Imperial College London

Dr Nathan Green

Faculty of MedicineSchool of Public Health

Research Fellow



+44 (0)20 7594 Website




UG 1147 Praed StreetSt Mary's Campus





I am a Statistician and Mathematical Modeller Research Fellow in the Department of Infectious Disease Epidemiology. I am also involved with the Statistics, Modelling and Economics Department at Public Health England.

I have a number of years experience working on a wide range of projects across government and academia in defence and health.

I studied mathematics and statistics at the University of Newcastle-Upon-Tyne and obtained a PhD in applied probability from the University of Liverpool. After working for the Ministry of Defence for several years, applying novel Bayesian Inference ideas, I moved back into academia and the field of public health in 2010.

My general fields of interest include:

  • Operational research
  • Health economics
  • Survival analysis and multistate models
  • Epidemiology
  • Small area estimation

My current methodological interests include:

  • Care pathway analysis
  • Excess length of stay estimation
  • Cost-effectiveness
  • Multi-level modelling of spatio-temporal data, including aggregation of disparate sources
  • Discrete event simulation (DES)

 My current application areas include:

  • Tuberculosis (latent and active cases)
  • Healthcare-acquired infections
  • Sexually transmitted infections (principally Chlamydia)



Green N, Johnson AP, Henderson KL, et al., 2015, Quantifying the Burden of Hospital-Acquired Bloodstream Infection in Children in England by Estimating Excess Length of Hospital Stay and Mortality Using a Multistate Analysis of Linked, Routinely Collected Data, Journal of the Pediatric Infectious Diseases Society, Vol:4, ISSN:2048-7193, Pages:305-312

Green N, 2015, Statistics for People Who (Think They) Hate Statistics, Journal of the Royal Statistical Society Series A-statistics in Society, Vol:178, ISSN:0964-1998, Pages:784-784

Drobniewski F, Cooke M, Jordan J, et al., 2015, Systematic review, meta-analysis and economic modelling of molecular diagnostic tests for antibiotic resistance in tuberculosis, Health Technology Assessment, Vol:19, ISSN:1366-5278, Pages:1-+

van Kleef E, Green N, Goldenberg SD, et al., 2014, Excess length of stay and mortality due to Clostridium difficile infection: a multi-state modelling approach, Journal of Hospital Infection, Vol:88, ISSN:0195-6701, Pages:213-217


Lowndes CM, Sherrard-Smith E, Dangerfield C, et al., 2014, Point-of-care testing versus standard practice for chlamydia: a new approach to assessing the public health effect of rapid testing and treatment at local level, European Public Health Science Conference, ELSEVIER SCIENCE INC, Pages:47-47, ISSN:0140-6736

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