Professor Mark Strong


Population Health, School of Medicine and Population Health

Dean of the School of Medicine and Population Health

Professor of Public Health

Photograph of Mark Strong
Profile picture of Photograph of Mark Strong
+44 114 222 0812

Full contact details

Professor Mark Strong
Population Health, School of Medicine and Population Health
Barber House
S10 2HQ

PA: Francesca Baker


I am Dean of the School of Medicine and Population Health (SMPH) and a Professor of Public Health.

I also hold an honorary clinical consultant contract with the Office for Health Improvement and Disparities at the Department of Health and Social Care.

Research interests

I have three related research interests that fall under the general banner of Uncertainty Quantification:

  1. How do we properly account for all relevant uncertainties when we build a computer model of a physical, biological or social system?
  2. How do we (efficiently) compute value of information?
  3. How do we work out the value of a computer model? How much should we pay to make a simple model more complex? When do we stop increasing the complexity of a model?

Jeremy OakleyJim Chilcott and I have proposed an "internal" discrepancy-based method for managing model uncertainty. See this paper in JRSS Series C, and this paper in SIAM/ASA Journal of Uncertainty Quantification that develops the idea of the 'Expected Value of Model Improvement'. The method is discussed in more detail in my PhD thesis.

We have proposed an efficient method for computing partial EVPI. This method works for any number of parameters of interest and requires only the PSA sample. See this open access paper in Medical Decision Making. R functions to implement the method can be downloaded here.

Our online web calculator for partial EVPI, SAVI, is easy to use: Just upload your PSA sample and SAVI does the rest.

SAVI is also available as an R package from GitHub. This allows users to run the SAVI app on their own machine, and removes the need to transfer any data over the net. Installation instructions.

The partial EVPI method extends nicely to the computation of EVSI. See here for our open access paper on the efficient computation of EVSI.

Current and recent projects 

  • Calibrated Agent Simulations for Combined Analysis of Drinking Etiologies (CASCADE): A US National Institutes of Health funded project on alcohol consumption (2016-2021). PI - Robin Purshouse.
  • Systems Science in Public Health and Health Economic Research (SIPHER): A major UK Prevention Research Partnership funded project that will generate evidence for healthy public policy through a systems-science approach (2019-2024). PI - Petra Meier.

Show: Featured publications All publications

Journal articles

Conference proceedings papers


All publications

Journal articles


Conference proceedings papers



  • Kritsotakis E, Castilla-Fernandez G & Strong M (2017) Modelling recurrent event data: a comparison of the Cox proportional hazards model and three of its extensions to estimate the risk of recurrent healthcare-associated infections. Sixth Annual Survival Analysis for Junior Researchers. RIS download Bibtex download
  • Tosh J, Stevenson M, Akehurst R & Strong M (2014) A Framework for the Economic Evaluation of Sequential Therapies for Chronic Conditions (2014). ISPOR. RIS download Bibtex download
  • Barnes A, Black M, Baxter S, Furber A, Strong M, Beynon C, Dallat M, Jeffery C, Davies AR, Goyder E , Kritsotakis E et al Understanding public health systems: a participatory systematic review and systems infographic. RIS download Bibtex download
  • Black M, Barnes A, Creative NF, Baxter S, Jeffrey C, Dallat M, Beynon C, Furber A, Strong M, Davies A , Goyder E et al Early Years Policy in the UK - from the child’s perspective. RIS download Bibtex download



  • Relton C, Bridge G, Crowder M, Blake M, Strong M & Roberts G (2022) Fresh Street Report_Sheffield, Center for Open Science. RIS download Bibtex download
  • Vervaart M, Strong M, Claxton KP, Welton NJ, Wisløff T & Aas E (2021) An Efficient Method for Computing Expected Value of Sample Information for Survival Data from an Ongoing Trial, arXiv. RIS download Bibtex download
  • Mandrik O, Thomas C, Strong M & Whyte S (2021) Calibration and Validation of the Microsimulation Model in Cancer of the Bowel (MiMiC-Bowel), an Individual Patient Simulation Model for Investigation of the Cost-effectiveness of Personalised Screening and Surveillance Strategies.. View this article in WRRO RIS download Bibtex download
  • Black M, Barnes A, Strong M & Taylor-Robinson D (2020) Impact of Child Development at Primary School Entry on Adolescent Health – Protocol for a Participatory Systematic Review., Research Square Platform LLC. RIS download Bibtex download
  • Srivastava T, Strong M, Stevenson MD & Dodd PJ (2020) Improving Cycle Corrections in Discrete Time Markov Models: A Gaussian Quadrature Approach, Cold Spring Harbor Laboratory. RIS download Bibtex download
  • Kunst NR, Wilson E, Alarid-Escudero F, Baio G, Brennan A, Fairley M, Glynn D, Goldhaber-Fiebert JD, Jackson C, Jalal H , Menzies NA et al (2019) Computing the Expected Value of Sample Information Efficiently: Expertise and Skills Required for Four Model-Based Methods, arXiv. RIS download Bibtex download
  • Heath A, Kunst NR, Jackson C, Strong M, Alarid-Escudero F, Goldhaber-Fiebert JD, Baio G, Menzies NA & Jalal H (2019) Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies, arXiv. RIS download Bibtex download
Research group

PhD students

Teaching interests

I teach on the Master in Public Health (MPH) course, the MSc in Health Economics and Decision Modelling course, and the medical undergraduate MB ChB degree. I also support registrars on the Yorkshire and Humber public health training scheme who are taking the DFPH exam.

PhD opportunities

I welcome PhD applications at any time. You are welcome to email me to discuss an idea before making an application. I supervise students who are interested in the topics of Value of Information and Uncertainty Quantification in health economic decision making.