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Mr David Prieto

MSc PhD

Associate Professor

Room
Room 249

LSHTM
Keppel Street
London
WC1E 7HT
United Kingdom

Tel.
+44 (0) 20 7927 2378

Fax.
+44 (0) 20 7637 2853

I've been working for over 20 years as a biostatistician. I started my professional career at the University of Alcala de Henares in Spain, and I have also worked in two public hospitals in Spain and in the Spanish Agency for Evaluation of Health Technologies. I used to combine my academic work with freelance consultancy and teaching of biostatistics to health professionals.  Currently my work is split between the UK (LSHTM) and Spain, where I lead a group on applied medical statistics at the Catholic University of Murcia (UCAM).

Affiliations

Faculty of Epidemiology and Population Health
Department of Non-communicable Disease Epidemiology

Centres

Centre for Global Chronic Conditions
Statistical Methodology

Teaching

I used to co-ordinate the module on Bayesian Statistics in the Medical Statistics MSc, where I still teach. I also teach basic statistics in the Diploma in Pharmacoepidemiology and the Intensive course in Epidemiology and Medical Statistics. 

Research

For several years I have worked in the development and application of Bayesian Hierarchical Models to the analysis of large databases of pharmacovigilance where I have used the WHO database of adverse drug reactions. 

I have also worked in risk prediction modelling. I have developed a risk score for cardiovascular events (ASCORE) and another one for death after traumatic injuries (CRASH-2). I have done theoretical work on the design and analysis of clinical trials and I have applied this to the analysis of large clinical trials, such as CRASH-2 and WOMAN trials in the Clinical Trials Unit.

Most recently I am developing an interest in statistical and computational methods to use large multidimensional data sets ("big data") for prediction of events and for aethiological research. Among the models that we are considering are: penalised generalised lineal models (and a Bayesian approach to these), multivariate analysis, diferential network analysis and machine learning methods.  At the Farr Institute (UCL) I have worked with electronic health records (CALIBER) of millions of patients and  with large databases of genomic, metabolomic and proteomic data (the UCLEB consortium and the UK biobank).

Research Area
Clinical trials
Complex interventions
Pharmacovigilance
Risk
Statistical methods
Bayesian Analysis
Electronic health records
Mobile technologies
Implementation research
Discipline
Pharmacoepidemiology
Epidemiology
Statistics
Disease and Health Conditions
Cardiovascular disease
Injuries