Professor George Streftaris


Maxwell Institute for Mathematical Sciences

Actuarial Mathematics and Statistics
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh EH14 4AS, UK

tel: (+44) 131 451 3679
fax: (+44) 131 451 3249


Professor of Statistics at Heriot-Watt University. Previous roles include associate professor and lecturer at HWU (2004-2019)

and post-doctoral positions at BioSS and HWU (2001-2004). I am a member of the Board of Examiners for the Institute and

Faculty of Actuaries in the UK, and external examiner for a number of institutes in the UK and overseas.

Professional memberships: Fellow of the Royal Statistical Society; member of the International Society for Bayesian Analysis;

member of the Greek Statistical Institute. Education: PhD in Statistics (Edinburgh U); MSc (with Distinction) in Statistics

and OR (Essex U); Ptychion (BSc) in Statistics and Actuarial Science (Piraeus U, Greece).



My research is focussed on Bayesian stochastic modelling, inference and assessment across the interface of statistics,

epidemiology and actuarial science. I have an interdisciplinary research record, with involvement in cross-sectional projects

and have been recipient of 5 research grants since 2012 (3 as PI), in areas including predictive modelling and statistical

machine learning in health and morbidity, and Bayesian modelling in critical illness and epidemiology. Work also involves

collaborations with researchers in life and biomedical sciences. I have supervised a number of PhD students and PDRAs to

completion and I currently supervise PhD candidates in topics including Bayesian and neural network modelling in

epidemiology, morbidity and mortality.

Research profile also on HWUs PURE pages



Funded research projects


v  Predictive Modelling for Medical Morbidity Risk Related to Insurance

Centers of Actuarial Excellence (CAE) Grant, SOA, PI, 2019-2023

v  Estimating the impact of the COVID-19 pandemic on breast cancer deaths - an application on breast cancer life insurance

SCOR Foundation of Science , CoI, 2022-2024

v  Modelling, Measurement and Management of Longevity and Morbidity Risk

ARC project, IFoA, Co-Lead, 2016-2022

v  The Data Lab with Aberdeen Asset Management, PI, 2017-2018

Machine learning to support big data for advanced multi-asset strategies

v  Actuarial Profession (IFoA) grant, PI, 2012-14

Incorporating model and parameter uncertainty in rate graduation and pricing for Critical Illness Insurance.

v  Scottish Government, Centre of Expertise for Waters, Co-I, 2013-14

Land management for increased ood resilience (with Built Environment, HWU).

v  Catalyst Grant: MRC/BBSRC/NERC/ESRC, Co-I, 2010-11

Episystem: Designing biological, social and economic environments to enhance resistance to zoonotic outbreaks (UK consortium).

v  Bridging the Gaps (EPSRC), PI, 2010

Bayesian Modelling of culvert blockage data (SBE, MACS at HWU)


Possible PhD topics (see here for more details)


Current and recent PRRAs

Statistical machine learning for financial multi-asset strategies




Current and previous PhD students


1)    Kaitlyn Louth, 1st year

2)    Farhad Waseel, 2nd year (HWU Malaysia)

3)    Wai Meng Kwok, 3rd year (HWU Malaysia)

4)    Niamh Graham, 3rd year (MIGSAA, with Edinburgh U)

5)    Alex Jose, 4th year

6)    Ying Zhang, (MIGSAA, with Edinburgh U), completed 2021

7)    Alexander Yiu, completed 2022

8)    Eirini Dimakakou, completed 2020

9)    Chunxiao Xie, completed 2021

10) Ian Duncan, completed 2020

11) David Thong, completed 2019

12) Adrakey Kwame, completed 2017

13) Jeff Pollock, completed 2015

14) Hani Syahida Zulkafli,completed 2017

15) Max Lau, completed 2015

16) George Mavros, completed 2014

17) Kokouvi Gamado, completed 2012

18) Yumn Yusoff, completed 2013

19) Erengul Ozkok, completed 2011

20) Charnchai Leuwattanachotinan, completed 2011




Refereed papers:


o   Arik, A., Cairns, A. J. G., Dodd, E., Macdonald, A. S., & STREFTARIS, G. (2024) The effect of the COVID-19 health

disruptions on breast cancer mortality for older women: A semi-Markov modelling approach.

To appear in Scandinavian Actuarial Journal.

o   Jose, A., Macdonald, A.S., Tzougas, G. and STREFTARIS, G. (2024) Interpretable zero-inflated neural network models

for predicting admission counts. Annals of Actuarial Science, Published online 2024:1-31. doi:10.1017/S1748499524000058

o   Waseel, F., STREFTARIS, G., Rudrusamy, B., and Dass, S.C. (2024) Assessing the dynamics and impact of COVID-19

vaccination on disease spread: A data-driven approach. To appear in Infectious Disease Modelling. Volume 9, Issue 2,


o   Kwok, W. M., STREFTARIS, G. and Dass, S. C., G. (2023). Laplace based Bayesian inference for ordinary differential

equation models using regularized artificial neural networks. Statistics & Computing 33, 124 (2023).

o   Arik, A., Cairns, A. J. G., Dodd, E., Macdonald, A. S., & STREFTARIS, G. (2023). Estimating the impact of the

COVID-19 pandemic on breast cancer deaths among older women. Living to 100 Research Symposium, Hong Kong.

o   Kwok, W. M., STREFTARIS, G., & Dass, S. C. (2023). A Novel Target Value Standardization Method Based on Cumulative

Distribution Functions for Training Artificial Neural Networks. In 13th IEEE Symposium on Computer Applications

& Industrial Electronics (pp. 250-255). IEEE.

o   Yiu, A., Kleinow, T., & STREFTARIS, G. (2023) Cause-of-death contributions to declining mortality improvements

and life expectancies using cause-specific scenarios. North American Actuarial Journal. DOI: 10.1080/10920277.2023.2230275

o   Jose, A., Macdonald, A.S., Tzougas, G and STREFTARIS, G. (2022) A combined neural network approach for the prediction

of admission rates related to respiratory diseases. Risks, 10(11), [217].

o   Arik, A., Dodd, E., Cairns, A., Shao, A., STREFTARIS, G. (2022) Uneven outcomes: findings on cancer mortality.

The Actuary,

o   Arik, A., Dodd, E., Cairns, A., STREFTARIS, G. (2021) Socioeconomic disparities in cancer incidence and mortality in England

and the impact of age-at-diagnosis on cancer mortality.

PLoS ONE. 16, 7, e0253854 10.1371/journal.pone.0253854

o   Dimakakou, E., Johnston, H.J., STREFTARIS, G., Cherrie, J.W. (2020) Is environmental and occupational particulate air pollution

exposure related to diabetes and dementia? A cross-sectional analysis in UK Biobank.

International Journal of Environmental Research and Public Health. 17, 24, 9581.10.3390/ijerph17249581

o   Thong, D., Streftaris, G. and Gibson, G.J. (2020) Latent likelihood ratio tests for assessing spatial kernels in epidemic models.

J. Math. Biol. 81, 853-873. DOI: 10.1007/s00285-020-01529-3

o   Zulkafli, H.S., Streftaris, G., Gibson. G.J. (2020). Stochastic latent residual approach for consistency model assessment.

Mathematics and Statistics, 8(5), 583 - 589. DOI: 10.13189/ms.2020.080513.

o   Dimakakou, E.; Johnston, H.J.; Streftaris, G.; Cherrie, J.W. (2020) Evaluation of the Suitability of an Existing Job-Exposure

Matrix for the Assessment of Exposure of UK Biobank Participants to Dust, Fumes, and Diesel Exhaust Particulates.

Int. J. Environ. Res. Public Health, 17, 4919. DOI: 10.3390/ijerph17144919

o   Arık A., Dodd E., Streftaris G. (2020) Cancer morbidity trends and regional differences in England - A Bayesian analysis.

PLoS ONE 15(5): e0232844.

o   Dimakakou, E., Johnston, H. J., Streftaris, G., & Cherrie, J. W. (2018). Exposure to Environmental and Occupational Particulate Air Pollution

as a Potential Contributor to Neurodegeneration and Diabetes: A Systematic Review of Epidemiological Research.

International Journal of Environmental Research and Public Health, 15(8), [1704]. DOI: 10.3390/ijerph15081704

o   Gibson, G.J., Streftaris, G. and Thong, D. (2018) Comparison and assessment of epidemic models.

Statistical Science, Vol. 33, No. 1, 19-33,

o   Stone, V., Streftaris, G. et al. (2017) The Essential Elements of a Risk Governance Framework for Current a nd Future Nanotechnologies,

Risk Analysis, DOI: 10.1111/risa.12954

o   Lau, S. Y., Gibson, G. J., Kwame, A. H., McClelland, A., Riley, S., Zelner, J., Streftaris, G., Funk, S., Metcalf, J., Dalziel, B.

& Grenfell, B. (2017) A mechanistic spatio-temporal framework for modelling individual-to-individual transmission in a heterogeneous

landscape - with an application to the 2014-2016 West Africa Ebola outbreak. PLoS Computational Biology 13(10): e1005798.

o   Adrakey, H.K., Streftaris, G., Gunniffe, N., Gottwald, T., Gilligan, C.A., and Gibson, G.J. (2017) Controlling spatio-temporal

epidemics using latent processes in a Bayesian framework. JRS Interface, DOI: 10.1098/rsif.2017.0386

o   Mavros, G., Cairns, A.J.G, Kleinow, T. and Streftaris, G. (2017) Stochastic Mortality Modelling: Key Drivers and Dependent Residuals.

North American Actuarial Journal, 21, 343-368,

o   Gamado, K.M., Streftaris, G. and Zachary, S. (2016) Estimation of under-reporting in epidemics using approximations.

Journal of Mathematical Biology, 74: 1683- 1707,

o   Dodd, E. and Streftaris, G. (2016) Prediction of settlement delay in critical illness insurance claims using GB2 distribution.

Journal of the Royal Statistical Society C, 66 (2), 273-294.

o   Zulkafli, H.S , STREFTARIS, G. , Gibson, G.J., and Zammitt, N.N. (2016) Bayesian modelling of the consistency of symptoms reported

during hypoglycaemia for individual patients. Malaysian Journal of Mathematical Sciences, 10(s), 27-39.

o   Lau, M.S.Y., Marion, G., Streftaris, G. and Gibson, G.J. (2015) A Systematic Bayesian Integration of Epidemiological and Genetic Data.

PLoS Computational Biology, 11(11): e1004633. doi:10.1371/journal.pcbi.1004633

o   Streftaris, G., Ozkok-Dodd, E., Waters, H.R. and Stott, A.D. (2015). Model and parameter uncertainty in critical illness insurance -

Abstract of the Edinburgh Discussion. British Actuarial Journal, 20, 387-403, DOI: 10.1017/S1357321715000112

o   Ozkok-Dodd, E., Streftaris, G., Waters, H.R. and Stott, A.D. (2015) The effect of model uncertainty on the pricing of critical illness insurance.

Annals of Actuarial Science, DOI: 10.1017/S1748499514000244

o   Lau, M.S.Y., Marion, G., Streftaris, G. and Gibson, G.J. (2014) New model diagnostics for spatio-temporal systems in epidemiology

and ecology. Journal of the Royal Society Interface, 11: 20131093, DOI 10.1098/rsif.2013.1093.

o   Yusoff Y. S., STREFTARIS, G. and Waters, H. R 2014) Modelling Sudden Deaths from Myocardial Infarction and Stroke. International

Journal of Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering, 8 (2), 84-87.

o   Gamado, K.M, Streftaris, G. and Zachary, S. (2013) Modelling under-reporting in epidemics. Journal of Mathematical Biology,

DOI 10.1007/s00285-013-0717-z.

o   Streftaris, G., Wallerstein, N.P., Gibson, G.J. and Arthur, S. (2013) Prediction of flood risk associated with blocked culverts using Bayesian

modelling. Journal of Hydraulic Engineering, DOI: 10.1061/(ASCE)HY.1943-7900.0000723.

o   Ozkok, E., Streftaris, G., Waters, H.R., and Wilkie, A.D. (2013) Modelling critical illness claim diagnosis rates II: results.

Scandinavian Actuarial Journal, DOI:10.1080/03461238.2012.728538.

o   Ozkok, E., Streftaris, G., Waters, H.R., and Wilkie, A.D. (2012) Modelling critical illness claim diagnosis rates I: Methodology.

Scandinavian Actuarial Journal, DOI:10.1080/03461238.2012.728537.

o   Streftaris G. and Gibson, G.J. (2012) Non-exponential tolerance to infection in epidemic systems - modelling, inference and assessment,

Biostatistics, 13, 580-593, doi:10.1093/biostatistics/kxs011.

o   Ozkok, E., Streftaris, G., Waters, H.R., and Wilkie, A.D. (2012) Bayesian modelling of the time delay between diagnosis and settlement

for Critical Illness Insurance using a Burr generalised-linear-type model. Insurance: Mathematics & Economics, 50, 266-279,


o   Zammitt, N.N., Streftaris, G., Gibson, G.J., Deary, I.J. and Frier, B.M. (2011) Modelling the consistency of symptoms reported during

hypoglycaemia: high variability in people with type 1 and type 2 diabetes. Diabetes Technology & Therapeutics, 13(5), 571-578.

o   Gibson, G.J., Streftaris, G. and Zachary, S. (2011) Generalised data augmentation and posterior inferences, Journal of Statistical Planning

and Inference, 141(1), 156-171, doi:10.1016/j.jspi.2010.05.025

o   Streftaris, G. and Worton, B.J. (2008) Efficient and accurate approximate Bayesian inference with an application to insurance data.
Computational Statistics & Data Analysis 52, 2604-2622, doi:10.1016/j.csda.2007.09.006

o   Streftaris, G. and Worton, B.J. (2007) Hierarchical and empirical Bayes estimators in the analysis of insurance claims. Proceedings of the

22nd international Workshop on Statistical Modelling, Barcelona, pp556-559.

o   Streftaris, G. and Gibson, G.J. (2004) Bayesian analysis of transmission dynamics of experimental epidemics. Proceedings of the 19th

international Workshop on Statistical Modelling, Florence, pp184-188.

o   Streftaris, G. and Gibson, G.J. (2004) Bayesian analysis of experimental epidemics of foot-and-mouth disease. Proc. R. Soc. Lond. B 271,

1111-1117, doi:10.1098/rspb.2004.2715

o   Streftaris, G. and Gibson, G.J. (2004) Bayesian inference for stochastic epidemics in closed populations. Statistical Modelling 4, 63-75,


o   Streftaris, G. and Gibson, G.J. (2002) Statistical inference for stochastic epidemic models. Proceedings of the 17th international

Workshop on Statistical Modelling, Chania, pp609-616. (Full paper in pdf form)


Under review/revision:


o   A. Arık, A. Cairns, E. Dodd, A. Macdonald, and G. Streftaris. The effect of the COVID-19 health disruptions on breast cancer mortality

for older women: A semi-Markov modelling approach. (under review).

o   Arik, A., Cairns, A.J.G, Dood, E, Macdonald, A.S, Shao, A. and Streftaris, G. Insurance pricing for breast cancer under different multiple

state models (under revision).



Research seminars


I have given a number of invited seminars at universities and conferences in the UK and internationally.

A detailed list can be found here.



George Streftaris

Last modified: February 2024