big Data Analytics in the ESRC funded Business and Local Government Data Research Centre (BLG DRC).
Padma Chutoo
Padma Chutoo is a postgraduate researcher at the University of East Anglia working on the topic of survival prospects after an ischaemic stroke and a transient ischaemic attack in UK. The aim of the study is to assess the effects of these neurological medical conditions on the longevity and morbidity risk. My research interests are mortality modelling and survival analysis
Nurunnahar Akter
Mrs. Nurunnahar Akter is a final year postgraduate researcher at the University of East Anglia (UEA). She is working on the project Use of Big Health and Actuarial Data for Understanding Longevity and morbidity risks, funded by the Actuarial Research Centre of the Institute and Faculty of Actuaries (IFoA). Her area of research is hormone replacement therapy and its impact on mortality and morbidity. Before joining UEA, she worked as a research assistant on Clinical Data Analysis at the College of Engineering, Mathematics, and Physical Sciences of University of Exeter.
Mrs. Akter completed her B.Sc. in Mathematics in 2005, and M.Sc. in Pure Mathematics in 2007 from the University of Dhaka, Bangladesh with first class in all. After completing her Masters, she worked as a lecturer at the school of Computer Science and Engineering, Darul Ihsan University, and at the Department of Mathematics, Dhaka City College for more than seven years. In 2016, Mrs. Akter received her second Masters in Mathematical Medicine and Biology from the University of Nottingham, UK. Her research interest includes the areas in mathematical modelling, survival analysis, medical statistics, statistical modelling and actuarial analysis.
Njabulo Ncube
Njabulo Ncube is a Post-Graduate Research student at University of East Anglia. He has more than 13 years of work experience in social security. He joined the National Social Security Authority, Zimbabwe, in 2003 as an ICT Graduate Management Trainee and moved up the ranks to work as a Statistician in 2005. He then joined the University of East Anglia in 2017 as a Post-Graduate Research Student.
Njabulo Ncube received a BSc in Computer Science and Statistics from the University of Zimbabwe in 2002 and an MSc in Actuarial Science from the University of Lausanne, Switzerland, in 2013.
Ilyas Bakbergenuly
Ilyas Bakbergenuly is a postdoctoral researcher in statistics, based at the School of Computing Sciences at the University of East Anglia. His work is funded by ARC grant on Use of Big Health and Actuarial Data for understanding Longevity and Morbidity Risks. His research includes computational aspects of Big data handling, selection and analysis, as well as statistical modelling of longevity. Ilyas Bakbergenuly completed a BSc in Mathematics with Statistics and a PhD in Statistics at the University of East Anglia, United Kingdom.
Panellist:
Prof Nicholas Steel
Nick is Professor of Public Health at the University of East Anglia (UEA) and his research interests focus on improving outcomes for people with complex health problems managed in primary care. Current research projects include national surveys of older participants in the English Longitudinal Study of Ageing during the COVID-19 pandemic, using the Global Burden of Disease Study in England, and analysis of primary care databases (THIN and CPRD). He has developed a future learn open access online course to help GPs and people with multiple conditions set goals together, and advises UEA and Norfolk County Council about their response to COVID-19.
Mr Nigel Wright
Nigel Wright is an actuary working in the Life and Health Data Science team within Aviva and is an Honorary Senior Lecturer at the University of East Anglia (UEA). He has worked with UEA since 2010 and is currently involved with IFoA, ARC funded research programme: Use of Big Health and Actuarial Data for Understanding Longevity and Morbidity Risks.
Chair:
Erik Vynckier
Erik Vynckier is non-executive director of Foresters Friendly Society, chair of Research and Thought Leadership at the Institute and Faculty of Actuaries and senior adviser to derivatives and capital markets software vendors FiNCAD and Maxeler, following a career in investment banking, insurance, asset management and the petrochemical industry.
He co-founded EU initiatives on high performance computing and big data in finance and co-authored “High-Performance Computing in Finance” and “Tercentenary Essays on the Philosophy and Science of Leibniz”. Erik graduated as MBA at London Business School and as chemical engineer at Universiteit Gent.
Event organiser
Contact Niki Park for more information.
020 7632 2152
This webinar will take place from 12.30-14.00.