Professor Duncan Lee

  • Professor of Statistics (Statistics)

telephone: 01413304047
email: Duncan.Lee@glasgow.ac.uk

Room 342, Mathematics and Statistics Building, Glasgow G12 8SQ

Import to contacts

ORCID iDhttps://orcid.org/0000-0002-6175-6800

Biography

I received a first class BSc in Mathematical Sciences from the University of Bath in 2003, and a PhD in statistics with applications in environmental epidemiology from the same university in 2007. Following a 6-month temporary lectureship and a 1-year research assistant position, both at the University of Bath, I became a lecturer in statistics at the University of Glasgow in September 2007. I have been at the University of Glasgow ever since, and became a professor in August 2018. 

Research interests

My research interests are in developing spatio-temporal statistical methods for use in epidemiology in a predominantly Bayesian setting, focusing on disease mapping, predicting air pollution concentrations, and investigating the effects of air pollution on human health.

My first research area is in disease mapping whose aim is to estimate the spatial pattern in disease risk over a city or country, as well as determining whether there has been any increase or reduction in risk over time. These spatio-temporal risk estimates allow public health officials to address key policy questions, such as: (i) where is disease risk highest and which areas are exhibiting an increasing risk of disease over time; (i) how big are the health inequalities in disease risk between rich and poor communities, and how are they changing over time; and (iii) what are the impacts of covariate factors on disease risk.

My second research area concerns air pollution, both how to predict it in space and time, and what impact it has on public health. The first of these requires a high-resolution spatio-temporal prediction model to be developed, which allows air pollution concentrations to be predicted at unmeasured locations. The second of these requires regression models to be built that allow for residual spatio-temporal autocorrelation, which allows both the short-term and long-term health effects to be estimated. 

 

Research groups

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007
Number of items: 85.

2024

Zhu, Q., Lee, D. and Stoner, O. (2024) A comparison of statistical and machine learning models for spatio-temporal prediction of ambient air pollutant concentrations in Scotland. Environmental and Ecological Statistics, (Accepted for Publication)

MacBride, C., Davies, V. and Lee, D. (2024) A spatial autoregressive random forest algorithm for small-area spatial prediction. Annals of Applied Statistics, (Accepted for Publication)

Enright, J. , Lee, D. , Meeks, K. , Sylvester, J. and Pettersson, W. (2024) The complexity of finding and enumerating optimal subgraphs to represent spatial correlation. Algorithmica, (doi: 10.1007/s00453-024-01256-x) (Early Online Publication)

Muegge, R. , Jack, E. , Dean, N. and Lee, D. (2024) COVID-19 vaccine fatigue in Scotland: how do the trends in attrition rates for the second and third doses differ by age, sex, and council area? Journal of the Royal Statistical Society: Series A (Statistics in Society), (doi: 10.1093/jrsssa/qnae036) (Early Online Publication)

Zou, Z., O'Donnell, R. , Miller, C. , Lee, D. and Wilkie, C. (2024) A computationally efficient spatio-temporal fusion model for reflectance data. In: Developments in Statistical Modelling, 38th International Workshop on Statistical Modelling (IWSM 2024), Durham, UK, 14-19 Jul 2024, (Accepted for Publication)

Lee, D. (2024) Computationally efficient localised spatial smoothing of disease rates using anisotropic basis functions and penalised regression fitting. Spatial Statistics, 59, 100796. (doi: 10.1016/j.spasta.2023.100796)

2023

Lee, D. (2023) Identifying boundaries in spatially continuous risk surfaces from spatially aggregated disease count data. Annals of Applied Statistics, 17(4), pp. 3153-3172. (doi: 10.1214/23-AOAS1755)

Foster, H. M.E. , Gill, J. M.R. , Mair, F. S. , Celis-Morales, C. A. , Jani, B. D. , Nicholl, B. I. , Lee, D. and O'Donnell, C. A. (2023) Social connection and mortality in UK Biobank: a prospective cohort analysis. BMC Medicine, 21, 384. (doi: 10.1186/s12916-023-03055-7) (PMID:37946218) (PMCID:PMC10637015)

Lee, D. , Walton, H., Evangelopoulos, D., Katsouyanni, K., Gowers, A. M., Shaddick, G. and Mitsakou, C. (2023) Health impact assessment for air pollution in the presence of regional variation in effect sizes: the implications of using different meta-analytic approaches. Environmental Pollution, 336, 122465. (doi: 10.1016/j.envpol.2023.122465) (PMID:37640226)

Lee, D. and Anderson, C. (2023) Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data. Biometrics, 79(3), pp. 2691-2704. (doi: 10.1111/biom.13739) (PMID:35972420)

McCartney, G. , Hoggett, R., Walsh, D. and Lee, D. (2023) How important is it to avoid indices of deprivation that include health variables in analyses of health inequalities? Public Health, 221, pp. 175-180. (doi: 10.1016/j.puhe.2023.06.028) (PMID:37473649)

McCartney, G. , Hoggett, R., Walsh, D. and Lee, D. (2023) How well do area-based deprivation indices identify income- and employment-deprived individuals across Great Britain today? Public Health, 217, pp. 22-25. (doi: 10.1016/j.puhe.2023.01.020) (PMID:36841035)

Muegge, R. , Dean, N. , Jack, E. and Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, 100559. (doi: 10.1016/j.sste.2022.100559) (PMCID:PMC9719849)

2022

Olsen, J. R. et al. (2022) Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: a cross-sectional study using GPS from 122 individuals in three European cities. SSM - Population Health, 19, 101172. (doi: 10.1016/j.ssmph.2022.101172) (PMID:35865800) (PMCID:PMC9294330)

Lee, D. , Robertson, C., McRae, C. and Baker, J. (2022) Quantifying the impact of air pollution on Covid-19 hospitalisation and death rates in Scotland. Spatial and Spatio-Temporal Epidemiology, 42, 100523. (doi: 10.1016/j.sste.2022.100523) (PMID:PMC917620)

Lee, D. , Robertson, C. and Marques, D. (2022) Quantifying the small-area spatio-temporal dynamics of the Covid-19 pandemic in Scotland during a period with limited testing capacity. Spatial Statistics, 49, 100508. (doi: 10.1016/j.spasta.2021.100508) (PMID:33868908) (PMCID:PMC8035810)

Yin, X., Napier, G. , Anderson, C. and Lee, D. (2022) Spatio-temporal disease risk estimation using clustering-based adjacency modelling. Statistical Methods in Medical Research, 31(6), pp. 1184-1203. (doi: 10.1177/09622802221084131) (PMID:35286183) (PMCID:PMC9245163)

Gerogiannis, G., Tranmer, M. , Lee, D. and Valente, T. (2022) A Bayesian spatio-network model for multiple adolescent adverse health behaviours. Journal of the Royal Statistical Society: Series C (Applied Statistics), 71(2), pp. 271-287. (doi: 10.1111/rssc.12531)

2021

Lee, D. , Meeks, K. and Pettersson, W. (2021) Improved inference for areal unit count data using graph-based optimisation. Statistics and Computing, 31(4), 51. (doi: 10.1007/s11222-021-10025-7)

Enright, J. , Lee, D. , Meeks, K. , Pettersson, W. and Sylvester, J. (2021) The complexity of finding optimal subgraphs to represent spatial correlation. In: Du, D.-Z., Du, D., Wu, C. and Xu, D. (eds.) Combinatorial Optimization and Applications. Series: Lecture Notes in Computer Science (13135). Springer, pp. 152-166. ISBN 9783030926809 (doi: 10.1007/978-3-030-92681-6_13)

2020

Lee, D. , Robertson, C., Ramsay, C. and Pyper, K. (2020) Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution. Environmetrics, 31(8), e2643. (doi: 10.1002/env.2643)

Lee, D. (2020) A tutorial on spatio-temporal disease risk modelling in R using Markov chain Monte Carlo simulation and the CARBayesST package. Spatial and Spatio-Temporal Epidemiology, 34, 100353. (doi: 10.1016/j.sste.2020.100353)

Hanlon, P. et al. (2020) Assessing risks of polypharmacy involving medications with anticholinergic properties. Annals of Family Medicine, 18(2), pp. 148-155. (doi: 10.1370/afm.2501) (PMID:32152019) (PMCID:PMC7062487)

Hanlon, P. , McCallum, M. , Jani, B. D. , McQueenie, R., Lee, D. and Mair, F. S. (2020) Association between childhood maltreatment and the prevalence and complexity of multimorbidity: a cross-sectional analysis of 157,357 UK Biobank participants. Journal of Comorbidity, 10, pp. 1-12. (doi: 10.1177/2235042X10944344)

2019

Napier, G. , Lee, D. , Robertson, C. and Lawson, A. (2019) A Bayesian space–time model for clustering areal units based on their disease trends. Biostatistics, 20(4), pp. 681-697. (doi: 10.1093/biostatistics/kxy024) (PMID:29917057) (PMCID:PMC6797054)

Jack, E. , Lee, D. and Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(3), pp. 1061-1080. (doi: 10.1111/rssa.12447) (PMID:31217673) (PMCID:PMC6563432)

Lee, D. , Roertson, C., Ramsay, C., Gillespie, C. and Napier, G. (2019) Estimating the health impact of air pollution in Scotland, and the resulting benefits of reducing concentrations in city centres. Spatial and Spatio-Temporal Epidemiology, 29, pp. 85-96. (doi: 10.1016/j.sste.2019.02.003)

Jani, B. D. , Hanlon, P. , Nicholl, B. I. , McQueenie, R., Gallacher, K. I. , Lee, D. and Mair, F. S. (2019) Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank Cohort. BMC Medicine, 17, 74. (doi: 10.1186/s12916-019-1305-x) (PMID:30967141) (PMCID:PMC6456941)

2018

Lee, D. (2018) A locally adaptive process-convolution model for estimating the health impact of air pollution. Annals of Applied Statistics, 12(4), pp. 2540-2558. (doi: 10.1214/18-AOAS1167)

Jani, B. D. , Nicholl, B. I. , McQueenie, R., Connelly, D. T., Hanlon, P. , Gallacher, K. I. , Lee, D. and Mair, F. S. (2018) Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort. Europace, 20, f329-f336. (doi: 10.1093/europace/eux322) (PMID:29112751) (PMCID:PMC6277149)

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

Cullen, B. , Newby, D., Lee, D. , Lyall, D. M. , Nevado-Holgado, A. J., Evans, J. J. , Pell, J. P. , Lovestone, S. and Cavanagh, J. (2018) Cross-sectional and longitudinal analyses of outdoor air pollution exposure and cognitive function in UK Biobank. Scientific Reports, 8, 12089. (doi: 10.1038/s41598-018-30568-6) (PMID:30108252) (PMCID:PMC6092329)

Hanlon, P. , Nicholl, B. I. , Jani, B. D. , Lee, D. , McQueenie, R. and Mair, F. S. (2018) Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493,737 UK Biobank participants. Lancet Public Health, 3(7), e323-e332. (doi: 10.1016/S2468-2667(18)30091-4) (PMID:29908859) (PMCID:PMC6028743)

Lee, D. , Rushworth, A. and Napier, G. (2018) Spatio-temporal areal unit modelling in R with conditional autoregressive priors using the CARBayesST package. Journal of Statistical Software, 84(9), (doi: 10.18637/jss.v084.i09)

Huang, G., Lee, D. and Scott, E. M. (2018) Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty. Statistics in Medicine, 37(7), pp. 1134-1148. (doi: 10.1002/sim.7570)

Gallacher, K. I. , McQueenie, R., Nicholl, B. , Jani, B. D. , Lee, D. and Mair, F. S. (2018) Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants. Journal of Comorbidity, 8(1), pp. 1-8. (doi: 10.15256/joc.2018.8.129)

Hanlon, P. , Nicholl, B. I. , Jani, B. D. , McQueenie, R., Lee, D. , Gallacher, K. I. and Mair, F. S. (2018) Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study. BMJ Open, 8(1), e018404. (doi: 10.1136/bmjopen-2017-018404) (PMID:29332840) (PMCID:PMC5781016)

2017

Neslihanoglu, S., Sogiakas, V., McColl, J. and Lee, D. (2017) Nonlinearities in the CAPM: evidence from developed and emerging markets. Journal of Forecasting, 36(8), pp. 867-897. (doi: 10.1002/for.2389)

Lee, D. , Mukhopadhyay, S., Rushworth, A. and Sahu, S. K. (2017) A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health. Biostatistics, 18(2), pp. 370-385. (doi: 10.1093/biostatistics/kxw048) (PMID:28025181)

Pannullo, F., Lee, D. , Neal, L., Dalvi, M., Agnew, P., O'Connor, F. M., Mukhopadhyay, S., Sahu, S. and Sarran, C. (2017) Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England. Environmental Health, 16, 29. (doi: 10.1186/s12940-017-0237-1) (PMID:28347336) (PMCID:PMC5368918)

Anderson, C. , Lee, D. and Dean, N. (2017) Spatial clustering of average risks and risk trends in Bayesian disease mapping. Biometrical Journal, 59(1), pp. 41-56. (doi: 10.1002/bimj.201600018) (PMID:27492753)

Rushworth, A., Lee, D. and Sarran, C. (2017) An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk. Journal of the Royal Statistical Society: Series C (Applied Statistics), 66(1), pp. 141-157. (doi: 10.1111/rssc.12155)

Lawson, A. and Lee, D. (2017) Bayesian disease mapping for public health. In: Srinivasa Rao, A. S.R., Pyne, S. and Rao, C.R. (eds.) Handbook of Statistics. Elsevier, pp. 443-481. ISBN 9780444369684 (doi: 10.1016/bs.host.2017.05.001)

2016

Lee, D. and Lawson, A. (2016) Quantifying the spatial inequality and temporal trends in maternal smoking rates in Glasgow. Annals of Applied Statistics, 10(3), pp. 1427-1446. (doi: 10.1214/16-AOAS941) (PMID:28580047) (PMCID:PMC5449583)

Lawson, A. B., Lee, D. and MacNab, Y. (2016) Editorial. Statistical Methods in Medical Research, 25(4), p. 1079. (doi: 10.1177/0962280216660410) (PMID:27566766)

Napier, G. , Lee, D. , Robertson, C., Lawson, A. and Pollock, K. G. (2016) A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland. Statistical Methods in Medical Research, 25(4), pp. 1185-1200. (doi: 10.1177/0962280216660420) (PMID:27566772)

Pannullo, F., Lee, D. , Waclawski, E. and Leyland, A. H. (2016) How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging. Spatial and Spatio-Temporal Epidemiology, 18, pp. 53-62. (doi: 10.1016/j.sste.2016.04.001) (PMID:27494960) (PMCID:PMC4985538)

Anderson, C., Lee, D. and Dean, N. (2016) Bayesian cluster detection via adjacency modelling. Spatial and Spatio-Temporal Epidemiology, 16, pp. 11-20. (doi: 10.1016/j.sste.2015.11.005) (PMID:26919751)

Kavanagh, L., Lee, D. and Pryce, G. (2016) Is poverty decentralizing? Quantifying uncertainty in the decentralization of urban poverty. Annals of the American Association of Geographers, 106(6), pp. 1286-1298. (doi: 10.1080/24694452.2016.1213156)

Lee, D. and Sahu, S. (2016) Estimating the health impact of air pollution fields. In: Lawson, A. B., Banerjee, S., Haining, R. P. and Ugarte, M. D. (eds.) Handbook of Spatial Epidemiology. Series: Chapman & Hall/CRC handbooks of modern statistical methods. CRC: Boca Raton, FL, pp. 271-288. ISBN 9781482253016

2015

Lee, D. and Sarran, C. (2015) Controlling for unmeasured confounding and spatial misalignment in long-term air pollution and health studies. Environmetrics, 26(7), pp. 477-487. (doi: 10.1002/env.2348)

Huang, G., Lee, D. and Scott, M. (2015) An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: a case study of nitrogen dioxide concentrations in Scotland. Spatial and Spatio-Temporal Epidemiology, 14-15, pp. 63-74. (doi: 10.1016/j.sste.2015.09.002) (PMID:26530824)

Pannullo, F., Lee, D. , Waclawski, E. and Leyland, A. H. (2015) Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland. Atmospheric Environment, 118, pp. 227-235. (doi: 10.1016/j.atmosenv.2015.08.009) (PMID:26435684) (PMCID:PMC4567077)

Lee, D. , Minton, J. and Pryce, G. (2015) Bayesian inference for the dissimilarity index in the presence of spatial autocorrelation. Spatial Statistics, 11, pp. 81-95. (doi: 10.1016/j.spasta.2014.12.001)

2014

Lee, D. , Minton, J. and Pryce, G. (2014) Inference for segregation indices in the presence of spatial autocorrelation. In: Royal Statistical Society Annual Conference 2014, Sheffield, 2-4 Sept 2014,

Livingston, M. and Lee, D. (2014) "The Glasgow effect?"– the result of the geographical patterning of deprived areas? Health and Place, 29, pp. 1-9. (doi: 10.1016/j.healthplace.2014.05.002)

Anderson, C., Lee, D. and Dean, N. (2014) Identifying clusters in Bayesian disease mapping. Biostatistics, 15(3), pp. 457-469. (doi: 10.1093/biostatistics/kxu005) (PMID:24622038)

Rushworth, A., Lee, D. and Mitchell, R. (2014) A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London. Spatial and Spatio-Temporal Epidemiology, 10, pp. 29-38. (doi: 10.1016/j.sste.2014.05.001)

Eze, J.I., Scott, E.M. , Pollock, K.G., Stidson, R., Miller, C.A. and Lee, D. (2014) The association of weather and bathing water quality on the incidence of gastrointestinal illness in the west of Scotland. Epidemiology and Infection, 142(6), pp. 1289-1299. (doi: 10.1017/S0950268813002148) (PMID:24007797)

Lee, D. , Rushworth, A. and Sahu, S. K. (2014) A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution. Biometrics, 70(2), pp. 419-429. (doi: 10.1111/biom.12156) (PMID:24571082) (PMCID:PMC4282098)

Powell, H. and Lee, D. (2014) Modelling spatial variability in concentrations of single pollutants and composite air quality indicators in health effects studies. Journal of the Royal Statistical Society: Series A (Statistics in Society), 177(3), pp. 607-623. (doi: 10.1111/rssa.12034)

Miller, C. , Magdalina, A.-M., Willows, R., Bowman, A. , Scott, E. , Lee, D. , Burgess, C., Pope, L., Pannullo, F. and Haggarty, R. (2014) Spatiotemporal statistical modelling of long-term change in river nutrient concentrations in England & Wales. Science of the Total Environment, 466-7, pp. 914-923. (doi: 10.1016/j.scitotenv.2013.07.113) (PMID:23988742)

Lee, D. and Mitchell, R. (2014) Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies. Statistical Methods in Medical Research, 23(6), pp. 488-506. (doi: 10.1177/0962280214527384)

Mitchell, R. and Lee, D. (2014) Is there really a "wrong side of the tracks" in urban areas and does it matter for spatial analysis? Annals of the Association of American Geographers, 104(3), pp. 432-443. (doi: 10.1080/00045608.2014.892321)

2013

Lee, D. (2013) CARBayes: an R package for Bayesian spatial modeling with conditional autoregressive priors. Journal of Statistical Software, 55(13), pp. 1-24.

Lee, D. and Mitchell, R. (2013) Locally adaptive spatial smoothing using conditional auto-regressive models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 62(4), pp. 593-608. (doi: 10.1111/rssc.12009)

Shaddick, G., Lee, D. and Wakefield, J. (2013) Ecological bias in studies of the short-term effects of air pollution on health. International Journal of Applied Earth Observation and Geoinformation, 22, pp. 65-74. (doi: 10.1016/j.jag.2012.03.011)

2012

Powell, H., Lee, D. and Bowman, A. (2012) Estimating constrained concentration-response functions between air pollution and health. Environmetrics, 23(3), pp. 228-237. (doi: 10.1002/env.1150)

Lee, D. (2012) Using spline models to estimate the varying health risks from air pollution across Scotland. Statistics in Medicine, 31(27), pp. 3366-3378. (doi: 10.1002/sim.5420)

Lee, D. and Mitchell, R. (2012) Boundary detection in disease mapping studies. Biostatistics, 13(3), pp. 415-426. (doi: 10.1093/biostatistics/kxr036)

Lee, D. and Mitchell, R. (2012) Localised spatial smoothing in Bayesian disease mapping. In: Royal Statistical Society (RSS) annual international conference, Telford, UK, 03 Sep 2012,

Willocks, L., Bhaskar, A., Ramsay, C., Lee, D. , Brewster, D., Fischbacher, C., Chalmers, J., Morris, G. and Scott, E.M. (2012) Cardiovascular disease and air pollution in Scotland: no association or insufficient data and study design? BMC Public Health, 12, p. 227. (doi: 10.1186/1471-2458-12-227)

2011

Lee, D. , Ferguson, C. and Scott, E.M. (2011) Constructing representative air quality indicators with measures of uncertainty. Journal of the Royal Statistical Society: Series A (Statistics in Society), 174(1), pp. 109-126. (doi: 10.1111/j.1467-985X.2010.00658.x)

Lee, D. (2011) A comparison of conditional autoregressive models used in Bayesian disease mapping. Spatial and Spatio-Temporal Epidemiology, 2(2), pp. 79-89. (doi: 10.1016/j.sste.2011.03.001)

2010

Lee, D. and Shaddick, G. (2010) Spatial modeling of air pollution in studies of its short-term health effects. Biometrics, 66(4), pp. 1238-1246. (doi: 10.1111/j.1541-0420.2009.01376.x)

Salway, R., Lee, D. , Shaddick, G. and Walker, S. (2010) Bayesian latent variable modelling in studies of air pollution and health. Statistics in Medicine, 29(26), pp. 2732-2742. (doi: 10.1002/sim.4039)

Lee, D. and Neocleous, T. (2010) Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(5), pp. 905-920. (doi: 10.1111/j.1467-9876.2010.00725.x)

Lee, D. , Orr, A. and Pryce, G. (2010) Risk pricing on residential mortgages in the UK. In: CCHPR 20th Anniversary Conference: Housing – the next 20 years, Cambridge, 15-16 September 2010, (Unpublished)

Anderson, C., Lee, D. , Pryce, G. and Taal, M. (2010) Factors affecting environmental attitudes and volunteering in England and Wales. Working Paper, (Unpublished)

Magdalina, A., Ferguson, C. , Bowman, A. , Willows, R., Johnson, D., Burgess, C., Pope, L., Scott, E.M. and Lee, D. (2010) Spatiotemporal modelling of nitrate and phosphorus in river catchments for England and Wales. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010,

Scott, E. M. , Bowman, A. , Ferguson, C., Lee, D., O’Donnell, D., Villoria, M. F. and Gemmell, J. C. (2010) A Statistical Framework for an Evidence Base to Support Environmental Regulation and Policy. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010, pp. 25-32.

2009

Lee, D. , Ferguson, C. and Mitchell, R. (2009) Air pollution and health in Scotland: a multicity study. Biostatistics, 10(3), pp. 409-423. (doi: 10.1093/biostatistics/kxp010) (PMID:19377033)

2008

Lee, D. and Shaddick, G. (2008) Modelling the effects of air pollution on health using Bayesian dynamic generalised linear models. Environmetrics, 19(8), pp. 785-804. (doi: 10.1002/env.894)

Shaddick, G., Lee, D. , Zidek, J. and Salway, R. (2008) Estimating exposure response functions using ambient pollution concentrations. Annals of Applied Statistics, 2(4), pp. 1249-1270. (doi: 10.1214/08-AOAS177)

2007

Lee, D. and Shaddick, G. (2007) Time-varying coefficient models for the analysis of air pollution and health outcome data. Biometrics, 63(4), pp. 1253-1261. (doi: 10.1111/j.1541-0420.2007.00776.x)

This list was generated on Fri Dec 20 12:00:45 2024 GMT.
Jump to: Articles | Book Sections | Conference Proceedings
Number of items: 85.

Articles

Zhu, Q., Lee, D. and Stoner, O. (2024) A comparison of statistical and machine learning models for spatio-temporal prediction of ambient air pollutant concentrations in Scotland. Environmental and Ecological Statistics, (Accepted for Publication)

MacBride, C., Davies, V. and Lee, D. (2024) A spatial autoregressive random forest algorithm for small-area spatial prediction. Annals of Applied Statistics, (Accepted for Publication)

Enright, J. , Lee, D. , Meeks, K. , Sylvester, J. and Pettersson, W. (2024) The complexity of finding and enumerating optimal subgraphs to represent spatial correlation. Algorithmica, (doi: 10.1007/s00453-024-01256-x) (Early Online Publication)

Muegge, R. , Jack, E. , Dean, N. and Lee, D. (2024) COVID-19 vaccine fatigue in Scotland: how do the trends in attrition rates for the second and third doses differ by age, sex, and council area? Journal of the Royal Statistical Society: Series A (Statistics in Society), (doi: 10.1093/jrsssa/qnae036) (Early Online Publication)

Lee, D. (2024) Computationally efficient localised spatial smoothing of disease rates using anisotropic basis functions and penalised regression fitting. Spatial Statistics, 59, 100796. (doi: 10.1016/j.spasta.2023.100796)

Lee, D. (2023) Identifying boundaries in spatially continuous risk surfaces from spatially aggregated disease count data. Annals of Applied Statistics, 17(4), pp. 3153-3172. (doi: 10.1214/23-AOAS1755)

Foster, H. M.E. , Gill, J. M.R. , Mair, F. S. , Celis-Morales, C. A. , Jani, B. D. , Nicholl, B. I. , Lee, D. and O'Donnell, C. A. (2023) Social connection and mortality in UK Biobank: a prospective cohort analysis. BMC Medicine, 21, 384. (doi: 10.1186/s12916-023-03055-7) (PMID:37946218) (PMCID:PMC10637015)

Lee, D. , Walton, H., Evangelopoulos, D., Katsouyanni, K., Gowers, A. M., Shaddick, G. and Mitsakou, C. (2023) Health impact assessment for air pollution in the presence of regional variation in effect sizes: the implications of using different meta-analytic approaches. Environmental Pollution, 336, 122465. (doi: 10.1016/j.envpol.2023.122465) (PMID:37640226)

Lee, D. and Anderson, C. (2023) Delivering spatially comparable inference on the risks of multiple severities of respiratory disease from spatially misaligned disease count data. Biometrics, 79(3), pp. 2691-2704. (doi: 10.1111/biom.13739) (PMID:35972420)

McCartney, G. , Hoggett, R., Walsh, D. and Lee, D. (2023) How important is it to avoid indices of deprivation that include health variables in analyses of health inequalities? Public Health, 221, pp. 175-180. (doi: 10.1016/j.puhe.2023.06.028) (PMID:37473649)

McCartney, G. , Hoggett, R., Walsh, D. and Lee, D. (2023) How well do area-based deprivation indices identify income- and employment-deprived individuals across Great Britain today? Public Health, 217, pp. 22-25. (doi: 10.1016/j.puhe.2023.01.020) (PMID:36841035)

Muegge, R. , Dean, N. , Jack, E. and Lee, D. (2023) National lockdowns in England: the same restrictions for all, but do the impacts on COVID-19 mortality risks vary geographically? Spatial and Spatio-Temporal Epidemiology, 44, 100559. (doi: 10.1016/j.sste.2022.100559) (PMCID:PMC9719849)

Olsen, J. R. et al. (2022) Day-to-day intrapersonal variability in mobility patterns and association with perceived stress: a cross-sectional study using GPS from 122 individuals in three European cities. SSM - Population Health, 19, 101172. (doi: 10.1016/j.ssmph.2022.101172) (PMID:35865800) (PMCID:PMC9294330)

Lee, D. , Robertson, C., McRae, C. and Baker, J. (2022) Quantifying the impact of air pollution on Covid-19 hospitalisation and death rates in Scotland. Spatial and Spatio-Temporal Epidemiology, 42, 100523. (doi: 10.1016/j.sste.2022.100523) (PMID:PMC917620)

Lee, D. , Robertson, C. and Marques, D. (2022) Quantifying the small-area spatio-temporal dynamics of the Covid-19 pandemic in Scotland during a period with limited testing capacity. Spatial Statistics, 49, 100508. (doi: 10.1016/j.spasta.2021.100508) (PMID:33868908) (PMCID:PMC8035810)

Yin, X., Napier, G. , Anderson, C. and Lee, D. (2022) Spatio-temporal disease risk estimation using clustering-based adjacency modelling. Statistical Methods in Medical Research, 31(6), pp. 1184-1203. (doi: 10.1177/09622802221084131) (PMID:35286183) (PMCID:PMC9245163)

Gerogiannis, G., Tranmer, M. , Lee, D. and Valente, T. (2022) A Bayesian spatio-network model for multiple adolescent adverse health behaviours. Journal of the Royal Statistical Society: Series C (Applied Statistics), 71(2), pp. 271-287. (doi: 10.1111/rssc.12531)

Lee, D. , Meeks, K. and Pettersson, W. (2021) Improved inference for areal unit count data using graph-based optimisation. Statistics and Computing, 31(4), 51. (doi: 10.1007/s11222-021-10025-7)

Lee, D. , Robertson, C., Ramsay, C. and Pyper, K. (2020) Quantifying the impact of the modifiable areal unit problem when estimating the health effects of air pollution. Environmetrics, 31(8), e2643. (doi: 10.1002/env.2643)

Lee, D. (2020) A tutorial on spatio-temporal disease risk modelling in R using Markov chain Monte Carlo simulation and the CARBayesST package. Spatial and Spatio-Temporal Epidemiology, 34, 100353. (doi: 10.1016/j.sste.2020.100353)

Hanlon, P. et al. (2020) Assessing risks of polypharmacy involving medications with anticholinergic properties. Annals of Family Medicine, 18(2), pp. 148-155. (doi: 10.1370/afm.2501) (PMID:32152019) (PMCID:PMC7062487)

Hanlon, P. , McCallum, M. , Jani, B. D. , McQueenie, R., Lee, D. and Mair, F. S. (2020) Association between childhood maltreatment and the prevalence and complexity of multimorbidity: a cross-sectional analysis of 157,357 UK Biobank participants. Journal of Comorbidity, 10, pp. 1-12. (doi: 10.1177/2235042X10944344)

Napier, G. , Lee, D. , Robertson, C. and Lawson, A. (2019) A Bayesian space–time model for clustering areal units based on their disease trends. Biostatistics, 20(4), pp. 681-697. (doi: 10.1093/biostatistics/kxy024) (PMID:29917057) (PMCID:PMC6797054)

Jack, E. , Lee, D. and Dean, N. (2019) Estimating the changing nature of Scotland's health inequalities using a multivariate spatiotemporal model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(3), pp. 1061-1080. (doi: 10.1111/rssa.12447) (PMID:31217673) (PMCID:PMC6563432)

Lee, D. , Roertson, C., Ramsay, C., Gillespie, C. and Napier, G. (2019) Estimating the health impact of air pollution in Scotland, and the resulting benefits of reducing concentrations in city centres. Spatial and Spatio-Temporal Epidemiology, 29, pp. 85-96. (doi: 10.1016/j.sste.2019.02.003)

Jani, B. D. , Hanlon, P. , Nicholl, B. I. , McQueenie, R., Gallacher, K. I. , Lee, D. and Mair, F. S. (2019) Relationship between multimorbidity, demographic factors and mortality: findings from the UK Biobank Cohort. BMC Medicine, 17, 74. (doi: 10.1186/s12916-019-1305-x) (PMID:30967141) (PMCID:PMC6456941)

Lee, D. (2018) A locally adaptive process-convolution model for estimating the health impact of air pollution. Annals of Applied Statistics, 12(4), pp. 2540-2558. (doi: 10.1214/18-AOAS1167)

Jani, B. D. , Nicholl, B. I. , McQueenie, R., Connelly, D. T., Hanlon, P. , Gallacher, K. I. , Lee, D. and Mair, F. S. (2018) Multimorbidity and co-morbidity in atrial fibrillation and effects on survival: findings from UK Biobank cohort. Europace, 20, f329-f336. (doi: 10.1093/europace/eux322) (PMID:29112751) (PMCID:PMC6277149)

Young, D. M., Parry, L. E. , Lee, D. and Ray, S. (2018) Spatial models with covariates improve estimates of peat depth in blanket peatlands. PLoS ONE, 13(9), e0202691. (doi: 10.1371/journal.pone.0202691) (PMID:30192790) (PMCID:PMC6128521)

Cullen, B. , Newby, D., Lee, D. , Lyall, D. M. , Nevado-Holgado, A. J., Evans, J. J. , Pell, J. P. , Lovestone, S. and Cavanagh, J. (2018) Cross-sectional and longitudinal analyses of outdoor air pollution exposure and cognitive function in UK Biobank. Scientific Reports, 8, 12089. (doi: 10.1038/s41598-018-30568-6) (PMID:30108252) (PMCID:PMC6092329)

Hanlon, P. , Nicholl, B. I. , Jani, B. D. , Lee, D. , McQueenie, R. and Mair, F. S. (2018) Frailty and pre-frailty in middle-aged and older adults and its association with multimorbidity and mortality: a prospective analysis of 493,737 UK Biobank participants. Lancet Public Health, 3(7), e323-e332. (doi: 10.1016/S2468-2667(18)30091-4) (PMID:29908859) (PMCID:PMC6028743)

Lee, D. , Rushworth, A. and Napier, G. (2018) Spatio-temporal areal unit modelling in R with conditional autoregressive priors using the CARBayesST package. Journal of Statistical Software, 84(9), (doi: 10.18637/jss.v084.i09)

Huang, G., Lee, D. and Scott, E. M. (2018) Multivariate space-time modelling of multiple air pollutants and their health effects accounting for exposure uncertainty. Statistics in Medicine, 37(7), pp. 1134-1148. (doi: 10.1002/sim.7570)

Gallacher, K. I. , McQueenie, R., Nicholl, B. , Jani, B. D. , Lee, D. and Mair, F. S. (2018) Risk factors and mortality associated with multimorbidity in people with stroke or transient ischaemic attack: a study of 8,751 UK Biobank participants. Journal of Comorbidity, 8(1), pp. 1-8. (doi: 10.15256/joc.2018.8.129)

Hanlon, P. , Nicholl, B. I. , Jani, B. D. , McQueenie, R., Lee, D. , Gallacher, K. I. and Mair, F. S. (2018) Examining patterns of multimorbidity, polypharmacy and risk of adverse drug reactions in chronic obstructive pulmonary disease: a cross-sectional UK Biobank study. BMJ Open, 8(1), e018404. (doi: 10.1136/bmjopen-2017-018404) (PMID:29332840) (PMCID:PMC5781016)

Neslihanoglu, S., Sogiakas, V., McColl, J. and Lee, D. (2017) Nonlinearities in the CAPM: evidence from developed and emerging markets. Journal of Forecasting, 36(8), pp. 867-897. (doi: 10.1002/for.2389)

Lee, D. , Mukhopadhyay, S., Rushworth, A. and Sahu, S. K. (2017) A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health. Biostatistics, 18(2), pp. 370-385. (doi: 10.1093/biostatistics/kxw048) (PMID:28025181)

Pannullo, F., Lee, D. , Neal, L., Dalvi, M., Agnew, P., O'Connor, F. M., Mukhopadhyay, S., Sahu, S. and Sarran, C. (2017) Quantifying the impact of current and future concentrations of air pollutants on respiratory disease risk in England. Environmental Health, 16, 29. (doi: 10.1186/s12940-017-0237-1) (PMID:28347336) (PMCID:PMC5368918)

Anderson, C. , Lee, D. and Dean, N. (2017) Spatial clustering of average risks and risk trends in Bayesian disease mapping. Biometrical Journal, 59(1), pp. 41-56. (doi: 10.1002/bimj.201600018) (PMID:27492753)

Rushworth, A., Lee, D. and Sarran, C. (2017) An adaptive spatio-temporal smoothing model for estimating trends and step changes in disease risk. Journal of the Royal Statistical Society: Series C (Applied Statistics), 66(1), pp. 141-157. (doi: 10.1111/rssc.12155)

Lee, D. and Lawson, A. (2016) Quantifying the spatial inequality and temporal trends in maternal smoking rates in Glasgow. Annals of Applied Statistics, 10(3), pp. 1427-1446. (doi: 10.1214/16-AOAS941) (PMID:28580047) (PMCID:PMC5449583)

Lawson, A. B., Lee, D. and MacNab, Y. (2016) Editorial. Statistical Methods in Medical Research, 25(4), p. 1079. (doi: 10.1177/0962280216660410) (PMID:27566766)

Napier, G. , Lee, D. , Robertson, C., Lawson, A. and Pollock, K. G. (2016) A model to estimate the impact of changes in MMR vaccine uptake on inequalities in measles susceptibility in Scotland. Statistical Methods in Medical Research, 25(4), pp. 1185-1200. (doi: 10.1177/0962280216660420) (PMID:27566772)

Pannullo, F., Lee, D. , Waclawski, E. and Leyland, A. H. (2016) How robust are the estimated effects of air pollution on health? Accounting for model uncertainty using Bayesian model averaging. Spatial and Spatio-Temporal Epidemiology, 18, pp. 53-62. (doi: 10.1016/j.sste.2016.04.001) (PMID:27494960) (PMCID:PMC4985538)

Anderson, C., Lee, D. and Dean, N. (2016) Bayesian cluster detection via adjacency modelling. Spatial and Spatio-Temporal Epidemiology, 16, pp. 11-20. (doi: 10.1016/j.sste.2015.11.005) (PMID:26919751)

Kavanagh, L., Lee, D. and Pryce, G. (2016) Is poverty decentralizing? Quantifying uncertainty in the decentralization of urban poverty. Annals of the American Association of Geographers, 106(6), pp. 1286-1298. (doi: 10.1080/24694452.2016.1213156)

Lee, D. and Sarran, C. (2015) Controlling for unmeasured confounding and spatial misalignment in long-term air pollution and health studies. Environmetrics, 26(7), pp. 477-487. (doi: 10.1002/env.2348)

Huang, G., Lee, D. and Scott, M. (2015) An integrated Bayesian model for estimating the long-term health effects of air pollution by fusing modelled and measured pollution data: a case study of nitrogen dioxide concentrations in Scotland. Spatial and Spatio-Temporal Epidemiology, 14-15, pp. 63-74. (doi: 10.1016/j.sste.2015.09.002) (PMID:26530824)

Pannullo, F., Lee, D. , Waclawski, E. and Leyland, A. H. (2015) Improving spatial nitrogen dioxide prediction using diffusion tubes: a case study in West Central Scotland. Atmospheric Environment, 118, pp. 227-235. (doi: 10.1016/j.atmosenv.2015.08.009) (PMID:26435684) (PMCID:PMC4567077)

Lee, D. , Minton, J. and Pryce, G. (2015) Bayesian inference for the dissimilarity index in the presence of spatial autocorrelation. Spatial Statistics, 11, pp. 81-95. (doi: 10.1016/j.spasta.2014.12.001)

Livingston, M. and Lee, D. (2014) "The Glasgow effect?"– the result of the geographical patterning of deprived areas? Health and Place, 29, pp. 1-9. (doi: 10.1016/j.healthplace.2014.05.002)

Anderson, C., Lee, D. and Dean, N. (2014) Identifying clusters in Bayesian disease mapping. Biostatistics, 15(3), pp. 457-469. (doi: 10.1093/biostatistics/kxu005) (PMID:24622038)

Rushworth, A., Lee, D. and Mitchell, R. (2014) A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London. Spatial and Spatio-Temporal Epidemiology, 10, pp. 29-38. (doi: 10.1016/j.sste.2014.05.001)

Eze, J.I., Scott, E.M. , Pollock, K.G., Stidson, R., Miller, C.A. and Lee, D. (2014) The association of weather and bathing water quality on the incidence of gastrointestinal illness in the west of Scotland. Epidemiology and Infection, 142(6), pp. 1289-1299. (doi: 10.1017/S0950268813002148) (PMID:24007797)

Lee, D. , Rushworth, A. and Sahu, S. K. (2014) A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution. Biometrics, 70(2), pp. 419-429. (doi: 10.1111/biom.12156) (PMID:24571082) (PMCID:PMC4282098)

Powell, H. and Lee, D. (2014) Modelling spatial variability in concentrations of single pollutants and composite air quality indicators in health effects studies. Journal of the Royal Statistical Society: Series A (Statistics in Society), 177(3), pp. 607-623. (doi: 10.1111/rssa.12034)

Miller, C. , Magdalina, A.-M., Willows, R., Bowman, A. , Scott, E. , Lee, D. , Burgess, C., Pope, L., Pannullo, F. and Haggarty, R. (2014) Spatiotemporal statistical modelling of long-term change in river nutrient concentrations in England & Wales. Science of the Total Environment, 466-7, pp. 914-923. (doi: 10.1016/j.scitotenv.2013.07.113) (PMID:23988742)

Lee, D. and Mitchell, R. (2014) Controlling for localised spatio-temporal autocorrelation in long-term air pollution and health studies. Statistical Methods in Medical Research, 23(6), pp. 488-506. (doi: 10.1177/0962280214527384)

Mitchell, R. and Lee, D. (2014) Is there really a "wrong side of the tracks" in urban areas and does it matter for spatial analysis? Annals of the Association of American Geographers, 104(3), pp. 432-443. (doi: 10.1080/00045608.2014.892321)

Lee, D. (2013) CARBayes: an R package for Bayesian spatial modeling with conditional autoregressive priors. Journal of Statistical Software, 55(13), pp. 1-24.

Lee, D. and Mitchell, R. (2013) Locally adaptive spatial smoothing using conditional auto-regressive models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 62(4), pp. 593-608. (doi: 10.1111/rssc.12009)

Shaddick, G., Lee, D. and Wakefield, J. (2013) Ecological bias in studies of the short-term effects of air pollution on health. International Journal of Applied Earth Observation and Geoinformation, 22, pp. 65-74. (doi: 10.1016/j.jag.2012.03.011)

Powell, H., Lee, D. and Bowman, A. (2012) Estimating constrained concentration-response functions between air pollution and health. Environmetrics, 23(3), pp. 228-237. (doi: 10.1002/env.1150)

Lee, D. (2012) Using spline models to estimate the varying health risks from air pollution across Scotland. Statistics in Medicine, 31(27), pp. 3366-3378. (doi: 10.1002/sim.5420)

Lee, D. and Mitchell, R. (2012) Boundary detection in disease mapping studies. Biostatistics, 13(3), pp. 415-426. (doi: 10.1093/biostatistics/kxr036)

Willocks, L., Bhaskar, A., Ramsay, C., Lee, D. , Brewster, D., Fischbacher, C., Chalmers, J., Morris, G. and Scott, E.M. (2012) Cardiovascular disease and air pollution in Scotland: no association or insufficient data and study design? BMC Public Health, 12, p. 227. (doi: 10.1186/1471-2458-12-227)

Lee, D. , Ferguson, C. and Scott, E.M. (2011) Constructing representative air quality indicators with measures of uncertainty. Journal of the Royal Statistical Society: Series A (Statistics in Society), 174(1), pp. 109-126. (doi: 10.1111/j.1467-985X.2010.00658.x)

Lee, D. (2011) A comparison of conditional autoregressive models used in Bayesian disease mapping. Spatial and Spatio-Temporal Epidemiology, 2(2), pp. 79-89. (doi: 10.1016/j.sste.2011.03.001)

Lee, D. and Shaddick, G. (2010) Spatial modeling of air pollution in studies of its short-term health effects. Biometrics, 66(4), pp. 1238-1246. (doi: 10.1111/j.1541-0420.2009.01376.x)

Salway, R., Lee, D. , Shaddick, G. and Walker, S. (2010) Bayesian latent variable modelling in studies of air pollution and health. Statistics in Medicine, 29(26), pp. 2732-2742. (doi: 10.1002/sim.4039)

Lee, D. and Neocleous, T. (2010) Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(5), pp. 905-920. (doi: 10.1111/j.1467-9876.2010.00725.x)

Anderson, C., Lee, D. , Pryce, G. and Taal, M. (2010) Factors affecting environmental attitudes and volunteering in England and Wales. Working Paper, (Unpublished)

Lee, D. , Ferguson, C. and Mitchell, R. (2009) Air pollution and health in Scotland: a multicity study. Biostatistics, 10(3), pp. 409-423. (doi: 10.1093/biostatistics/kxp010) (PMID:19377033)

Lee, D. and Shaddick, G. (2008) Modelling the effects of air pollution on health using Bayesian dynamic generalised linear models. Environmetrics, 19(8), pp. 785-804. (doi: 10.1002/env.894)

Shaddick, G., Lee, D. , Zidek, J. and Salway, R. (2008) Estimating exposure response functions using ambient pollution concentrations. Annals of Applied Statistics, 2(4), pp. 1249-1270. (doi: 10.1214/08-AOAS177)

Lee, D. and Shaddick, G. (2007) Time-varying coefficient models for the analysis of air pollution and health outcome data. Biometrics, 63(4), pp. 1253-1261. (doi: 10.1111/j.1541-0420.2007.00776.x)

Book Sections

Enright, J. , Lee, D. , Meeks, K. , Pettersson, W. and Sylvester, J. (2021) The complexity of finding optimal subgraphs to represent spatial correlation. In: Du, D.-Z., Du, D., Wu, C. and Xu, D. (eds.) Combinatorial Optimization and Applications. Series: Lecture Notes in Computer Science (13135). Springer, pp. 152-166. ISBN 9783030926809 (doi: 10.1007/978-3-030-92681-6_13)

Lawson, A. and Lee, D. (2017) Bayesian disease mapping for public health. In: Srinivasa Rao, A. S.R., Pyne, S. and Rao, C.R. (eds.) Handbook of Statistics. Elsevier, pp. 443-481. ISBN 9780444369684 (doi: 10.1016/bs.host.2017.05.001)

Lee, D. and Sahu, S. (2016) Estimating the health impact of air pollution fields. In: Lawson, A. B., Banerjee, S., Haining, R. P. and Ugarte, M. D. (eds.) Handbook of Spatial Epidemiology. Series: Chapman & Hall/CRC handbooks of modern statistical methods. CRC: Boca Raton, FL, pp. 271-288. ISBN 9781482253016

Conference Proceedings

Zou, Z., O'Donnell, R. , Miller, C. , Lee, D. and Wilkie, C. (2024) A computationally efficient spatio-temporal fusion model for reflectance data. In: Developments in Statistical Modelling, 38th International Workshop on Statistical Modelling (IWSM 2024), Durham, UK, 14-19 Jul 2024, (Accepted for Publication)

Lee, D. , Minton, J. and Pryce, G. (2014) Inference for segregation indices in the presence of spatial autocorrelation. In: Royal Statistical Society Annual Conference 2014, Sheffield, 2-4 Sept 2014,

Lee, D. and Mitchell, R. (2012) Localised spatial smoothing in Bayesian disease mapping. In: Royal Statistical Society (RSS) annual international conference, Telford, UK, 03 Sep 2012,

Lee, D. , Orr, A. and Pryce, G. (2010) Risk pricing on residential mortgages in the UK. In: CCHPR 20th Anniversary Conference: Housing – the next 20 years, Cambridge, 15-16 September 2010, (Unpublished)

Magdalina, A., Ferguson, C. , Bowman, A. , Willows, R., Johnson, D., Burgess, C., Pope, L., Scott, E.M. and Lee, D. (2010) Spatiotemporal modelling of nitrate and phosphorus in river catchments for England and Wales. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010,

Scott, E. M. , Bowman, A. , Ferguson, C., Lee, D., O’Donnell, D., Villoria, M. F. and Gemmell, J. C. (2010) A Statistical Framework for an Evidence Base to Support Environmental Regulation and Policy. In: 25th International Workshop on Statistical Modelling (IWSM 2010), Glasgow, UK, 5-9 Jul 2010, pp. 25-32.

This list was generated on Fri Dec 20 12:00:45 2024 GMT.

Grants

Grants as PI.

  • ESRC grant ‘Allowing for cliffs and slopes in the risk surface when modelling small-area data’, Oct 2010, £52,556.
  • EPSRC grant ‘A rigorous statistical framework for estimating the long-term health effects of air pollution’, Jan 2013, £269,755.
  • MRC grant entitled ‘A flexible class of Bayesian spatio-temporal models for cluster detection, trend estimation and forecasting of disease risk’, Feb 2015, £304, 000.
  • EPSRC grant 'Linking air pollution and health in Scotland to inform on locations for a Low Emission Zone', July 2017, £14,962.
  • TB Alliance grant entitled 'Mathematical modelling of MDR, pre XDR, and XDR burden of the TB population', August 2017, £24,068. 
  • Scottish Government grant entitled `Estimating the effects of air pollution on the Covid-19 epidemic in Scotland', August 2021, £41,335.

 

Grants as CI.

  • Environment Agency  grant `'Spatiotemporal modelling of Nitrate and Phosphorus in River Catchments for England and Wales', March 2009, £61,710.
  • Carnegie scholarship for PhD study for Craig Anderson, October 2011, £63,696.
  • NERC knowledge transfer grant 'Statistics, environmental management, policy and regulation: developing the evidence base', August 2009,  £295,868.85.
  • ESRC grant 'Applied Quantitative Methods Network: Phase II', January 2013, £2,601,794
  • NERC Postgraduate and Professional Skills Development Award, September 2013, £73,000.
  • ESRC grant entitled 'Urban Big Data Research Centre', January 2014, £6,003,547.
  • NERC grant entitled 'Advanced statistics training', September 2014, £73,000.
  • Carnegie scholarship for PhD study for Eilidh Jack, October 2015, £70,000.
  • NERC grant entitled 'Advanced statistics training', September 2015, £70,000.
  • Innovate UK grant entitled 'A new integrated decision-making tool for urban health and policy evaluation: ‘QCumber-envHealth’', October 2015, £456,398.
  • EPSRC grant (as part of the SECURE network) entitled 'Feasibility testing of low-cost sensors to represent spatio-temporal variability of ambient ground-level NO2 and O3 concentrations', October to December 2015, £25,000.
  • CI for a NERC funded CASE PhD studentship, October 2016, £60,000.
  • EPSRC grant (as part of the SECURE network) entitled 'Improved approaches for mapping and modelling blanket peatland extent and depth', May 2016, £24,962.
  • Scottish Executive Health Department grant  entitled 'Multimorbidity in UK Biobank', December 2016, £22,029.
  • EPSRC grant entitled `Multilayer Algorithmics to Leverage Graph Structure (MultilayerALGS)', 2020, £765,538.

 

 

Supervision

  • Boonsuriyatham, Panthakan
    Forecasting Local Net-electricity Demand at scale
  • Foster, Hamish
    Understanding the interplay of lifestyle and deprivation to support policy and intervention development: a mixed methods study
  • Li, Fengjiao
    Spatio-temporal modelling of big disease data combining machine learning and spatial statistics
  • Muegge, Robin
    Spatio-temporal areal data modelling: COVID-19 applications and outlier detection for big data
  • Zhang, Qianruo
    Quantifying the drivers of and magnitudes in health inequalities in big spatial data
  • Zhu, Qiangqiang
    Spatio-temporal modelling of population-level disease risk when the populations at risk have partially unknown spatial locations
  • Zou, Zhaoyuan
    Methodological developments in Data Fusion for Environmental Statistics

Completed / Existing research staff

  • Alastair Rushworth - January 2013 - May 2015,  working on the EPSRC funded project 'A rigorous statistical framework for estimating the long-term health effects of air pollution'.
  • Francesca Pano - June 2015 - December 2015,  working on the EPSRC funded project 'A rigorous statistical framework for estimating the long-term health effects of air pollution'.
  • Gary Napier - March 2015 - August 2018,  working on the MRC funded project 'A flexible class of Bayesian spatio-temporal models for cluster detection, trend estimation and forecasting of disease risk'.

Completed / Existing PhD students

  • Helen Powell - 'Statistical methods in air pollution and health studies', October 2008 until July 2012.
  • Serdar Neslihanoglu - 'Financial time series modelling',  March 2011 until June 2014, jointly with Prof McColl.
  • Craig Anderson -  'Bayesian space-time modelling of disease risk',  October 2011 until February 2015, jointly with Dr Dean.
  • Guowen Huang -  'Space-time air pollution and health modelling',  August 2013 until July 2016, jointly with Prof  Scott.
  • Francesca Pannullo - 'Space-time air pollution and health modelling',  October 2013 until August 2017, jointly with Prof Leyland and Dr  Waclawski.
  • Eilidh Jack - `Space-time modelling of disease risk', October 2015 - July 2019, jointly with Dr Dean.
  • Yoana Borisova - `Space-time modelling of air pollution', October 2016 until current day,  jointly with Prof Scott.
  • Kamol Sanittham - `Spatial modelling of disease risk', October 2016 until March 2021,  jointly with Dr Anderson.
  • Xueqing Yin  - `Spatio-temporal modelling of disease risk', January 2019 until July 2022,  jointly with Dr Anderson and Dr Napier.
  • George Gerogiannis - `Multiple membership multiple classification models', October 2018 - current day, jointly with Prof Tranmer and Prof Moore.
  • Zhaoyuan Zou - `Spatial misalignment in environmental data', October 2019 until current day,  jointly with Dr O'Donnell and Prof Miller.
  • Enoch Havyarimana - `Modelling inflamatory and rheumatic diseases', October 2019 until current day,  jointly with Dr Basu and Dr Cullen.
  • Robin Muegge - `Space-time modelling of disease risk', October 2020 - current day, jointly with Dr Jack and Dr Dean.
  • Hamish Foster - `Factors contributing to ill health in UK Biobank', October 2020 - current day, jointly with Prof Mair.
  • Qiangqiang Zhu - `Fusing machine learning and spatial statistics to estimation air pollution and its health effects', October 2022 - current day, jointly with Dr Stoner. 
  • Panthakan Boonsuriyatham - `Spatio-temporal prediction of energy consumption', November 2022 - current day, jointly with Dr Browell. 

Completed / Existing MSc (by research) students

  • Abita Bhaskar - MSc Statistics - 'Environmental exposures and cardiovascular morbidity in Scotland', October 2007 until February 2009, jointly with Prof Scott.
  • Neil Murphy - MSc Statistics - 'Modelling aids incidence in South Africa', October 2009 until September 2010, jointly with Prof McColl.
  • Greg Halbert - MSc Statistics - 'Estimating the changing effects of air pollution on health in Scotland', October 2010 until September 2012.
  • Katie Stewart - MSc Statistics - 'How much spatial autocorrelation is too much?', October 2013 until January 2015.
  • Cillian Docherty - MSc Statistics - 'Environmental indicators', October 2015 until September 2017, jointly with Prof Scott.
  • Cara MacBride - MSc Statistics - 'Spatial predictive modelling of average property prices', October 2022 until September 2023, jointy with Dr Davies.

Research datasets

Jump to: 2018
Number of items: 1.

2018

Lee, D. (2018) A locally adaptive process-convolution model for estimating the health impact of air pollution. [Data Collection]

This list was generated on Fri Dec 20 12:00:47 2024 GMT.

Additional information

Twitter

@DuncanPLee

Computer software

CARBayes - A package for the statistical software R to implement spatial generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation.The spatial autocorrelation is modelled by a set of random effects, which are assigned a conditional autoregressive (CAR) prior distribution. A number of different CAR priors are available for the random effects, and full details are given in the vignette accompanying the package. The software is available on the Comprehensive R Archive Network (CRAN) here. Over 131,600 downloads since 2013.

CARBayesST - A package for the statistical software R to implement spatio-temporal generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation.The spatio-temporal autocorrelation is modelled by random effects, which are assigned conditional autoregressive (CAR) prior distributions. A number of different random effects structures are available, and full details are given in the vignette accompanying the package. The software is available on the Comprehensive R Archive Network (CRAN) here. Over 51,800 downloads since 2014.

 

Professional activities

  • Member of the UK government advisory committee on the medical effects of air pollutants (COMEAP) between March 2020 and the current day. 
  • Conference chair for the biennial GEOMED conference, which was held in Glasgow in August 2019. 
  • External examiner of BSc and MSci programmes at Queens University Belfast from 2018 to 2023.
  • Associate editorships at Journal of the Royal Statistical Society Series C, Biometrical Journal, Spatial and Spatio-temporal Epidemiology, and Biometrics.
  • Editorial board member at Spatial Statistics.
  • Guest edited three special issues of Statistical Methods in Medical research and one special issue of Spatial and Spatio-temporal Epidemiology.
  • External PhD examiner at the Universities of Bath; Exeter, Lancaster; Leeds; Oxford; Queen Mary University London, Queensland Technology; Southampton; Technology Sydney.
  • Secretary of the environmental statistics section (ESS) of the Royal Statistical Society between 2013 and 2016.
  • Honorary appointment with Public Health Scotland to work on Covid-19 surveillance modelling from April 2020 to current day.
  • Invited member of the Health effects working group that is advising the Cleaner Air for Scotland (CAFS) strategy, versions 1 and 2, January 2019 to 2026.

headshot

Professor Duncan Lee on Twitter