Huan Wang

+44 (0)1382 383198
Statistician / Epidemiologist

Biography

Dr Huan Wang is a statistician/epidemiologist in the Division of Population Health Sciences, at the School of Medicine, University of Dundee. He has been working closely with Professor Peter Donnan on many research projects since he joined Dundee Epidemiology and Biostatistics Unit (DEBU) in 2014. His current research is mainly in medical statistics and population health sciences.

A book named “Analysis for Time-to-Event Data under Censoring and Truncation”, written by Hongsheng Dai and Huan Wang, has been published in 2016 by Elsevier. This book provides an overview of recent developments in survival analysis under truncation, especially for bivariate survival analysis.

Prior to joining DEBU, he was working on a GlaxoSmithKline (GSK) funded research project with Professor John Dillon, in the Division of Cardiovascular and Diabetes Medicine, at the School of Medicine, University of Dundee.

Dr Huan Wang holds a PhD in mathematical sciences from University of Brighton (with Dr Hongsheng Dai), and a master in applied statistics from Lancaster University. He did his BSc in applied mathematics at Harbin Institute of Technology in China.

Research

Research interests:

· Nonparametric statistics

· Survival analysis

· Statistical modelling

· Epidemiology

· Public health research

Dr Huan Wang has also been involved in many research projects funded by different funding bodies.

· Respiratory effect of angiotensin-converting enzyme inhibitors in people with asthma: a pharmacoepidemiological analysis using linked UK primary care data. Tenovus Scotland Major Research Grant (Morales DR, Donnan PT, and Lipworth B). 2016 – 2017.

· Timing of contrast enhanced radiological procedures and risk of acute kidney injury in post-operative patients. Tenovus Scotland Major Research Grant (Bell S, Zealley I, and Donnan PT). 2016.

· Use and misuse of opioid prescribing across Scotland – rates. Quality, variations and explanations. Scottish Government Health Directorates Chief Scientist Office (Smith BH, Torrance N, Mansoor R, Wang H, Baldacchino A, Donnan PT, Colvin L, Gilbert S, Hales T, Macfarlane GJ, and Serpell M). 2013 - 2015. (The summary of this study can be found here: http://medicine.dundee.ac.uk/staff-member/dr-nicola-torrance)

· Prediction of hip, knee and cataract replacement across Scotland. Scottish Government. 2015.

· Impact of severe hypoglycaemia on emergency healthcare services. Novo Nordisk. 2014 - 2015.

· Descriptive database study to determine the prevalence and incidence of thrombocytopenia in patients with hepatitis C and their current management in Scotland. GlaxoSmithKline. 2013 - 2014.

Teaching

Dr Huan Wang, as a member of DEBU, provides statistical advice to researchers and students within the School of Medicine. He also contributes to teaching the course “Statistics for Health and Medical Research” (held annually by DEBU).

Publications

Book

Dai Hongsheng and Wang Huan. (2016). Analysis for Time-to-Event Data under Censoring and Truncation. Elsevier.

Journal Articles

Dai H., Restaino M. and Wang H. (2016). A class of non-parametric bivariate survival function estimators for randomly censored and truncated data. Journal of Nonparametric Statistics, 28(4): 736-751.

Tait J., Wang H., Miller M. Stephens B., Mclntyre P., Cleary S. and Dillon J. (2016). Multidisciplinary managed care networks – Life-saving interventions for hepatitis C patients. Journal of Viral Hepatitis, 24 (3): 207-215.

Wang H. et al. (2016). The prevalence and impact of thrombocytopenia, anaemia and leucopenia on sustained virological response in patients receiving hepatitis C therapy: evidence from a large real world cohort. European Journal of Gastroenterology & Hepatology, 28(4): 398-404.

Ragupathy K., Grandidge L., Strelley K., Wang H. and Tidy John. (2015). Early and late vulval cancer recurrences: Are they different? Journal of Obstetrics and Gynaecology, 36(4): 518-521.

Wang H., Dai H. and Fu B. (2013). Accelerated failure time models for censored survival data under referral bias. Biostatistics, 14(2): 313-326.