Stefano Conti Senior Statistician
Organisation: NHS England and NHS Improvement
Stefano joined NHS England and NHS Improvement in October 2016 as a Senior Statistician.
Prior to joining the Improvement Analytics Unit Stefano was a statistician for Public Health England, while for some of that time also a visiting researcher at the MRC Biostatistics Unit. Stefano previously held post-graduate research statistician posts at the University of Sheffield and the University of York.
Stefano holds a PhD (from La Sapienza University, IT) and an MSc (from Carnegie Mellon University, USA), both in Statistics. His BSc, also from La Sapienza University, was in Methodological Statistics.
Interests and memberships
- Associate editor for the Medical-Decision Making journal
- Peer-reviewer for a variety of international, mostly statistics journals
- Member of the UK Evaluation Society
Clarke G. M., Conti S., Wolters A., Steventon A. (2019): Evaluating the Impact of Healthcare Interventions Using Routine Data. The BMJ Education; DOI: 10.1136/bmj.l2239. An introduction effectiveness evaluations of a health-care improvement programmes, with guidelines on their design, analysis, implementation and interpretation.
Farah M., Birrell P. J., Conti S., De Angelis D. (2014): Bayesian Emulation and Calibration of a Dynamic Epidemic Model for H1N1 Influenza. The Journal of the American Statistical Association, 109(508):1398-1411; DOI: 10.1080/01621459.2014.934453. On the development of a statistical modelling framework for a computer simulator of the 2009 A/H1N1 influenza epidemic in London.
Conti S., Presanis A. M., van Veen M. G., Xiridou M., Donoghoe M. C., Rinder Stengaard A., De Angelis D. (2011): Modeling of the HIV Infection Epidemic in The Netherlands: A Multi-Parameter Evidence Synthesis Approach. The Annals of Applied Statistics, 5(4):2359-2384; DOI: 10.1214/11-AOAS488. On the development of a statistical modelling framework for synthesising, assessing and reconciling separate sources of evidence on HIV prevalence in The Netherlands in 2007.
Conti S., Claxton K. P. (2009): Dimensions of Design Space: A Decision-Theoretic Approach to Optimal Research Design. Medical Decision Making, 29(6):643-660; DOI: 10.1177/0272989X09336142. Illustration of a Value of Information-based approach to the determination of the sample sizes of a ensemble of medical studies for cost-effectiveness analysis purposes, with an application to a NICE-sponsored HTA of antibiotic treatments for adult seasonal flu.