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Professor Peter Congdon, BSc (Econ), MSc, PhD

Peter

Emeritus Professor in Quantitative Geography and Health Statistics

Email: p.congdon@qmul.ac.uk

Profile

I am a quantitative geographer with particular interests in geographic epidemiology, application of spatial statistical methods to area health and health survey data, and spatial demography. Since 2001 I have been a Research Professor in the School of Geography. I have authored a range of articles and books, including ‘Bayesian hierarchical models: with applications using R’ (CRC, 2019) and ‘Applied Bayesian Modelling’ (Wiley, 2014). My major projects recently have been development of health indicators (e.g. diabetes, obesity) for US micro areas (Zip Code Tracts), developing Scotland datazone population estimates using administrative datasets, and analysis of primary care health registers (Quality Outcomes Framework) to model neighbourhood psychosis inequalities by ethnicity.

Key Publications

  • Congdon P (2023) Psychosis prevalence in London neighbourhoods; A case study in spatial confounding. Spatial and Spatio-Temporal Epidemiology, 48, 100631
  • Congdon P (2023) The ethnic density effect as a contextual influence in ecological disease models: Establishing its quantitative expression, Health and Place, 83, 103083
  • M Gramatica, S Liverani, P Congdon (2023) Structure induced by a multiple membership transformation on the conditional autoregressive model, Bayesian Analysis, DOI: 10.1214/23-BA1370

  • Congdon, P (2019) Geographical Patterns in Drug-Related Mortality and Suicide: Investigating Commonalities in English Small Areas. Int. J. Environ. Res. Public Health 2019, 16(10), 1831; https://doi.org/10.3390/ijerph16101831

  • Congdon, P (2017) Variations in Obesity Rates between US Counties: Impacts of Activity Access, Food Environments, and Settlement Patterns. Int J Environ Res Public Health, 14(9). https://www.ncbi.nlm.nih.gov/pubmed/28880209

  • Congdon P (2017) Representing Spatial Dependence and Spatial Discontinuity in Ecological Epidemiology: a Scale Mixture Approach. Stochastic Environmental Research and Risk Assessment, 31(2): 291-304. http://link.springer.com/article/10.1007/s00477-016-1292-9

  • Congdon, P (2014) Applied Bayesian Modelling, 2nd edition, John Wiley

  • Jonker M, van Lenthe F, Congdon P et al (2012) Comparison of Bayesian random effects and traditional life expectancy estimations in small area applications, American Journal of Epidemiology, 176 (10): 929–37.

  • Congdon, P (2010) Applied Bayesian Hierarchical Methods, Chapman & Hall/CRC
  • Congdon, P (2010) Random effects models for migration attractivity and retentivity: a Bayesian methodology, J Roy Stat Soc Series A, 173 (4): 755–774

Professional Activities and Outreach

  • Elected Member, International Statistical Institute
  • Editorial Board (Spatial Statistics), Springer Handbook of Regional Science, 2019
  • Editorial Board of the International Journal of Environmental Research and Public Health
  • Editorial Board Member, Medicine (Kluwer)
  • Refereeing grant applications/project reviewing on behalf of ESRC, NHS Service Delivery and Organisation R&D Programme, Alberta Heritage Foundation for Medical Research, Arts and Humanities Research Board; Research Grants Council (Hong Kong); Health Research Council of New Zealand; ESRC-NWO Bilateral Research Scheme, Chief Scientist Office (Edinburgh) HSR Training Scheme.
  • Referee Panel ESRC/MRC Joint Studentship and Post-Doctoral Fellowship Scheme

Book Downloads (zip files):

Bayesian Hierarchical Models: With Applications Using R

Other downloads (zip files):

 

 

Teaching

Teaching: MSc International Health (Social Determinants of Health: Ecological Approaches)

Research

Research Interests:

I Spatial Statistics in Geographic Epidemiology
This strand of research considers application of statistical methods to analyse spatial variations in population mortality and chronic disease outcomes. This includes work to explain geographic variations in self-harm and suicide, to assess spatial clustering of disease, and to disease prevalence estimation for small areas. A particular aspect of this work is the use of Bayesian techniques.

Illustrative Outputs

II Methods for Public Health Needs Assessment
This work focuses on strategic analysis and health care profiles for small areas and GP practices in NE London, in collaboration with local public health departments. This work involves use of a variety of health indicators (mortality rates, hospital admission rates, population prevalence, etc.) to inform public health needs assessment. Research outputs include small area analysis of premature mortality using years of life lost indicators, and geographic interpolation methods to develop small area estimates of health indicators (such as the psychosis prevalence rate in outer North East London LSOAs) from the Quality Outcomes Framework dataset for GP practices.

Illustrative Outputs

  • Congdon P (2013) Interpolation between spatial frameworks: an application of process convolution to estimating neighbourhood disease prevalence. Stat Methods Med Res.
  • Congdon P (2013) Modelling small-area inequality in premature mortality using years of life lost rates. Journal of Geographical Systems, 15 (2): 149–167

III Small Area Demography

This group of projects includes development of small area life table methods (in collaboration with Department of Public Health, Erasmus MC) and investigating Bayesian techniques to produce small area population estimates using administrative datasets (funded by GRO Scotland). The former work illustrates the principle of borrowing strength (via Bayesian methods) to make life expectancy estimates for small areas, when conventional estimates may be subject to instability. The latter study, funded by GRO Scotland, investigated possible alternatives to Census based population estimates (known as the SAPE estimates) for 6505 Scotland datazones, using administrative datasets with comprehensive population coverage such as the NHSCR and DWP customer populations.

Illustrative Outputs

IV US Micro-Area Health
Health care profiles for US micro areas (Census 2000 and 2010 Zip Code Tracts) have been developed in collaboration with the National Minority Quality Forum (http://www.nmqf.org/). This has involved a variety of modelling techniques (multilevel, spatial) in the development of chronic health indicators, especially indicators of population prevalence (e.g. diabetes, obesity, cancer prevalence) or risk exposure (lead risk). The estimates are disaggregated by age group and ethnicity.

Illustrative Outputs:

 

Publications

Pubmed http://www.ncbi.nlm.nih.gov/pubmed/?term=congdon+p.

Google Scholar https://scholar.google.co.uk/citations?user=Ry7-4dUAAAAJ&hl=en

Congdon P (2024) Psychosis prevalence in London neighbourhoods; A case study in spatial confounding, Spatial and Spatio-temporal Epidemiology 48, 100631. https://www.sciencedirect.com/science/article/pii/S1877584523000680  Replication: https://figshare.com/account/home#/projects/200521

Ku B, Flores FJB, Congdon P, Yuan Q, Druss B (2024) The Association Between County-Level Mental Health Provider Shortage Areas and Suicide Rates in the United States During the COVID-19 Pandemic. General Hospital Psychiatry, 88

Congdon P (2024) Neighbourhood Health Inequalities between Ethnic Groups in England: an Application of Ecological Inference. https://link.springer.com/article/10.1007/s12061-024-09570-1. Applied Spatial Analysis and Policy, 17.

Congdon P (2023) The ethnic density effect as a contextual influence in ecological disease models: Establishing its quantitative expression, Health and Place, 83, 103083. https://www.sciencedirect.com/science/article/pii/S135382922300120X

M Gramatica, S Liverani, P Congdon (2023) Structure induced by a multiple membership transformation on the Conditional Autoregressive model, Bayesian Analysis, DOI: 10.1214/23-BA1370

P Congdon (2022) Measuring obesogenicity and assessing its impact on child obesity: A cross-sectional ecological study for England neighbourhoods.International Journal of Environmental Research and Public Health 19 (17), 10865

A Adin, P Congdon, G Santafe, M Ugarte (2022) Identifying extreme COVID-19 mortality risks in English small areas: a disease cluster approach. Stochastic Environmental Research and Risk Assessment 36(5)

P Congdon (2022) A Spatio-temporal Autoregressive Model for Monitoring and Predicting COVID Infection Rates, Journal of Geographical Systems 24,583–610

P Congdon (2022) A Model for Highly Fluctuating Spatio-temporal Infection Data, with Applications to the COVID Epidemic. 
International Journal of Environmental Research and Public Health.  https://www.mdpi.com/1660-4601/19/11/6669

S Curtis, N Cunningham, J Pearce, P Congdon, M Cherrie, S Atkinson (2021) Trajectories in mental health and socio-spatial conditions in a time of economic recovery and austerity: A longitudinal study in England 2011–17,Social Science and Medicine 270, 113654. https://pubmed.ncbi.nlm.nih.gov/33445118/

H Baptista, P Congdon, J Mendes, A Rodrigues, H Canhão, S Dias (2020) Disease mapping models for data with weak spatial dependence or spatial discontinuities. Epidemiologic Methods 9(1). https://www.degruyter.com/document/doi/10.1515/em-2019-0025/html
        
P Congdon (2021) Mid-Epidemic Forecasts of COVID-19 Cases and Deaths: A Bivariate Model applied to the UK. Interdisciplinary Perspectives on Infectious Diseases. https://www.hindawi.com/journals/ipid/2021/8847116/

P Congdon (2021) COVID-19 mortality in English neighborhoods: the relative role of socioeconomic and environmental factors,
J—Multidisciplinary Scientific Journal (MDPI), 4(2), 131-146. https://www.mdpi.com/2571-8800/4/2/11

M Gramatica, P Congdon, S Liverani (2021) Bayesian modelling for spatially misaligned health areal data: a multiple membership approach. Journal of the Royal Statistical Society: Series C (in press). DOI: 10.1111/rssc.12480. https://arxiv.org/abs/2004.05334

S Curtis, P Congdon, S Atkinson, R Corcoran, R MaGuire, T Peasgood (2020) Adverse conditions for wellbeing at the neighbourhood scale in England: Potential and challenges for operationalising indicators relevant to wellbeing in and of places. Wellbeing, Space and Society. https://www.sciencedirect.com/journal/wellbeing-space-and-society/vol/1.

Congdon, P (2020) Assessing Persistence in Spatial Clustering of Disease, with an Application to Drug Related Deaths in Scottish Neighbourhoods, Epidemiology, Biostatistics and Public Health, 16 (4). Accepted version [PDF 505KB] https://riviste.unimi.it/index.php/ebph/article/view/17158

Congdon P (2020) A Diabetes Risk Index for Small Areas in England, Health and Place, 63 (in press) Accepted Version (H&P) [PDF 1,160KB]

Congdon, P (2020) Modelling spatially varying coefficients via sparsity priors, Model Assisted Statistics and Applications, 15(2),99-109. MASA pdf [PDF 469KB]

P. Congdon (2020) The Upstream Environment for the Obesity Epidemic, contributed chapter in Obesity and Diabetes: New Surgical and Nonsurgical Approaches (2nd edition), Springer, ed J. Faintuch and S. Faintuch.Pre-publication [PDF 313KB]

Congdon P (2019) Bayesian Hierarchical Models with Applications using R, CRC/Chapman and Hall. https://www.crcpress.com/Bayesian-Hierarchical-Models-With-Applications-Using-R-Second-Edition/Congdon/p/book/9781498785754

Puckrein G, Walker D, Xu L, Congdon P, Gooch K (2019) The prevalence and forecasted prevalence of overactive bladder in the Medicare population, Clinical Medicine Insights: Urology. https://journals.sagepub.com/doi/full/10.1177/1179561119847464

S Curtis, P Congdon, et al (2019) Individual and local area factors associated with self-reported wellbeing, perceived social cohesion and sense of attachment to one’s community: analysis of the Understanding Society Survey. What Works Centre for Wellbeing and Durham Research Online. http://dro.dur.ac.uk/28433/

Congdon, P (2019) Geographical Patterns in Drug-Related Mortality and Suicide: Investigating Commonalities in English Small Areas. Int. J. Environ. Res. Public Health 2019, 16(10), 1831; https://doi.org/10.3390/ijerph16101831

Bagheri, N, Batterham, P, Salvador-Carulla L, Chen Y, Calear A, Page A, Congdon P (2019) Development of the Australian Neighbourhood Social Fragmentation Index and its Association with Spatial Variation in Depression across Communities, Social Psychiatry and Psychiatric Epidemiology, In Press, https://rdcu.be/bxhfI

Congdon P (2019) Obesity and Urban Environments, Int J Environ Res Public Health, 16(3), 464

Congdon, P (2019) Bayesian Models for Spatial Data, in: Handbook of Regional Science, Fischer, M, Nijkamp, P (eds.) Springer, 2nd edition.

Congdon P (2019) Spatial heterogeneity in Bayesian disease mapping, GeoJournal,  84: 1303–1316. https://link.springer.com/article/10.1007/s10708-018-9920-1

Zhao J, Luan J, Congdon P (2018) Bayesian Linear Mixed Model with Polygenic Effects, J Stat Software, 85(6) https://www.jstatsoft.org/article/view/v085i06

Congdon P (2018) Assessing Impacts on Mortality of Lifestyle Factors: Allowing for Model Uncertainty, International Journal of Statistics and Probability, 7, no. 2 (2018): 91.

Congdon, P (2017) Variations in Obesity Rates between US Counties: Impacts of Activity Access, Food Environments, and Settlement Patterns. Int J Environ Res Public Health, 14(9). https://www.ncbi.nlm.nih.gov/pubmed/28880209

Ferreira M, Congdon P, Edwards, Y (2017) Bayesian Confirmatory Analysis of Multiple Response Data. Applied Marketing Analytics, 3(1): 70-90

Congdon P (2017) Quantile regression for overdispersed count data: a hierarchical method. Journal of Statistical Distributions and Applications, 4:18 http://rdcu.be/x0eV

Congdon P (2017) Quantile Regression for Area Disease Counts: Bayesian Estimation using Generalized Poisson Regression, International Journal of Statistics in Medical Research 6 (3), 92-103

Jonker M, D`Ippolito, E, Eikemo, T, Congdon P (et al) (2017) The effect of regional politics on regional life expectancy in Italy (1980-2010), Scandinavian Journal of Public Health, 45(2):121-131

Congdon P (2017) Representing Spatial Dependence and Spatial Discontinuity in Ecological Epidemiology: a Scale Mixture Approach. Stochastic Environmental Research and Risk Assessment, 31(2): 291-304. http://link.springer.com/article/10.1007/s00477-016-1292-9

Congdon P (2016) Spatiotemporal Frameworks for Infectious Disease Diffusion and Epidemiology. Int J Environ Res Public Health. 13(12), 1261. doi: 10.3390/ijerph13121261. http://www.mdpi.com/1660-4601/13/12/1261

Congdon P (2016) Assessing Impacts on Unplanned Hospitalisations of Care Quality and Access Using a Structural Equation Method: With a Case Study of Diabetes, Int. J. Environ. Res. Public Health, 13(9), 870; doi:10.3390/ijerph13090870 http://www.mdpi.com/1660-4601/13/9/870

Congdon, P (2016) Area Variations in Multiple Morbidity using a Life Table Methodology. Health Services and Outcomes Research Methodology, 16(1): 58-74. http://link.springer.com/article/10.1007/s10742-015-0142-4/fulltext.html https://qmro.qmul.ac.uk/xmlui/handle/123456789/12227

Schofield, P, Das-Munshi, J, Mathur, R, Congdon, P, Hull, S (2016) Does depression diagnosis and antidepressant prescribing vary by location? Analysis of ethnic density associations using a large primary care dataset. Psychological Medicine, 46 (6): 1321-1329 https://qmro.qmul.ac.uk/xmlui/handle/123456789/12354

Congdon P (2016) A Local Join Counts Method for Spatial Clustering in Disease from Relative Risk Models, Communications in Statistics-Theory and Methods, 45, 3059-3075 https://qmro.qmul.ac.uk/xmlui/handle/123456789/12475

Congdon P (2016) Explaining Variations in Obesity and Inactivity between US Metropolitan Areas, GeoJournal, 81(2): 211-229

Congdon P (2015) Spatial variation in attributable risks, Spatial and Spatio-temporal Epidemiology, 12, 39-52 http://www.sciencedirect.com/science/article/pii/S1877584515000039

S. Andreon, P. Congdon (2014) The insignificant evolution of the richness-mass relation of galaxy clusters. Astronomy & Astrophysics, A&A 568, A23 (2014) DOI: 10.1051/0004-6361/201423616 http://www.aanda.org/articles/aa/pdf/2014/08/aa23616-14.pdf

Congdon P (2014) Modelling Changes in Small Area Disability Free Life Expectancy: Trends in London Wards between 2001 and 2011, Statistics in Medicine, 33(29), 5138-5150, http://onlinelibrary.wiley.com/doi/10.1002/sim.6298/abstract

Congdon, P (2014) Applied Bayesian Modelling, 2nd edition, John Wiley http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1119951518.html

http://www.amazon.co.uk/Applied-Bayesian-Modelling-Probability-Statistics-ebook/dp/B00LC0QUWY

Congdon P, Cai Q, Puckrein P, Xu L (2014) Predicting Risks of Increased Morbidity among Atrial Fibrillation Patients using Consumption Classes, International Journal of Statistics in Medical Research, 2014, 3, 203-214 http://www.lifescienceglobal.com/pms/index.php/ijsmr/article/view/2207

Congdon P (2014) Estimating Life Expectancy in Small Areas, with an Application to Recent Changes in Life Expectancy in US Counties. In: Mortality in an International Perspective, eds. J Anson, M Luy. Springer http://www.springer.com/social+sciences/population+studies/book/978-3-319-03028-9

Congdon P (2014) Modelling Changes in Arctic Sea Ice Cover: an Application of Generalized and Inflated Beta and Gamma Densities, Journal of Statistical Distributions and Applications 2014, 1:3 http://www.jsdajournal.com/content/1/1/3

Congdon P (2014) Interpolation between spatial frameworks: an application of process convolution to estimating neighbourhood disease prevalence. Stat Methods Med Res. 23(2):169-82 http://smm.sagepub.com/content/early/2012/05/02/0962280212447150.long

Congdon P (2014) Estimating life expectancies for US Small Areas: a regression framework, J Geog Systems 16, 1-18

Congdon P (2014) Bayesian Spatial Statistical Modelling. pp 1419-1434 in: Handbook of Regional Science, Fischer, M, Nijkamp, P (eds.) Springer

Congdon P (2013) Spatially Interpolated Disease Prevalence Estimation using Collateral Indicators of Morbidity and Ecological Risk, Int J Environ Res Public Health. 2013 Oct 14;10(10):5011-25. http://www.mdpi.com/1660-4601/10/10/5011

Congdon, P (2013) Forecasting Regional Demand for Acute Health Care, Chapter 14 in Patient Flow: Reducing Delay in Healthcare Delivery, 2nd edition, Springer http://www.springer.com/business+%26+management/operations+research/book/978-1-4614-9511-6

Congdon P (2013) A model for spatially varying crime rates in English Districts: the effects of social capital, fragmentation, deprivation and urbanicity, International Journal of Criminology and Sociology, 2 http://www.lifescienceglobal.com/home/cart?view=product&id=530

Jonker, M, Congdon P, van Lenthe F, Burdorf A, Mackenbach J (2013) Small-area health comparisons using health-adjusted life expectancy: a Bayesian random-effects approach, Health & Place http://www.sciencedirect.com/science/article/pii/S1353829213000634

Jonker M, van Lenthe F, Donkers B, Congdon P, Burdorf A, Mackenbach J (2013) The impact of nursing homes on small-area life expectancies. Health and Place, 19:25-32 http://www.sciencedirect.com/science/article/pii/S1353829212001669

Congdon P (2013) Assessing Univariate and Bivariate Spatial Clustering in Modelled Disease Risks. J Biomet Biostat 4:161. doi: http://dx.doi.org/10.4172/2155-6180.1000161

Congdon P (2013) Modelling small-area inequality in premature mortality using years of life lost rates. Journal of Geographical Systems, 15(2): 149-167 http://link.springer.com/article/10.1007/s10109-012-0167-y

Congdon P (2013) Assessing the impact of socioeconomic variables on small area variations in suicide outcomes in England., Int J Environ Res Public Health. 10(1):158-77. http://www.mdpi.com/1660-4601/10/1/158

Congdon, P (2012) A Model for Spatially Disaggregated Trends and Forecasts of Diabetes Prevalence, Journal of Data Science, 10(4), 597-617

Jonker M, van Lenthe F, Congdon P et al (2012) Comparison of Bayesian random effects and traditional life expectancy estimations in small area applications, American Journal of Epidemiology, 176(10):929-37. http://aje.oxfordjournals.org/content/176/10/929

Congdon, P (2012) Spatial health factors with selection among multiple causes: lung cancer in US counties, Communications in Statistics-Theory and Methods, 41, 1933-1953. http://dx.doi.org/10.1080/03610926.2010.551015

Congdon, P (2012) A Latent Variable Model for Suicide Risk in relation to Social Capital and Socio-economic Status. Soc Psychiatry Psychiatr Epidemiol. 47(8):1205-19. Epub 2011 Aug 28. http://www.springerlink.com/content/a7pm565485843432/

Congdon P, Lloyd C (2012) A spatial random effects model for interzone flows: commuting in Northern Ireland, Journal of Applied Statistics, 39, 199-213, http://www.tandfonline.com/doi/abs/10.1080/02664763.2011.580336

Congdon P (2011) Spatial path models with multiple indicators and multiple causes: mental health in US Counties, Spatial and Spatio-temporal Epidemiology, 2, 103-116 http://dx.doi.org/10.1016/j.sste.2011.03.003

Congdon P (2011) The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality. Urban Studies, 48, 2101-2122. http://dx.doi.org/10.1177/0042098010380961

Congdon, P (2011) Structural equation models for area health outcomes with model selection, Journal of Applied Statistics, 38: 745-767. http://dx.doi.org/10.1080/02664760903563692

Congdon P, Lloyd P (2011) Toxocara infection in the United States: the relevance of poverty, geography and demography as risk factors, and implications for estimating county prevalence, International Journal of Public Health 56, 15-24. http://dx.doi.org/10.1007/s00038-010-0143-6

Congdon, P (2011) Explaining the spatial pattern of suicide and self-harm rates: a case study of east and south east England, Applied Spatial Analysis and Policy, 4(1): 23-43, http://dx.doi.org/10.1007/s12061-009-9038-4

Congdon, P, Lloyd P (2010) Estimating small area diabetes prevalence in the US using the Behavioral Risk Factor Surveillance System, Journal of Data Science, 8(2), 235-252

Congdon, P (2010) Applied Bayesian Hierarchical Methods, Chapman & Hall/CRC http://www.crcpress.com/product/isbn/9781584887201

Congdon, P (2010) A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US , Int. J. Environ. Res. Public Health, 7(2), 333-352; http://dx.doi.org/10.3390/ijerph7020333

Congdon, P (2010) Estimating Prevalence of Coronary Heart Disease for Small Areas Using Collateral Indicators of Morbidity, Int. J. Environ. Res. Public Health, 7(1), 164-177; http://dx.doi.org/10.3390/ijerph7010164

Congdon, P (2010) Random effects models for migration attractivity and retentivity: a Bayesian methodology, J Roy Stat Soc Series A, 173(4): 755-774

Congdon P (2010) A spatial structural equation model with an application to area health needs. Journal of Statistical Computation and Simulation, 80(4), 401-412 http://dx.doi.org/10.1080/00949650802676300)

Congdon, P (2010) A multiple indicator, multiple cause method for representing social capital with an application to psychological distress. Journal of Geographical Systems, 12, pp 1-23, http://dx.doi.org/10.1007/s10109-009-0097-5

Congdon, P (2010) Assessing differential area mortality trends via Bayesian random effects. Communications in Statistics-Theory and Methods, 39, 2205-2230

LeSage J, Banerjee S, Fischer M, Congdon P (2009) Spatial statistics: methods, models & computation, Computational Statistics and Data Analysis, 53: 2781-2785. http://dx.doi.org/10.1016/j.csda.2008.11.001

Congdon, P (2009) Modelling the impact of socioeconomic structure on spatial health outcomes. Computational Statistics and Data Analysis 53: 3047-3056 http://dx.doi.org/10.1016/j.csda.2007.10.021

Congdon P (2009) A multilevel model for cardiovascular disease prevalence in the US and its application to micro area prevalence estimates, International Journal of Health Geographics http://www.ij-healthgeographics.com/content/8/1/6

Washington S, Congdon P, Karlaftis M, Mannering F (2009) Bayesian multinomial logit: theory and route choice example, Transportation Research Record, 2136, pp 28-36

Congdon P (2009) Life expectancies for small areas: a Bayesian random effects methodology, International Statistical Review, 77, 222-240 http://www3.interscience.wiley.com/journal/122457806/abstract

Congdon P (2009) Adaptive autoregressive priors for area and time structured mortality data. Journal of Statistical Planning and Inference, 139, 2870-2884. http://dx.doi.org/10.1016/j.jspi.2009.01.011

Curtis S, Congdon P, Almog M, Ellerman R (2009) County variation in use of inpatient and ambulatory psychiatric care in New York State 1999-2001: need and supply influences in a structural model, Health and Place 15(2):568-577 http://dx.doi.org/10.1016/j.healthplace.2008.09.009

Congdon P (2008) The need for psychiatric care in England: a spatial factor methodology. Journal of Geographical Systems 10 (3), 217-239 http://dx.doi.org/10.1007/s10109-008-0064-6

Congdon P (2008) A spatially adaptive conditional autoregressive prior for area health data, http://dx.doi.org/10.1016/j.stamet.2008.02.005 Statistical Methodology, 5, 552-563

Congdon P (2008) A bivariate frailty model for events with a permanent survivor fraction and non-monotonic hazards; with an application to age at first maternity, Computational Statistics and Data Analysis, 52 (9), 4346-4356 http://dx.doi.org/10.1016/j.csda.2008.02.017

Fagg, J, Curtis S, Clark C, Congdon, P, Stansfeld S (2008) Neighbourhood perceptions among inner city adolescents: relationships with their individual characteristics and with independently assessed neighbourhood conditions. Journal of Environmental Psychology, 28, 128-142 http://dx.doi.org/10.1016/j.jenvp.2007.10.004

Congdon, P (2008) Estimating the prevalence of coronary heart disease in local areas: integrating information from health surveys and area mortality, Health & Place, 14(1) 59-75

Congdon, P (2008) A spatial structural equation model for health outcomes. Journal of Statistical Planning and Inference 138 (7): 2090-2105 http://dx.doi.org/10.1016/j.jspi.2007.09.001

Congdon, P (2008) Indirect area estimates of disease prevalence: Bayesian evidence synthesis with an application to CHD. Journal of Data Science, 6 (1), 15-32, http://www.sinica.edu.tw/~jds/Content-v-6-1.html

Congdon, P (2008) Bayesian Statistics, in "Encyclopedia of Quantitative Risk Assessment" Wiley

Ghosh, S, Das, K, Congdon, P (2007) Analysis of marginally specified semi-nonparametric models for clustered binary data. Statistica Neerlandica 61 (3), 292-306. http://dx.doi.org/10.1111/j.1467-9574.2007.00355.x

Congdon, P (2007) A model for spatial variations in life expectancy; mortality in Chinese regions in 2000. International Journal of Health Geographics 2007, 6:16 http://dx.doi.org/10.1186/1476-072X-6-16

Congdon P, Almog M, Curtis S, Ellerman R (2007) A spatial structural equation modelling framework for health count responses. Statistics in Medicine 26 (29): 5267-5284, http://dx.doi.org/10.1002/sim.2921

Congdon, P (2007) Bayesian modeling of migration age structures. In "The Estimation of International Migration in Europe: Issues, Models and Assessment", Raymer, J, Willekens, F (eds). Wiley, Migration.pdf

Congdon, P (2007) Model weights for model choice and averaging, Statistical Methodology 4(2):143-157 http://www.sciencedirect.com/science/article/pii/S1572312706000190

Congdon, P (2007) Mixtures of spatial and unstructured effects for spatially discontinuous health outcomes. Computational Statistics and Data Analysis, 51, 3197-3212 http://dx.doi.org/10.1016/j.csda.2006.11.028

Congdon, P (2006) Modelling hospital activity: accounting for small area and primary care practice variation, Advances and Applications in Statistics, 6, 335-351

Congdon, P (2006) A model for geographical variation in health and total life expectancy, Demographic Research, 14, 157-178

http://www.demographic-research.org/volumes/vol14/9/

Congdon, P (2006) Modelling multiple hospital outcomes: the impact of small area and primary care practice variation. International Journal of Health Geographics, 5: 50. http://www.ij-healthgeographics.com/content/5/1/50

Congdon, P (2006) Bayesian modelling strategies for spatially varying regression coefficients: A multivariate perspective for multiple outcomes. Computational Statistics & Data Analysis, 51(5), pp 2586-2601,pdf http://dx.doi.org/10.1016/j.csda.2006.01.004

Congdon, P (2006) Bayesian Statistical Modelling, 2nd edition. Wiley http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470018755.html

Fagg, J, Curtis, S, Congdon, P, Stansfeld, S (2006) Psychological distress among adolescents, and its relationship to individual, family and area characteristics; evidence from East London, UK. Social Science & Medicine, 63, 636-48 http://dx.doi.org/10.1016/j.socscimed.2006.02.012

Congdon, P (2006) Estimating diabetes prevalence by small area in England. J Public Health, 28, 71-81,pdf http://dx.doi.org/10.1093/pubmed/fdi068

Congdon P (2006) Estimating population prevalence of psychiatric conditions by small area with applications to analysing outcome and referral variations. Health & Place, 12:465-78 http://dx.doi.org/10.1016/j.healthplace.2005.05.001

Congdon, P (2006) A spatio-temporal forecasting approach for health indicators, Journal of Data Science 4(4): 399-412

http://www.sinica.edu.tw/~jds/Content-v-4-4.html

Congdon, P (2006) A model framework for mortality and health data classified by age, area and time. Biometrics, 61, 269-278

Congdon, P (2006) Bayesian model comparison via parallel model output, Journal of Statistical Computation and Simulation, 76 (2), 149-165 http://dx.doi.org/10.1080/00949650412331320864

Congdon, P (2006) Forecasting Regional Demand for Acute Health Care, Chapter 10 in Patient Flow: Reducing Delay in Healthcare Delivery, Ed Randolph Hall, SpringerP.

Congdon, P (2006) Bayesian model choice based on Monte Carlo estimates of posterior model probabilities, Computational Statistics & Data Analysis, 50, 346-357 http://dx.doi.org/10.1016/j.csda.2004.08.001

Congdon, P (2006) A model for nonparametric spatially varying regression effects, Computational Statistics and Data Analysis, 50, 422-445 http://dx.doi.org/10.1016/j.csda.2004.08.008

Curtis, S, Copeland, A, Fagg, J, Congdon, P, Almog, M, Fitzpatrick, J (2006) The ecological relationship between deprivation, social isolation and rates of hospital admission for acute psychiatric care: a comparison of London and New York City. Health and Place, 12, 19-37

P. Congdon (2005) Bayesian Models for Categorical Data, Wiley

Congdon, P, Clarke, T (2005) Assessing intervention effects in a community based trial to reduce self-harm: a methodological case study, Public Health, 119, 1011-5.

Chapman J, Congdon P, Shaw S, Carter Y (2005) The geographical distribution of specialists in public health in the United Kingdom: Is capacity related to need? Public Health, 119, 639-646

P. Congdon (2005) MCMC and Bayesian Methods, In: Encyclopedia of Statistics in the Behavioural Sciences, Wiley

Mitra S, Washington S, Congdon P, Van Schalkwyk, I. (2005) A Bayesian estimation approach for modeling overdispersion in crash data. In Transportation Research Board, 84th Annual Meeting Proceedings. TRB, National Research Council, Washington, DC

Congdon, P, Southall, H (2005) Trends in inequality in infant mortality in the North of England, 1921-1973 and their association with urban and social structure, J Roy Stat Soc Series A, 168, 679-700

Chapman J, Shaw S, Congdon P, Carter Y, Abbott S, Petchey R.(2004) Specialist public health capacity in the UK: working in the new primary care organisations. Public Health 119, 22-31 http://www.publichealthjrnl.com/article/S0033-3506(04)00148-9/references

P.Congdon (2005) Bayesian predictive model comparison via parallel sampling, Computational Statistics and Data Analysis, 48(4), 735-753 http://dx.doi.org/10.1016/j.csda.2004.03.016

Fagg, J, Curtis, S, Stansfeld, S, Congdon, P (2004) Neighbourhood influences on adolescent health in East London. In Sagan, I. and Czepczinski, M. (eds.), Featuring the Quality of Urban Life in Contemporary Cities of Eastern and Western Europe, Bogucki Wydawnictwo Naukowe, Gdansk-Poznan, 117-124

P.Congdon (2004) Contextual effects: index construction and technique, International Journal of Epidemiology, 33, 741 742

Campos, R, Congdon, P, et al (2004) Locality level mortality and socioeconomic change in Britain since 1920: first steps towards an analysis of infant mortality variation, In P. Boyle, S. Curtis, A. Gatrell, E. Graham, E. Moore (eds.) The Geography of Health Inequalities in the Developed World, Aldershot: Ashgate

Congdon, P (2004) Modelling trends and inequality in small area mortality, J Applied Statistics, 31, 6, 603-622

Congdon, P, Southall, H (2004) Small area variations in infant mortality in England and Wales in the inter-war period and their link with socio-economic factors, Health and Place, 10, 363-382 http://dx.doi.org/10.1016/j.healthplace.2003.05.001

Almog, M, Curtis, S, Copeland, A, Congdon, P (2004) Geographical variation in acute psychiatric admissions within New York City 1990-2000: growing inequalities in service use?, Social Science and Medicine, 59,361-376

Congdon, P (2003) A multivariate model for spatio-temporal health outcomes with an application to suicide mortality, Geographical Analysis, 36, 234-258

Curtis, S, Southall, H, Congdon, P, Dodgeon, B (2003) Analysis of the Longitudinal Study sample in England using new data on area of residence in childhood. Social Science and Medicine, 57(12)

P.Congdon (2003) Modelling spatially varying impacts of socioeconomic predictors on mortality outcomes, Journal of Geographical Systems, 5 (20, 161-184

P.Congdon (2003) Applied Bayesian Models, John Wiley http://www.wiley.com/WileyCDA/WileyTitle/productCd-0471486957.html

P.Congdon (2002) A life table approach to small area health need profiling, Statistical Modelling, 2,1-26

P.Congdon (2002) A model for mental health needs and resourcing in small geographic areas: a multivariate spatial perspective, Geographical Analysis, 34, 2, 168-186

P.Congdon (2001) The development of gravity models for hospital patient flows under system change: a Bayesian modelling approach, Health Care Management Science, 4, 289-304

P. Congdon, R. Campos, S. Curtis, H. Southall, I. Gregory, I. Jones (2001) Quantifying and explaining changes in geographical inequality of infant mortality in England and Wales since the 1890s, International Journal of Population Geography, 7, 35-51

P. Congdon (2001) Health status and healthy life measures for population health need assessment: modelling variability and uncertainty, Health and Place, 7(1):13-25. http://dx.doi.org/10.1016/S1353-8292(00)00034-4

R. Fowler, P. Congdon and S. Hamilton (2001) Assessing health status and outcomes in older people attending a geriatric day hospital, Public Health, 114, 440-44

P. Congdon (2001) Monitoring suicide mortality: a Bayesian approach, European J. of Population , 16, 3,1-34

P.Congdon (2001) Bayesian Statistical Modelling, John WileyP.Congdon (2001) Predicting adverse infant health outcomes using routine screening variables: modelling the impact of interdependent risk factors, J. Applied Statistics, 28(2), 183-197

P. Congdon (2000) A Bayesian approach to prediction using the gravity model, with an application to patient flow modelling, Geographical Analysis, 32 (3) ,205-224

P Congdon, N Best (2000) Small area variation in hospital admission rates: adjusting for referral and provider variation, J. Roy Stat Soc, Series C, 49(2), 207-226

P. Congdon, (1999) Primary Care Needs Assessment and Resourcing: Complementary Practice and Geographic Perspectives, Health and Place, 5, 1, 59-82

P. Congdon, A. Smith, C. Dean (1998) Assessing psychiatric morbidity from a community register: methods for Bayesian adjustment, Urban Studies, 35 (12), 2323-2352

P. Congdon (1998) A multi-level model for infant health outcomes: maternal risk factors and geographic variation, The Statistician, 47 (1), 159-182

P. Congdon (1997) Multilevel and clustering analysis of health outcomes in small areas, European J.of Population, 13, 305-338

P.Congdon (1997) Realignment of suicide differentials in London: an examination of trends in the 1980s and 1990s, The London Journal,22, 160-174

P.Congdon (1997) Bayesian models for the spatial structure of rare health outcomes: a study of suicide using the BUGS program, Journal of Health and Place, 3(4), 229-247 http://dx.doi.org/10.1016/S1353-8292(97)00017-8

P.Congdon, S.Shouls,S.Curtis (1997) A multi-level perspective on small area health and mortality: a case study of England and Wales, International Journal of Population Geography,3, 243-263.

S. Hamilton, P. Congdon, R. Fowler (1996) Measuring outcomes of care in a day hospital setting, Elderly Care, 8(3), 14-17

P. Congdon (1996) General linear gravity models for the impact of casualty unit closures, Urban Studies, 33, 1707-1728S.

Shouls, P.Congdon, S.Curtis (1996) Modelling inequality in reported long term illness: combining individual and area characteristics, J. Epid. Comm. Health, 50, 366-376

S.Shouls, P.Congdon, S.Curtis (1996) Geographic variation in health: the development of a relevant area typology for SAR districts, Health and Place, 2(3), 139-155 http://dx.doi.org/10.1016/1353-8292(96)00002-0

P.Congdon (1996) The incidence of suicide and parasuicide: a small area study, Urban Studies, 33, 137-158

P.Congdon (1996) The epidemiology of suicide in London, J. Royal. Stat.Soc, Ser A, 159, 515-533

P.Congdon (1995) Life table analysis for areas using vital register data, Eur J Popul 11 (4): 343-369

P.Congdon (1995) The impact of area context on long term illness and premature mortality: an illustration of multi-level analysis, Regional Studies, 29, 327-344

P.Congdon (1995) Localities for epidemiological monitoring and health policy, Urban Studies, 32(7), 1175-1198

P.Congdon (1995) Socio-economic structure and health in London, Urban Studies, 32 (3), 523-549

P.Congdon (1995) Micro and aggregate perspectives on life table heterogeneity: an empirical investigation of area mortality, Social Science Research, 24, 136-166

P.Congdon (1995) Modelling frailty in area mortality, Statistics in Medicine, 14, 1859-1874P.Congdon (1994) Spatio-temporal analysis of area mortality, The Statistician, 43(4), 513-528

P.Congdon (1994) Analyzing mortality in London: life tables with frailty, The Statistician, 43(2), 277-308

P.Congdon (1993) Approaches to modelling overdispersion in the analysis of migration, Environment and Planning, 25, pp 1481-1510

P.Congdon (1993) Statistical graduation in local demographic analysis and projections, Journal of the Royal Statistical Society, Series A, 156(2), 237-270

P.Congdon, McCallum, I. (1992) A demo-educational model for forecasting school rolls for localities, The Statistician (JRSS Series D) , 41(5), pp 573-590

P.Congdon (1992) Aspects of the general linear modelling of migration, The Statistician, 41, pp 133-153

P. Congdon (1992) Time series fertility models and structural interpretation, The Journal of Cities and Regions (ISI/SCORUS), 3, 33-60

P.Congdon (1992) Multiregional demographic projections in practice: a metropolitan example, Regional Studies 26(2), pp 177-191

Champion, A, Congdon, P. (1992) Migration trends in the South of England: decentralisation from London and the validity of the Greater South East in Migration Processes and Patterns, Vol 2, eds. J. Stillwell et al, Belhaven Press

P.Congdon (1992) The potential of the Longitudinal Study for migration studies, Update (Longitudinal Study Newsletter), 1, pp 11-14

Stillwell, J. and Congdon, P (1992) Migration Modelling: Macro and Micro Perspectives, Belhaven Press& John Wiley

P.Congdon (1991) An application of general linear modelling to migration in London and South East England, in Migration Modelling: Macro and Micro Perspectives Belhaven Press & Wiley

P.Congdon (1991) Spatio-temporal models for small area social indicators, Papers in Regional Science, 70(3), pp 243-26

P.Congdon (1991) Metropolitan social change and the outer suburbs: a case study of London, Espace,Populations, Societes, 1991-3 , pp 381-394

P.Congdon (1990) Issues in the Analysis of Small Area Mortality, Urban Studies, 27(4), pp 519-536

P.Congdon (1990) Graduation of fertility schedules: an analysis of fertility patterns in London in the 1980s and an application to fertility forecasts, Regional Studies, 24(4),pp 311-326

P.Congdon (1990) Small area population and social monitoring: the London case, BURISA Newsletter 95, pp 5-9

P.Congdon (1990) Demographic change for districts and small areas, ASLIB Social Sciences Information Group Newsletter, 8(1), pp 14-17

P.Congdon (1990) The Analysis of Small Area Social Change, Progress in Planning, 34(3)

Shepherd, J, Congdon, P (1990) Small Town England: an Investigation of Population Change among Small and Medium Sized Urban Areas,1971-81, Progress in Planning, 33(1)

P.Congdon (1989) An analysis of population and social change in London wards in the 1980s, Transactions of the Institute of British Geographers, 14(4), pp 478-491

P.Congdon (1989) Modelling migration flows between areas: an example for London using the Census and OPCS Longitudinal Study. Regional Studies, 23(2), pp 87-103

P.Congdon, A. Champion (1989) Recent population shifts in South East England and their relevance to the counterurbanisation debate, in Growth and Change in a Core Region, London Papers in Regional Science, Volume 20

Breheny, M, Congdon, P. (1989) Growth and Change in a Core Region: the Case of South East England, London Papers in Regional Science, Volume 20, Pion, London

P.Congdon, P. Batey (1989) eds Advances in Regional Demography: Information, Forecasts, Models, John Wiley

P.Congdon (1989) Fertility forecasts and structural interpretations: an application to Greater London and England and Wales, Espace, Populations, Societes, 1989-2, pp 177-188

P.Congdon (1989) Trends and structure in London's migration and their relation to employment and housing markets, in Advances in Regional Demography, Belhaven Press

P.Congdon (1989) Gender and space in London in the 1980s, Espace, Populations, Societes, 1989-1, pp 27-42

P.Congdon (1988) Deprivation in London wards: mortality and unemployment trends in the 1980s, The Statistician, 37(4/5), pp 451-472

P.Congdon (1988) Occupational mobility and labour market structure: a multivariate Markov model, Scottish Journal of Political Economy, pp 208-226

A. Champion, P.Congdon (1988) Recent trends in Greater London's population, Population Trends, 53, pp 7-17

P.Congdon, J. Shepherd (1988) Components of social change in urban areas, Urban Studies, 25, pp 173-189

P.Congdon (1988) The interdependence of geographic migration with job and housing mobility in London, Regional Studies, 22, pp 81-93

P.Congdon (1988) Heterogeneity and timing effects in occupational mobility in the Irish Republic, in M.Uncles (ed.), Longitudinal Data Analysis: Models and Applications. Pion, London

A. Champion, P.Congdon (1987) An analysis of the recovery of London's population change rate, Built Environment, 13(4), pp193-211

P.Congdon, J.Shepherd (1986) Modelling population changes in small English urban areas, Environment and Planning, 18A, pp1297-1322

P.Congdon, J.Shepherd (1985) Small area social change in Greater London: a regression approach to measurement, Journal of Economic and Social Measurement, 13(1), pp 49-68

P.Congdon (1985) Heterogeneity and timing effects in occupational mobility: a general model, Oxford Bulletin of Economics and Statistics, 47(4), pp 347-369

P.Congdon (1983) A model for the interaction of migration and commuting, Urban Studies, 20, pp 185-195

P.Congdon (1980) Forecasting births in Greater London: an application of the Easterlin hypothesis, Population Studies, 34, pp 267-278

Supervision

PhD Students

  • Alison Copeland. Socioeconomic and Community Influences on Potentially Avoidable Emergency Admissions to Hospital for Older People in London
  • Marcel Jonker (Erasmus University). Summary measures and determinants of small-area population health (External Advisor)
  • Michael Grayer. Analysis of Variation in Small-area Life Expectancy within London
  • Marco Gramatica, Bayesian Spatial Modelling of Misaligned Data (jointly with School of Mathematical Sciences)

 

Public Engagement

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