Our research uses large volumes of complex, heterogenous, multi-dimensional and often unstructured dataset from different sources with the aim of understanding patterns, trends, and associations of diseases to inform preventive action. We use traditional statistical methods alongside artificial intelligence algorithms to draw insights on real-world problems.
This is alongside extensive qualitative research, to provide insights and gain a deeper understanding of big data interpretation and its application in both clinical and social contexts.
We are an interdisciplinary team that includes health and social care workers, data scientists, epidemiologists, mathematicians, engineers, environmental scientists, sociologists, psychologists, health economists alongside patients and public members. The group is led by Dr Hajira Dambha-Miller. We also regularly have visiting fellows from other institutions and across the faculty, as well as students.
We are based in the Primary Care Research Centre, where we work across the departmental research themes, but we also apply our research knowledge and skills across a range of other topics. We run seminars and online meetings to discuss all things related to data science.
To contact our group, please email: datasci@soton.ac.uk.
Dr Hajira Dambha-Miller MRCGP,PhD,FHEA
Group Leader
Hajira is a GP and Clinical Lecturer with an interest in large-scale epidemiology studies that can inform preventive action. She works across a range of clinical topics but particularly around chronic disease. Hajira leads the cross-faculty Data Science Group at the University of Southampton. Her studies primarily use primary care electronic health records including CPRD, SAIL, Q-Research, ELSA, CHIA and international datasets in Canada and the USA. She has also curated a number of novel datasets linking health, social and environmental data. She currently leads a programme of work funded by the NIHR to examine clusters of disease in people with Multiple Long-Term Conditions using health and social care electronic health records.
Hajira currently chairs the NIHR AI-Multiple Long Term Condition Big Data PI group, she has previously established and chaired the COVID-19 Big Data National Group and is a current member of the international Monitoring Mortality Inequality Consortium. She is an honorary fellow at the MRC Epidemiology at the University of Cambridge. She has provided evidence to Government ministers on big data methods and their interpretation, and is also editor-in-chief at the British Journal of General Practice Open.
Dr Nick Francis
Clinical Professor of Primary Care
Professor Francis' research focuses on helping patients and healthcare professionals prevent and manage infections in order to improve outcomes and reduce antimicrobial resistance.
Professor Francis leads research that focuses on the management of respiratory, urinary and skin problems in a primary care setting, with a particular focus on the prevention, diagnosis and management of infections and antimicrobial stewardship. Key area of interest include: COPD, asthma, skin infections and acne.
He brings extensive experience and expertise in leading clinical research including randomised controlled trials, observational studies, developing complex interventions, and epidemiological studies using large routine healthcare datasets.
Dr Simon Fraser BM MSc DM FFPH MRCGP FHEA DRCOG DCH
Associate Professor
As a public health doctor building on his past experience as a GP, his research aims to understand and address the determinants, burden, inequalities and adverse outcomes associated with chronic disease. He has a particular interest in kidney disease.
Simon qualified in medicine from Southampton in 1992. After ten years as a full time Principal in General Practice in Southampton, he joined the Wessex Public Health training programme while continuing as a part time GP. He completed his doctoral degree in 2014 on the epidemiology of chronic kidney disease, with a particular interest in inequalities and health literacy.
Dr Nazrul Islam MBBS, MSc, MPH, PhD
Associate Professor of Epidemiology and Medical Statistics
Dr. Nazrul Islam, MBBS, MSc, MPH, PhD, is an Associate Professor of Epidemiology and Medical Statistics at the School of Primary Care, Population Sciences and Medical Education in the Faculty of Medicine. His research involves big data analysis (e.g., whole-population electronic medical records of primary and secondary healthcare data) using advanced epidemiological study design methodology such as emulated target trial, minimising bias and confounding in observational studies, examining intersectional inequalities in morbidity and mortality locally and globally.
Dr Glenn Simpson PhD, MA, BSc (Hons)
Senior Research Fellow
Glenn has considerable experience in qualitative research and a growing involvement in mixed methods studies. He has worked in a range of fields including public policy, public health, health and social care policy and governance. Research interests include: integrated care, multiple long term health conditions, homelessness and health, health inequalities (including wider determinants of health), the impact of devolution on health and social policy and health governance (including the spatial configuration and scaling of governance).
Glenn has skills in a range of qualitative research methods including structured/semi-structured interviewing (e.g. interviewing professionals, vulnerable and disabled people), narrative interviewing, focus group research, the Delphi method, survey research and ethnographic observation. He is experienced in conducting reflexive thematic analysis and currently is engaged in project co-ordination and management. Glenn is also the senior research fellow overseeing the NIHR AIM grant.
Dr Sharon Xiaowen Lin PhD, MSc
Research Fellow in Data Science
Dr Lin has had extensive experience in evidence-based interdisciplinary research with expertise in unpicking complex problems using quantitative modelling techniques. Areas she has worked in so far include health and social behaviour change, energy and climate change and finance and financial markets.
She has received various fundings including a fellowship from British Academy, NESTA, UKERC, DUIS, and was a guest research fellow at the UK Parliamentary Office of Science and Technology.
Dr Yvonne Nartey PhD, MSc, BSc
Research Fellow in Epidemiology and Data Science
Dr Nartey is an epidemiologist whose current program of research seeks to understand the burden of multiple long-term conditions and identify groups of people based on their health and social needs using traditional statistical tools and machine learning methods.
Her research expertise includes clinical epidemiology studies on cancer, patient experience and health services research using large population-level databases of routinely collected health information from primary and secondary care. She has expertise in using the National Cancer Registration Dataset, Clinical Practice Research Datalink, the National Cancer Patient Experience Survey, Hospital Episode Statistics, and other disease registry data.
She is currently working in collaboration with physicians and other healthcare professionals on a funded National Institute of Health Research (NIHR) project on using artificial intelligence to understand multiple long-term conditions.
Dr Nusrat Khan Priya, MBBS, MPH, MSc, FRPH
Research Fellow in Data Science and Epidemiology
Priya is a medical doctor and public health epidemiologist with 10 years of work experience in large scale epidemiological studies in low- and middle-income countries (LMICs) and the UK. She has expertise in evidence based quantitative research using electronic health records and also in randomized controlled trials. She has wide exposure in working with qualitative research design, implementation research, and gold standard systematic reviews. Her research areas focus on non-communicable diseases and characterizing multimorbidity in various population group with risk factors. She has worked in various field of public health research including infectious diseases (TB, malaria), eye health, maternal and child health, program-based health system development in LMICs. She has also worked with various international funding agencies (USAID, Global Funds) and international collaborative projects. Currently she is completing her PhD in Public Health and Epidemiology at University of Cambridge with a thesis focus on multimorbidity and determinants in South Asian population.
Dr Christos Chalitsios MSc, PhD
Data Scientist/Senior Epidemiology Fellow
Dr Christos Chalitsios is an epidemiologist and medical statistician interested in epidemiological studies using large routine healthcare datasets that can inform preventive action. Christos works across a range of fields of public health research, including respiratory, skin, and cardiovascular diseases. His studies primarily use primary and secondary care electronic health records, including CPRD and HES as well as other disease registry data such as UK Biobank, MINAP, and ALSPAC. Christos has also undertaken the statistical analysis of randomised controlled trials and the design and analysis of Mendelian randomisation studies.
Using primary care datasets, his current research seeks to understand the burden of multiple long-term conditions and identify groups of people based on their health and social needs using traditional statistical tools and machine learning methods.
Dr Elizabeth Lovegrove BSc, BMBS
Academic Clinical Fellow in General Practice
Dr Elizabeth Lovegrove is Academic Clinical Fellow in General Practice at the University of Southampton.
Elizabeth is Academic Clinical Fellow in General Practice with the University of Southampton School of Primary Care, Population Sciences and Medical Education and a GP trainee in Portsmouth.
Elizabeth completed a BSc in Women’s Health during her intercalated year from medical school which stimulated her interest in research and in particular in women’s health. She then went on to complete an Academic Foundation Year in East London, completing a project with the primary care research team focussing on prescribing safety in women of childbearing age in primary care.