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_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2009 | 2008 | 2007 |

2024

• Economou T, Johnson C, Dyson E. (2024) A hierarchical spline model for correcting and hindcasting temperature data, The Annals of Applied Statistics, volume 18, no. 2, DOI:10.1214/23-aoas1855.
• Lazoglou G, Economou T, Anagnostopoulou C, Zittis G, Tzyrkalli A, Georgiades P, Lelieveld J. (2024) Multivariate adjustment of drizzle bias using machine learning in European climate projections, DOI:10.5194/egusphere-2024-45. [PDF]
• Lazoglou G, Economou T, Anagnostopoulou C, Zittis G, Tzyrkalli A, Georgiades P, Lelieveld J. (2024) Supplementary material to "Multivariate adjustment of drizzle bias using machine learning in European climate projections", DOI:10.5194/egusphere-2024-45-supplement. [PDF]
• Dawkins LC, Brown K, Bernie DJ, Lowe JA, Economou T, Grassie D, Schwartz Y, Godoy-Shimizu D, Korolija I, Mumovic D. (2024) Quantifying overheating risk in English schools: A spatially coherent climate risk assessment, Climate Risk Management, volume 44, DOI:10.1016/j.crm.2024.100602.

2023

• Lazoglou G, Economou T, Anagnostopoulou C, Tzyrkalli A, Zittis G, Lelieveld J. (2023) Bias Correction of Daily Precipitation on Two Eastern Mediterranean Stations with GAMs †, COMECAP 2023, Environmental Sciences Proceedings, volume 26, no. 1, DOI:10.3390/environsciproc2023026017.
• Melas D, Parliari D, Economou T, Giannaros C, Liora N, Papadogiannaki S, Kontos S, Cheristanidis S, Occhiuto D, Frezzini MA. (2023) Developing a System for Integrated Environmental Information in Urban Areas: An Estimation of the Impact of Thermal Stress on Health †, 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023, Environmental Sciences Proceedings, volume 26, no. 1, DOI:10.3390/environsciproc2023026117.
• Kekkou F, Lazoglou G, Economou T, Anagnostopoulou C. (2023) Exploring the Association of Heat Stress and Human Health in Cyprus †, 16th International Conference on Meteorology, Climatology and Atmospheric Physics—COMECAP 2023, Environmental Sciences Proceedings, volume 26, no. 1, DOI:10.3390/environsciproc2023026084.
• Bourtsoukidis E, Pozzer A, Williams J, Makowski D, Peñuelas J, Matthaios V, Economou T, Lazoglou G, Yañez-Serrano AM, Nölscher A. (2023) The temperature sensitivity of mono- and sesquiterpene emissions from terrestrial vegetation: Insights from a meta-analysis, DOI:10.5194/egusphere-egu23-6641. [PDF]
• Lazoglou G, Anagnostopoulou C, Economou T, Tzyrkalli A, Zittis G, Lelieveld J. (2023) Calculation of future Wet and Dry spells duration in Europe, using bias corrected data from the Q-GAM method, DOI:10.5194/ems2023-15. [PDF]
• Economou T, Parliari D, Kushta J. (2023) Using statistical approaches to quantify the synergy of heat stress and air pollution on human mortality for a Mediterranean city, DOI:10.5194/ems2023-69. [PDF]
• Tzyrkalli A, Lazoglou G, Constantinidou K, Economou T, Hadjinicolaou P. (2023) Quantification of the Urban Heat Island effect using paired station data in the Middle East and North Africa region, DOI:10.5194/ems2023-13. [PDF]
• Dawkins LC, Bernie DJ, Lowe JA, Economou T. (2023) Assessing climate risk using ensembles: A novel framework for applying and extending open-source climate risk assessment platforms, Climate Risk Management, volume 40, DOI:10.1016/j.crm.2023.100510.
• Dawkins LC, Bernie DJ, Pianosi F, Lowe JA, Economou T. (2023) Quantifying uncertainty and sensitivity in climate risk assessments: Varying hazard, exposure and vulnerability modelling choices, Climate Risk Management, volume 40, DOI:10.1016/j.crm.2023.100511.
• Bohlinger P, Economou T, Aarnes OJ, Malila M, Breivik Ø. (2023) A general framework to obtain seamless seasonal–directional extreme individual wave heights—Showcase Ekofisk, Ocean Engineering, volume 270, DOI:10.1016/j.oceaneng.2022.113535.
• Urdiales-Flores D, Zittis G, Hadjinicolaou P, Osipov S, Klingmüller K, Mihalopoulos N, Kanakidou M, Economou T, Lelieveld J. (2023) Drivers of accelerated warming in Mediterranean climate-type regions, npj Climate and Atmospheric Science, volume 6, no. 1, DOI:10.1038/s41612-023-00423-1.
• Stoner O, Halliday A, Economou T. (2023) Correcting delayed reporting of COVID-19 using the generalized-Dirichlet-multinomial method, Biometrics, volume 79, no. 3, pages 2537-2550, DOI:10.1111/biom.13810. [PDF]
• Economou T, Lazoglou G, Tzyrkalli A, Constantinidou K, Lelieveld J. (2023) A data integration framework for spatial interpolation of temperature observations using climate model data, PeerJ, volume 11, DOI:10.7717/peerj.14519. [PDF]
• Steptoe H, Economou T. (2023) Proliferation of atmospheric datasets can hinder policy making: a data blending technique offers a solution, Front Big Data, volume 6, DOI:10.3389/fdata.2023.1198097. [PDF]
• Hajat S, Proestos Y, Araya-Lopez J-L, Economou T, Lelieveld J. (2023) Current and future trends in heat-related mortality in the MENA region: a health impact assessment with bias-adjusted statistically downscaled CMIP6 (SSP-based) data and Bayesian inference, Lancet Planet Health, volume 7, no. 4, pages e282-e290, DOI:10.1016/S2542-5196(23)00045-1. [PDF]
• Shackleton D, Economou T, Memon FA, Chen A, Dutta S, Kanungo S, Deb A. (2023) Seasonality of cholera in Kolkata and the influence of climate, BMC Infectious Diseases, volume 23, no. 1, article no. 572, DOI:10.1186/s12879-023-08532-1. [PDF]
• Shackleton D, Economou T, Memon F, Chen A, Dutta S, Kanungo S. (2023) Seasonality of Cholera in Kolkata and the Influence of Climate, DOI:10.21203/rs.3.rs-2539131/v1.
• Garrett JK, White MP, Elliott LR, Grellier J, Bell S, Bratman GN, Economou T, Gascon M, Lõhmus M, Nieuwenhuijsen M. (2023) Applying an ecosystem services framework on nature and mental health to recreational blue space visits across 18 countries, Sci Rep, volume 13, no. 1, DOI:10.1038/s41598-023-28544-w. [PDF]
• Kirkwood C, Economou T, Odbert H, Pugeault N. (2023) Can learning regression features by computer vision improve the generalisation of geostastistical interpolators?, DOI:10.5194/egusphere-egu23-6656. [PDF]
• Kirkwood C. (2023) Methods in machine learning for probabilistic modelling of environment, with applications in meteorology and geology.
• Stoner O, Economou T, Torres R, Ashton I, Brown AR. (2023) Quantifying Spatio-temporal risk of Harmful Algal Blooms and their impacts on bivalve shellfish mariculture using a data-driven modelling approach, Harmful Algae, volume 121, pages 102363-102363, article no. 102363, DOI:10.1016/j.hal.2022.102363. [PDF]

2022

• Economou T, Garry F. (2022) Probabilistic Simulationof Big Climate Data for Robust Quantification of Changes in Compound Hazard Events, DOI:10.2139/ssrn.4106219.
• Economou T, Garry F. (2022) Probabilistic modelling and simulation of big spatio-temporal climate data for quantifying future changes of compound events, DOI:10.5194/egusphere-egu22-3392. [PDF]
• Lee SA, Economou T, Lowe R. (2022) A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping. [PDF]
• Dawkins LC, Osborne JM, Economou T, Darch GJC, Stoner OR. (2022) The Advanced Meteorology Explorer: a novel stochastic, gridded daily rainfall generator, Journal of Hydrology, volume 607, DOI:10.1016/j.jhydrol.2022.127478.
• Lee SA, Economou T, Lowe R. (2022) A Bayesian modelling framework to quantify multiple sources of spatial variation for disease mapping, J R Soc Interface, volume 19, no. 194, DOI:10.1098/rsif.2022.0440. [PDF]
• Economou T, Garry F. (2022) Probabilistic simulation of big climate data for robust quantification of changes in compound hazard events, Weather Clim Extrem, volume 38, DOI:10.1016/j.wace.2022.100522. [PDF]
• Kirkwood C, Economou T, Odbert H, Pugeault N. (2022) A deep mixture density network for outlier-corrected interpolation of crowd-sourced weather data. [PDF]
• Kirkwood C, Economou T, Pugeault N, Odbert H. (2022) Bayesian Deep Learning for Spatial Interpolation in the Presence of Auxiliary Information, Mathematical Geosciences, volume 54, no. 3, pages 507-531, DOI:10.1007/s11004-021-09988-0. [PDF]

2021

• Stoner O, Lewis J, Martínez I, Gumy S, Economou T, Adair-Rohani H. (2021) What fuels the fire? Cooking fuel estimates at global, regional and country level for 1990-2030, DOI:10.21203/rs.3.rs-251806/v1.
• Lee SA, Economou T, de Castro Catão R, Barcellos C, Lowe R. (2021) The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil, DOI:10.1101/2021.09.16.21263065.
• Lee SA, Economou T, de Castro Catão R, Barcellos C, Lowe R. (2021) The impact of climate suitability, urbanisation, and connectivity on the expansion of dengue in 21st century Brazil, PLoS Negl Trop Dis, volume 15, no. 12, DOI:10.1371/journal.pntd.0009773. [PDF]
• Kirkwood C, Economou T, Odbert H, Pugeault N. (2021) Bayesian deep learning for large scale environmental data modelling. [PDF]
• Stoner O, Economou T, Torres R, Ashton I, Brown A. (2021) Predicting Harmful Algal Blooms and Impacts on Shellfish Mariculture using Novel Data-Driven Approaches, DOI:10.21203/rs.3.rs-668820/v1.
• Creer S, Rowney FM, Brennan GL, Skjoth C, Griffith G, Mcinnes RN, Clewlow Y, Adams-Groom B, Barber A, Devere N. (2021) Environmental DNA analyses reveal links between abundance and composition of airborne grass pollen and population scale respiratory health, ALLERGY, volume 76, pages 316-316. [PDF]
• Stoner O, Lewis J, Martínez IL, Gumy S, Economou T, Adair-Rohani H. (2021) Household cooking fuel estimates at global and country level for 1990 to 2030, Nat Commun, volume 12, no. 1, DOI:10.1038/s41467-021-26036-x. [PDF]
• Davison SMC, White MP, Pahl S, Taylor T, Fielding K, Roberts BR, Economou T, McMeel O, Kellett P, Fleming LE. (2021) Public concern about, and desire for research into, the human health effects of marine plastic pollution: Results from a 15-country survey across Europe and Australia, Global Environmental Change, volume 69, pages 102309-102309, article no. 102309, DOI:10.1016/j.gloenvcha.2021.102309. [PDF]
• Lee SA, Jarvis CI, Edmunds WJ, Economou T, Lowe R. (2021) Spatial connectivity in mosquito-borne disease models: a systematic review of methods and assumptions, J R Soc Interface, volume 18, no. 178, DOI:10.1098/rsif.2021.0096. [PDF]
• Steptoe H, Economou T. (2021) Extreme wind return periods from tropical cyclones in Bangladesh: insights from a high-resolution convection-permitting numerical model, Natural Hazards and Earth System Sciences, volume 21, no. 4, pages 1313-1322, DOI:10.5194/nhess-21-1313-2021. [PDF]
• Lee SA, Economou T, Barcellos C, Catão R, Carvalho MS, Lowe R. (2021) Effect of climate change, connectivity, and socioeconomic factors on the expansion of the dengue virus transmission zone in 21st century Brazil: an ecological modelling study, The Lancet Planetary Health, volume 5, pages S14-S14, DOI:10.1016/s2542-5196(21)00098-x. [PDF]
• White MP, Elliott LR, Grellier J, Economou T, Bell S, Bratman GN, Cirach M, Gascon M, Lima ML, Lõhmus M. (2021) Associations between green/blue spaces and mental health across 18 countries, Sci Rep, volume 11, no. 1, DOI:10.1038/s41598-021-87675-0. [PDF]
• Kirkwood C, Economou T, Odbert H, Pugeault N. (2021) Bayesian deep learning for large scale environmental data modelling, The Turing Presents: AI UK, The Alan Turing Institute, Uk, 23rd - 24th Mar 2021.
• Rowney FM, Brennan GL, Skjøth C, Griffith GW, Clewlow Y, Adams-Groom B, Barber A, De Vere N, Economou T, Hegarty M. (2021) Environmental DNA reveals links between abundance and composition of airborne grass pollen and respiratory health, Current Biology.
• Richardson S, Lintott P, Hosken D, Economou T, Matthews F. (2021) Peaks in bat activity at turbines and the implications for mitigating the impact of wind energy developments on bats, Scientific Reports, volume 11, DOI:10.1038/s41598-021-82014-9.
• Kirkwood C, Economou T, Odbert H, Pugeault N. (2021) A framework for probabilistic weather forecast post-processing across models and lead times using machine learning, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, volume 379, no. 2194, pages 20200099-20200099, DOI:10.1098/rsta.2020.0099. [PDF]

2020

• Kirkwood C, Economou T, Odbert H, Pugeault N. (2020) A framework for probabilistic weather forecast post-processing across models and lead times using machine learning, DOI:10.48550/arxiv.2005.06613.
• Steptoe H, Economou T. (2020) Improving our understanding of wind extremes from Bangladesh tropical cyclones: insights from a high-resolution convection-permitting numerical model, volume 2020, pages 1-18, DOI:10.5194/nhess-2020-299.
• Tester-Jones M, White MP, Elliott LR, Weinstein N, Grellier J, Economou T, Bratman GN, Cleary A, Gascon M, Korpela KM. (2020) Results from an 18 country cross-sectional study examining experiences of nature for people with common mental health disorders, Scientific Reports, volume 10, no. 1, article no. 19408, DOI:10.1038/s41598-020-75825-9. [PDF]
• Orton F, Svanholm S, Jansson E, Carlsson Y, Eriksson A, Uren Webster T, McMillan T, Leishman M, Verbruggen B, Economou T. (2020) A laboratory investigation into features of morphology and physiology for their potential to predict reproductive success in male frogs, PLOS ONE, volume 15, no. 11, pages e0241625-e0241625, DOI:10.1371/journal.pone.0241625. [PDF]
• Xiong X, Youngman BD, Economou T. (2020) Data fusion with Gaussian processes for estimation of environmental hazard events, Environmetrics, volume 32, no. 3, DOI:10.1002/env.2660. [PDF]
• Dodd R, Chadwick D, Harris I, Hines A, Hollis D, Economou T, Gwynn-Jones D, Scullion J, Robinson D, Jones D. (2020) Spatial co-localisation of extreme weather events: a clear and present danger, Ecology Letters, DOI:10.22541/au.159076913.30642070.
• Kirkwood C, Economou T, Pugeault N. (2020) Bayesian deep learning for mapping via auxiliary information: a new era for geostatistics?. [PDF]
• Stoner O, Economou T. (2020) A more transparent way to estimate and report daily Covid-19 deaths.
• Stoner O, Economou T. (2020) Multivariate hierarchical frameworks for modeling delayed reporting in count data, Biometrics, volume 76, no. 3, pages 789-798, DOI:10.1111/biom.13188.
• Stoner O, Economou T. (2020) An advanced hidden Markov model for hourly rainfall time series, Computational Statistics and Data Analysis, volume 152, DOI:10.1016/j.csda.2020.107045.
• Stoner O, Shaddick G, Economou T, Gumy S, Lewis J, Lucio I, Ruggeri G, Adair-Rohani H. (2020) Global Household Energy Model: A Multivariate Hierarchical Approach to Estimating Trends in the Use of Polluting and Clean Fuels for Cooking, Journal of the Royal Statistical Society Series C: Applied Statistics, DOI:10.1111/rssc.12428.

2019

• Stoner O, Economou T. (2019) Multivariate Hierarchical Frameworks for Modelling Delayed Reporting in Count Data, DOI:10.48550/arxiv.1904.03397.
• Stoner O, Economou T. (2019) An Advanced Hidden Markov Model for Hourly Rainfall Time Series, DOI:10.48550/arxiv.1906.03846.
• Stoner O, Shaddick G, Economou T, Gumy S, Lewis J, Lucio I, Ruggeri G, Adair-Rohani H. (2019) Global Household Energy Model: A Multivariate Hierarchical Approach to Estimating Trends in the Use of Polluting and Clean Fuels for Cooking, DOI:10.48550/arxiv.1901.02791.
• F R, C P, G B, N O, T E, R M, S C, N DV, C S, B W. (2019) Respiratory health outcomes associated with different grass taxa in the UK, Environmental Epidemiology, volume 3, no. Supplement 1, pages 342-342, DOI:10.1097/01.ee9.0000609768.07517.40.
• Stoner O, Economou T, Halliday A. (2019) A Powerful Modelling Framework for Nowcasting and Forecasting COVID-19 and Other Diseases. [PDF]
• Auzenbergs M, Correia-Gomes C, Economou T, Lowe R, O’Reilly KM. (2019) Desirable BUGS in models of infectious diseases, Epidemics, volume 29, pages 100361-100361, article no. 100361, DOI:10.1016/j.epidem.2019.100361. [PDF]
• Stoner O. (2019) Bayesian Hierarchical Modelling Frameworks for Flawed Data in Environment and Health.
• Stoner OR, Shaddick G, Economou T, Gumy S, Lewis J, Lucio I, Ruggeri G, Adair-Rohani H. (2019) Multivariate Hierarchical Modelling of Household Air Pollution, 34th International Workshop on Statistical Modelling, Guimarães, Portugal, 7th - 12th Jul 2019, Proceedings of the 34th International Workshop on Statistical Modelling, volume 2, pages 242-247.
• Economou T, Menary M. (2019) A hidden semi-Markov model for characterising regime shifts in ocean density variability, Journal of the Royal Statistical Society: Series C, volume 68, pages 1529-1553, DOI:10.1111/rssc.12373. [PDF]
• Bohlinger P, Breivik O, Economou T, Muller M. (2019) A novel approach to computing super observations for probabilistic wave model validation, Ocean Modelling, volume 139, DOI:10.1016/j.ocemod.2019.101404.
• Pope ECD, Buontempo C, Economou T. (2019) Exploring constraints on the realised value of a forecast-based climate service, Climate Services, DOI:10.1016/j.cliser.2019.100102.
• Stoner O, Economou T, Drummond Marques da Silva G. (2019) A Hierarchical Framework for Correcting Under-Reporting in Count Data, Journal of the American Statistical Association, volume 114, no. 528, pages 1481-1492, DOI:10.1080/01621459.2019.1573732.
• Bastos L, Economou T, Gomes M, Villela D, Coelho F, Cruz O, Stoner O, Bailey T, Codeço C. (2019) A modelling approach for correcting reporting delays in disease surveillance data, Statistics in Medicine, DOI:10.1002/sim.8303.

2018

• Stoner O, Economou T, Drummond G. (2018) A Hierarchical Framework for Correcting Under-Reporting in Count Data, DOI:10.48550/arxiv.1809.00544.
• Ho K, Economou T, Smart N, Daniels I. (2018) Radiological progression of end colostomy trephine diameter and area, BJS Open, DOI:10.1002/bjs5.50109.
• Stoner O, Economou T. (2018) Correcting Under-Reporting in Historical Volcano Data, International Workshop on Statistical Modelling, Bristol, Uk, Proceedings of the 33rd International Workshop on Statistical Modelling, volume 1, pages 288-292.
• Orton F, Säfholm M, Jansson E, Carlsson Y, Eriksson A, Fick J, Uren Webster T, McMillan T, Leishman M, Verbruggen B. (2018) Exposure to an anti-androgenic herbicide negatively impacts reproductive physiology and fertility in Xenopus tropicalis, Sci Rep, volume 8, no. 1, DOI:10.1038/s41598-018-27161-2. [PDF]

2017

• Bastos L, Economou T, Gomes M, Villela D, Coelho F, Cruz O, Stoner O, Bailey T, Codeço C. (2017) Modelling reporting delays for disease surveillance data, DOI:10.48550/arxiv.1709.09150.
• Sanderson MG, Economou T, Salmon KH, Jones SEO. (2017) Historical trends and variability in heat waves in the United Kingdom, Atmosphere, volume 8, DOI:10.3390/atmos8100191.
• Pope ECD, Buontempo C, Economou T. (2017) Quantifying how user-interaction can modify the perception of the value of climate information: A Bayesian approach, Climate Services, DOI:10.1016/j.cliser.2017.06.006.
• Youngman BD, Economou T. (2017) Generalised additive point process models for natural hazard occurrence, Environmetrics, DOI:10.1002/env.2444.

2016

• Economou T, Stephenson DB, Rougier JC, Neal RA, Mylne KR. (2016) On the use of Bayesian decision theory for issuing natural hazard warnings, Proceedings of the Royal Society of London. Series A, Mathematical and physical sciences, volume 472, no. 2194, DOI:10.1098/rspa.2016.0295. [PDF]
• Simpson M, James R, Hall JW, Borgomeo E, Ives MC, Almeida S, Kingsborough A, Economou T, Stephenson DB, Wagener T. (2016) Decision Analysis for Management of Natural Hazards, Annual Review of Environment and Resources, volume 41, pages 15.1-15.28, DOI:10.1146/annurev-environ-110615-090011.
• Pinto JG, Ulbrich S, Economou T, Stephenson DB, Karrenman M, Shaffrey LC. (2016) Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method, Tellus A, volume 68, DOI:10.3402/tellusa.v68.32204.
• Ffrench-Constant RH, Somers-Yeates R, Bennie J, Economou T, Hodgson D, Spalding A, McGregor PK. (2016) Light pollution is associated with earlier tree budburst across the United Kingdom, Proceedings of the Royal Society of London. Series B.

2015

• Economou T, Stephenson DB, Ferro CAT. (2015) Spatio-temporal modelling of extreme storms, DOI:10.48550/arxiv.1501.06377.
• Economou T, Stephenson DB, Pinto JG, Shaffrey LC, Zappa G. (2015) Serial clustering of extratropical cyclones in a multi-model ensemble of historical and future simulations, Quarterly Journal of the Royal Meteorological Society, volume 141, no. 693, pages 3076-3087, DOI:10.1002/qj.2591.
• Ho KK, Economou T, White ES, Smart NJ, Daniels IR. (2015) THE COLOSTOMY LOCATION AND RADIOLOGICAL PROGRESSION OF TREPHINE SIZE OVER TIME: A CLUE TO THE DEVELOPMENT OF PARASTOMAL HERNIA?, GUT, volume 64, pages A534-A535, DOI:10.1136/gutjnl-2015-309861.1169. [PDF]
• Hunter A, Stephenson DB, Economou T, Holland M, Cook I. (2015) New perspectives on the collective risk of extratropical cyclones, Quarterly Journal of the Royal Meteorological Society, volume 142, no. 694, pages 243-256, DOI:10.1002/qj.2649. [PDF]
• Economou T, Stephenson DB, Pinto JG, Shaffrey LC, Zappa G. (2015) Serial clustering of extratropical cyclones in a multi‐model ensemble of historical and future simulations, Quarterly Journal of the Royal Meteorological Society, volume 141, no. 693, pages 3076-3087, DOI:10.1002/qj.2591. [PDF]
• Taylor MS, Wheeler BW, White MP, Economou T, Osborne NJ. (2015) Research note: Urban street tree density and antidepressant prescription rates—A cross-sectional study in London, UK, Landscape and Urban Planning, volume 136, pages 174-179, DOI:10.1016/j.landurbplan.2014.12.005. [PDF]

2014

• Alves S, Economou T, Carvalho M, Bailey T, Pina M. (2014) In-hospital fatality following hip fracture care in Portugal: understand the role of patient characteristics and compare providers, European Journal of Public Health, volume 24, no. suppl_2, pages cku166-cku092, DOI:10.1093/eurpub/cku166.092.
• Oliveira CM, Economou T, Bailey TC, Carvalho M, Pina MF. (2014) Effects of climatic factors on spatial-temporal distribution of hip fracture, European Journal of Public Health, volume 24, no. supp 2, pages cku162.079-cku162.079, DOI:10.1093/eurpub/cku162.079.
• Economou T, Bailey TC, Kapelan Z. (2014) MCMC implementation for Bayesian hidden semi-Markov models with illustrative applications, Statistics and Computing, volume 24, no. 5, pages 739-752, DOI:10.1007/s11222-013-9399-z.
• Kapsch M, Graversen RG, Economou T, Tjernström M. (2014) The importance of spring atmospheric conditions for predictions of the Arctic summer sea ice extent, Geophysical Research Letters, volume 41, no. 14, pages 5288-5296, DOI:10.1002/2014gl060826. [PDF]
• Oliveira CM, Economou T, Bailey T, Mendonça D, Pina MF. (2014) The interactions between municipal socioeconomic status and age on hip fracture risk, Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, volume 26, no. 2, pages 489-498, DOI:10.1007/s00198-014-2869-0.
• Correia-Gomes C, Economou T, Bailey T, Brazdil P, Alban L, Niza-Ribeiro J. (2014) Transmission parameters estimated for salmonella typhimurium in swine using susceptible-infectious-resistant models and a bayesian approach, BMC Veterinary Research, volume 10, DOI:10.1186/1746-6148-10-101.
• Economou T, Stephenson DB, Ferro CAT. (2014) Spatio-temporal modelling of extreme storms, The Annals of Applied Statistics, volume 8, no. 4, DOI:10.1214/14-aoas766. [PDF]
• Correia-Gomes C, Economou T, Bailey T, Brazdil P, Alban L, Niza-Ribeiro J. (2014) Transmission parameters estimated for Salmonella typhimurium in swine using susceptible-infectious-resistant models and a Bayesian approach, BMC Veterinary Research, volume 10, no. 1, pages 101-101, DOI:10.1186/1746-6148-10-101. [PDF]

2013

• Correia-Gomes C, Economou T, Bailey T, Brazdil P, Vieira-Pinto M, Niza-Ribeiro J. (2013) Simulation Model for Salmonella Typhimurium on a Farrow-to-Finish Herd, International Conference on the Epidemiology and Control of Biological, Chemical and Physical Hazards in Pigs and Pork, DOI:10.31274/safepork-180809-937.
• Kwiatkowski L, Cox PM, Economou T, Halloran PR, Mumby PJ, Booth BBB, Carilli J, Guzman HM. (2013) Caribbean coral growth influenced by anthropogenic aerosol emissions, Nature Geoscience, volume 6, no. 5, pages 362-366, DOI:10.1038/ngeo1780. [PDF]
• Alves SM, Economou T, Oliveira C, Ribeiro AI, Neves N, Goméz-Barrena E, Pina MF. (2013) Osteoporotic hip fractures: Bisphosphonates sales and observed turning point in trend. A population-based retrospective study, Bone, volume 53, no. 2, pages 430-436, DOI:10.1016/j.bone.2012.12.014. [PDF]

2012

• Correia-Gomes C, Economou T, Mendonça D, Vieira-Pinto M, Niza-Ribeiro J. (2012) Assessing risk profiles for Salmonella serotypes in breeding pig operations in Portugal using a Bayesian hierarchical model, BMC Veterinary Research, volume 8, no. 1, pages 226-226, DOI:10.1186/1746-6148-8-226. [PDF]
• Kapsch M, Kunz M, Vitolo R, Economou T. (2012) Long‐term trends of hail‐related weather types in an ensemble of regional climate models using a Bayesian approach, Journal of Geophysical Research: Atmospheres, volume 117, no. D15, DOI:10.1029/2011jd017185. [PDF]
• Economou T, Kapelan Z, Bailey TC. (2012) On the prediction of underground water pipe failures: zero inflation and pipe-specific effects, Journal of Hydroinformatics, volume 14, no. 4, pages 872-883, DOI:10.2166/hydro.2012.144. [PDF]

2009

• Economou T, Kapelan Z, Bailey TC. (2009) Bayesian pipe burst models using cumulative failure history, Alexandroupolis, Thrace, Greece, Proceedings of Asset Management of Medium and Small Wastewater Utilities Conference.
• Economou T, Vitolo R, Bailey TC, Waterhouse E, Kapelan Z. (2009) A latent structure model for high river flows, Ithaka, Ny, 20th - 24th Jul 2009, 24th International Workshop on Statistical Modelling.

2008

• Bailey TC, Economou T. (2008) A hidden semi-Markov model for recurrent events, Dublin, Ireland, Proceedings of XXIV International Biometric Conference.
• Economou T, Kapelan Z, Bailey TC. (2008) A Zero-Inflated Bayesian Model for the Prediction of Water Pipe Bursts, South Africa, Proceedings of the 10th International Water Distribution System Analysis conference (WDSA2008).
• Economou T, Bailey TC, Kapelan Z. (2008) A hidden semi-Markov model for occurrences of water pipe bursts, Utrecht, Netherlands, 7th - 11th Jul 2008, Proceedings of the 23rd International Workshop on Statistical Modelling, pages 216-220.
• Economou T, Kapelan Z, Bailey T. (2008) A Zero-Inflated Bayesian Model for the Prediction of Water Pipe Bursts, South Africa.

2007

• Economou T, Kapelan Z, Bailey TC. (2007) An Aggregated Hierarchical Bayesian Model for the Prediction of Pipe Failures, De Montfort University, Proceedings of CCWI2007 (Computing and Control for the Water Industry).
• Economou T, Bailey TC, Kapelan Z. (2007) Bayesian modelling of time aggregated water pipe bursts with a zero-inflated, non-homogeneous Poisson process, Barcelona, Spain, 2nd - 6th Jul 2007, Proceedings of 22nd International Workshop on Statistical Modelling.

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