Professor George Streftaris

Heriot-Watt University

 

 

Research Grants

 

·        CAE SOA grant, PI, 2019-2022

Predictive Modelling for Medical Morbidity Risk Related to Insurance

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

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

·        IFoA grant, Co-I, 2016-2020

Modelling, Measurement and Management of Longevity and Morbidity Risk

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

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

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

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

·        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).

·        Bridging the Gaps (EPSRC), PI, 2010

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

 

 

Research supervision

 

I am currently interested in supervising PhD projects on the following topics:

·        Model diagnostics for infectious epidemics

Stochastic modelling of communicable disease outbreaks is challenging due to inter-dependence in the involved transmission dynamics and imperfect observation of infection-related events. Estimation in such models is now well established, but research on model assessment and comparison is still under progress. This project will build on recently developed tools for epidemic model diagnostics to investigate the use of Bayesian methodology related to latent residuals, in cases where the epidemic outbreak is: (a) under-reported, (b) at early stages of its course, and/or (c) under the impact of intervention measures.

Supervisor: Prof. G Streftaris

 

·        Predictive models in health and morbidity trends related to insurance

Over recent decades, medical interventions and advances have become important drivers of health and morbidity trends. In this project we will consider statistical predictive models for such trends, relating to particular major conditions such as heart disease and cancer. The principal aim will be to address the timely need to develop robust predictive models for rapidly changing morbidity risks and relevant impact on health-related insurance, such as long-term care, disability and critical illness insurance. Bayesian model diagnostics, assessment and selection will be considered for a range of models including machine learning-based approaches.

Supervisor: Prof. G Streftaris

 

Current and recent PRRAs

 

·      Dr. Yen Lok, 2017-2018

Statistical machine learning for financial multi-asset strategies

·      Dr. Arik Ayse, 2018-2020

 

Current and previous PhD students

 

·      Charnchai Leuwattanachotinan, completed 2011

·      Erengul Ozkok, completed 2011

·      Yumn Yusoff, completed 2013

·      Kokouvi Gamado, completed 2012

·      George Mavros, completed 2014

·      Max Lau, completed 2015

·      Hani Syahida Zulkafli,completed 2017

·      Jeff Pollock, completed 2015

·      Adrakey Kwame, completed 2017

·      David Thong, completed 2019

·      Ian Duncan, completed 2020

·      Chunxiao Xie, completed 2021

·      Alexander Yiu, writing-up

·      Eirini Dimakakou, completed 2020

·      Ying Zhang, 3rd year (MIGSAA, with Edinburgh U)

·      Alex Jose, 2nd year

·      Niamh Graham, 2nd year (MIGSAA, with Edinburgh U)

·      Wai Meng Kwok, 1st year

 

 

Publications

Refereed papers:

·        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

·        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

·        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

·        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.

·        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

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

PLoS ONE 15(5): e0232844. https://doi.org/10.1371/journal.pone.0232844

·        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

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

Statistical Science, Vol. 33, No. 1, 19–33, https://doi.org/10.1214/17-STS615

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

Risk Analysis, DOI: 10.1111/risa.12954

·        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.

https://doi.org/10.1371/journal.pcbi.1005798

·        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

·        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, https://doi.org/10.1080/10920277.2017.1286992

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

Journal of Mathematical Biology, 74: 1683- 1707, https://doi.org/10.1007/s00285-016-1064-7

·        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.

·        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.

·        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

·        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

·        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

·        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.

·        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.

·        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.

·        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.

·        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.

·        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.

·        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.

·        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,

doi:10.1016/j.insmatheco.2011.12.001

·        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.

·        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

·        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

·        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.

·        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.

·        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

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

doi:10.1191/1471082X04st065oa

·        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:

 

·        Yiu, A., Kleinow, T., Streftaris, G. Quantifying cause-of-death contributions to declining life expectancies using cause-specific mortality

scenarios (2020, in preparation)

·        Streftaris, G., Xie, C., Dodd, E. Bayesian modelling of critical illness insurance claim rates (2020, in preparation)

·        Thong, D., Jewell, C., Streftaris, G., Gibson, G.J. Model Assessment of Epidemic Models of the 2001 Foot-And-Mouth Disease Epidemic

using Infection Link Residuals (2020, in preparation).

 

 

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.

 

 

 

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