Martin Gulliford is Professor of Public Health in the School of Population Health and Life Course Sciences at King's College London. He qualified in medicine from the University of Cambridge and University College Hospital, London and trained in public health and health services research at Guy’s and St Thomas’ Medical Schools London where he was a Wellcome Training Fellow in Health Services Research. He worked in Trinidad for some time, organising a programme of health services research and training.

Martin's research interests are in epidemiology as applied to public health and health services research. His current research focuses on the use of electronic health records to evaluate public health interventions. This includes public health trials with either cluster or individual level randomisation, as well as health economic modelling studies. The main areas of application are in obesity, chronic disease prevention, ageing and antimicrobial utilisation.

Research Publications: For a full list, see PubMed.

Research funding: Martin's research has received funding from: Medical Research Council; National Prevention Research Initiative; NIHR Health Technology Assessment Programme; NIHR Health Services and Delivery Programme; Dunhill Medical Trust; Guy's and St Thomas' Charity; and Wellcome Trust.

Books include: 

    Healthcare Public Health: Improving health services through population science. OUP 2020. Edited with Edmund Jessop.

    Oxford Textbook of Global Public Health, 6th edition, (2015) edited with Detels, Tan and Abdool Karim

    Oxford Textbook of Public Health, 5th edition, (2009), edited with Detels, Beaglehole and Lansang

    Access to Health Care (Routlege, 2003), edited with Myfanwy Morgan.

Teaching: Epidemiology and Biostatistics and Healthcare Public Health on the following programmes:

    King's MBBS

    King's campus-based Masters in Public Health

    King's online MSc in Public Health 

Epidemiology as applied to public health and health services research; design and analysis of studies with clustered data; large datasets and electronic patient records; obesity, chronic disease prevention, ageing and antimicrobial utilisation.