Book

• Spatio – Temporal Methods in Environmental Epidemiology with R (2023). Gavin Shaddick, James V. Zidek and Alexandra M. Schmidt. Second Edition, CRC Press.

Journals

• A nationwide joint spatial modelling of simultaneous epidemics of dengue, chikungunya, and Zika in Colombia. Laís P. Freitas, Mabel Carabli, Alexandra M. Schmidt, J. E. S. Flórez, M. A. Monsalve, C. Garcı́a-Balaguera, B. N. Restrepo, G. I. Jaramillo-Ramirez, and K. Zinszer (2025). BMC Infectious Diseases, 25, 406.

• Conditional forecasting of bus travel time and passenger occupancy with Bayesian Markov regime-switching vector autoregression, Xiaoxu Chen, Zhanhong Cheng, Alexandra M. Schmidt, Lijun Sun (2025). Transportation Research Part B: Methodological, 192, 103147.

• A Bayesian hierarchical model for disease mapping that accounts for scaling and heavy-tailed latent effects, Victoire Michal, Alexandra M. Schmidt, Laís P. Freitas, Oswaldo G. Cruz (2025). Statistical Methods in Medical Research, 34(2):307–321.

• A three-state coupled Markov switching model for COVID-19 outbreaks across Quebec based on hospital admissions. Dirk Douwes-Schultz, Alexandra M. Schmidt, Yannan Shen, David L. Buckeridge (2025). The Annals of Applied Statistics, 19(1): 371-396.

• A joint temporal model for hospitalizations and ICU admissions due to COVID-19 in Quebec, Mariana Carmona-Baez, Alexandra M. Schmidt, Shirin Golchi, David L. Buckeridge (2024). Stat, 13: e70000.

• Mapping socio-economic status using mixed data: a hierarchical Bayesian approach, Gabrielle Virgili-Gervais, Alexandra M. Schmidt, Honor Bixby, Alicia Cavanaugh, George Owusu, Samuel Agyei-Mensah, Brian Robinson, and Jill Baumgartner (2024). Journal of the Royal Statistical Society Series A, qnae080.

• Model-based prediction for small domains using covariates: a comparison of four methods, Victoire Michal, Jon Wakefield, Alexandra M. Schmidt, Alicia Cavanaugh, Brian Robinson, and Jill Baumgartner (2024). Journal of Survey Statistics and Methodology, smae032.

• A comparison of Bayesian approximation methods for analyzing large spatial skewed data, Paritosh Kumar Roy and Alexandra M. Schmidt (2024). Journal of Agricultural, Biological and Environmental Statistics.

• A Bayesian Non-Stationary Heteroskedastic Time Series Model for Multivariate Critical Care Data, Zayd Omar, David A. Stephens, Alexandra M. Schmidt and David Buckeridge (2024). Statistics in Medicine, 43(20), 3958-3974.

• Zika emergence, persistence, and transmission rate in Colombia: a nationwide application of a space-time Markov switching model, Laís P. Freitas, Dirk Douwes-Schultz, Alexandra M. Schmidt, Brayan Ávila Monsalve, Jorge Emilio Salazar Flórez, César García-Balaguera, Berta N. Restrepo, Gloria I. Jaramillo-Ramirez, Mabel Carabali, and Kate Zinszer (2024). Scientific Reports, 14, 10003.

• Modelling left-censored skewed spatial processes: the case of arsenic drinking water contamination, Qi Zhang, Alexandra M. Schmidt and Yogendra P. Chaubey (2024). Spatial Statistics, 59, 100816.

• Strangers in a strange land: Mapping household and neighbourhood associations with improved wellbeing outcomes in Accra, Ghana, Alicia C. Cavanaugh, J. C. Baumgartner, H. Bixby, Alexandra M. Schmidt, S. Agyei-Mensah, S. K. Annim, J. Anum, R. Arku, J. Bennett, F. Berkhout, M. Ezzati, S. E. Mintah, G. Owusu, J. Doku Tetteh, B. E. Robinson (2023), Cities, 143, 104584.

• Bayesian modeling of dynamic behavioral change during an epidemic, Caitlin Ward, Rob Deardon and Alexandra M. Schmidt (2023). Infectious Disease Modelling, 8(4), 947–963.

• Modelling temporally misaligned data across space: the case of total pollen concentration in Toronto, Sara Zapata-Marin, Alexandra M. Schmidt, Scott Weichenthal and Eric Lavigne (2023). Environmetrics, 34(8), e2820.

• The impact of directly observed therapy on the efficacy of Tuberculosis treatment: A Bayesian multilevel approach, Widemberg S. Nobre, Alexandra M. Schmidt, Erica E. M. Moodie and David A. Stephens (2023). Journal of the Royal Statistical Society, Series C: Applied Statistics, 72 (4), 889–911.

• Causal inference under mis-specification: adjustment based on the propensity score (with Discussion), David A. Stephens, Widemberg S. Nobre, Erica E. M. Moodie and Alexandra M. Schmidt (2023). Bayesian Analysis, 18(2): 639–694.

• Identifying deprived “slum” neighbourhoods in the Greater Accra Metropolitan Area of Ghana using census and remote sensing data, Robert MacTavis, Honor Bixby, Alicia Cavanaugh, Samuel Agyei-Mensah, Ayaga Bawah, George Owusu, Majid Ezzati, Raphael Arku, Brian Robinson, Alexandra M. Schmidt and Jill Baumgartner (2023). World Development, 167, 106253.

• On-line warning system for pipe burst using Bayesian dynamic linear models, Renato Henriques-Silva, Sophie Duchesne, Nicolas F. St-Gelais, Naysan Saran, Alexandra M. Schmidt (2023). Water Resources Research, 59 (4), e2021WR031745.

• Dynamical non-Gaussian modelling of spatial processes, Thaís C. O. Fonseca, Viviana G. R. Lobo and Alexandra M. Schmidt (2023). Journal of the Royal Statistical Society, Series C: Applied Statistics, 72, (1), 76–103.

• Spatial modelling of ambient concentrations of volatile organic compounds in Montreal, Canada, Sara Zapata-Marin, Alexandra M. Schmidt, Dan Crouse, Vikki Ho, France Labrèche, Eric Lavigne, Marie-Élise Parent and Mark S. Goldberg (2022). Environmental Epidemiology, 6 (5), p e226.

• A process convolution model for crash count data on a network,  Hassan Rezaee, Alexandra M. Schmidt, Joshua Stipancic and Aurélie Labbe (2022). Accident Analysis and Prevention, 14;177:106823.

• Extended Bayesian endemic–epidemic models to incorporate mobility data into COVID-19 forecasting, Dirk Douwes-Schultz, Shuo Sun, Alexandra M. Schmidt and Erica E. M. Moodie (2022). Canadian Journal of Statistics, 50, 713-733.

• Estimating the lagged effect of price discounting: a time-series study on sugar sweetened beverage purchasing in a supermarket, Hiroshi Mamiya, Alexandra M. Schmidt, Erica E. M. Moodie and David L. Buckeridge (2022). BMC Public Health, 22, 1502.

• Revisiting Transfer Functions: Learning About a Lagged Exposure-Outcome Association in Time-Series Data, Hiroshi Mamiya, Alexandra M. Schmidt, Erica E. M. Moodie and David L. Buckeridge (2022). International Journal of Public Health, 11; 67:1604841.

• A Poisson-multinomial spatial model for simultaneous outbreaks with application to arboviral diseases, Alexandra M. Schmidt, Laís P. Freitas, Oswaldo G. Cruz and Marilia S. Carvalho (2022). Statistical Methods in Medical Research, 31 (8), 1590–1602.

• A joint hierarchical model for the number of cases and deaths due to COVID-19 across the boroughs of Montreal, Victoire Michal, Leo Vanciu and Alexandra M. Schmidt (2022). Spatial and Spatio-Temporal Epidemiology, 42, 100518.

• Zero-state coupled Markov switching count models for spatio-temporal infectious disease spread, Dirk Douwes-Schultz and Alexandra M. Schmidt (2022). Journal of the Royal Statistical Society, Series C, 71(3), 589–612.

• A joint spatial marked point process model for dengue and severe dengue in Medellin, Colombia, Mabel Carabali, Alexandra M. Schmidt, Berta N. Restrepo and Jay S. Kaufman (2022). Spatial and Spatio-Temporal Epidemiology, 41, 100495.

• Socioeconomic factors and bacillary dysentery risk in Jiangsu Province, China: a spatial investigation using Bayesian hierarchical models, Sabrina Li, Alexandra M. Schmidt and Susan J. Elliot (2022). International Journal of Environmental and Health Research, 32(1), 220-231.

• Quantifying within-city inequalities in child mortality across neighbourhoods in Accra, Ghana: A Bayesian spatial analysis, Honor Bixby, James E. Bennett, Ayaga Agula Bawah, Raphael E. Arku, Alexandra M. Schmidt, Brian E. Robinson, Samuel Agyei Mensah, George Owusu, Samilia E. Mintah, Jacqueline D. Anum, Majid Ezzati, and Jill Baumgartner (2022). BMJ Open, 12, 1, e054030.

• Within city spatiotemporal variation of pollen concentration in the city of Toronto, Canada, Sara Zapata-Marin, Alexandra M. Schmidt, Scott Weichenthal, Daniel S.W.Katz, Tim Takaro, Jeffrey Brooke, Eric Lavigne (2022). Environment Research, 206, 112566.

• Generating Community Measures of Food Purchasing Activities Using Store-Level Electronic Grocery Transaction Records: An Ecological Study in Montreal, Canada, Mamiya, H., Schmidt, A. M., Moodie, E. M., Ma, Y., and Buckeridge, D. L. (2021). Public Health Nutrition, 24(17), 5616-5628.

• Spatio-temporal modelling of the first Chikungunya epidemic in an intra-urban setting: the role of socioeconomic status, environment and temperature, Laís P. Freitas, Alexandra M. Schmidt, William Cossich, Oswaldo G. Cruz, and Marilia S. Carvalho (2021). PLOS Neglected Tropical Diseases, 15(6): e0009537.

• Estimating an individual-level deprivation index for HIV/HCV coinfected persons in Canada, Adam Palayew, Alexandra M. Schmidt, Sahar Saeed, Curtis L Cooper, Alexander Wong, Valérie Martel-Laferrière, Sharon Walmsley, Joseph Cox, and Marina B. Klein (2021). PLOS ONE 16(4): e0249836.

• Price discounting as a hidden risk factor of energy drink consumption, Hiroshi Mamiya, Erica E. M. Moodie, Alexandra M. Schmidt, Yu Ma, and David Buckeridge (2021). Canadian Journal of Public Health, 112, 638–646.

• Importation of SARS-CoV-2 following the semaine de relâche and Québec’s COVID-19 burden - a mathematical modeling study, A. Godin, Y. Xia, D.L. Buckeridge, S. Mishra, D. Douwes-Schultz, Y. Shen, M. Lavigne, M. Drolet, A.M. Schmidt, M. Brisson and M. Maheu-Giroux (2021). International Journal of Infectious Diseases, 102, 254–259.

• On the effects of spatial confounding in hierarchical models, Widemberg S. Nobre, Alexandra M. Schmidt and João B. M. Pereira (2021). International Statistical Review, 89, 302–322.

• Flexible spatial covariance functions, Alexandra M. Schmidt and Peter Guttorp (2020). Spatial Statistics - Special Issue on Frontiers in Spatial Research, 37, 100416.

• Spatial confounding in hurdle multilevel beta models: the case of the Brazilian Mathematical Olympics for public schools, João B. M. Pereira, Widemberg S. Nobre, Igor F. L. Silva and Alexandra M. Schmidt (2020). Journal of the Royal Statistical Society, Series A, 183, 1051–1073.

• Fluoroquinolone use and seasonal patterns of ciprofloxacin resistance in community-acquired urinary Escherichia coli in a large urban center, Jean-Paul R Soucy, Alexandra M. Schmidt, Caroline Quach and David L Buckeridge (2020). American Journal of Epidemiology, 189, 215–223.

• Longitudinal evaluation of a household energy package on blood pressure, central hemodynamics, and arterial stiffness in China, Sierra N. Clark, Alexandra M. Schmidt, Ellison M. Carter, James J. Schauer, Xudong Yang, Majid Ezzati, Stella S. Daskalopoulou and Jill Baumgartner (2019). Environmental Research, 177, 108592.

• An area-level indicator of latent soda demand: Spatial statistical modeling of grocery store transaction data to characterize the nutritional landscape in Montreal, Canada, Hiroshi Mamiya, Alexandra M. Schmidt, Erica E. M. Moodie, Yu Ma and David L. Buckeridge (2019). American Journal of Epidemiology, 188, 1713–1722.

• Joint modelling of resistance to six antimicrobials in urinary Escherichia coli isolates in Quebec, Canada, Jean-Paul R Soucy, Alexandra M. Schmidt, Charles Frenette, Patrick Dolcé, Alexandre A Boudreault, David L Buckeridge and Caroline Quach (2019). Antimicrobial Agents and Chemotherapy, 63, e02531-18.

• Bayesian estimation of the average treatment effect on the treated using inverse weighting, Estelina S. Capistrano, Erica E. M. Moodie and Alexandra M. Schmidt (2019). Statistics in Medicine, 38: 2447-2466.

• Healthcare-associated bloodstream infection trends under a provincial surveillance program, Iman Fakih, Élise Fortin, Marc-André Smith, Alex Carignan, Claude Tremblay, Jasmin Villeneuve, Danielle Moisan, Charles Frenette, Caroline Quach for SPIN-BACTOT and Alexandra M. Schmidt (2019). Infection Control & Hospital Epidemiology, 40, 307–313.

• Accounting for covariate information in the scale component of spatio-temporal mixing models, Renata S. Bueno, Thaís C. O . Fonseca and Alexandra M. Schmidt (2017). Spatial Statistics, 22, 196-218.

• Rejoinder to the Discussion of Genton and Hering, and Huerta and Stroud on Spatio-temporal models for skewed processes, Alexandra M. Schmidt, Kelly Gonçalves and Patrícia L. Velozo (2017). Environmetrics, 28:e2411.

• Spatio-temporal models for skewed processes, Alexandra M. Schmidt, Kelly Gonçalves and Patrícia L. Velozo (2017). Environmetrics (with discussion), 28:e2411.

• A Hierarchical Mixture Beta Dynamic Model of School Performance in the Brazilian Mathematical Olympiads for Public Schools, Alexandra M. Schmidt, Caroline P. de Moraes and Helio S. Migon (2017) (Invited by the Editor-in-Chief). Chilean Journal of Statistics, 8, 3-24.

• A nonlinear population Monte Carlo scheme for the Bayesian estimation of parameters of alpha-stable distributions, Eugenia Koblents, Joaquín Míguez, Marco A. Rodríguez and Alexandra M. Schmidt (2016). Computational Statistics and Data Analysis, 95, 57-74.

• Population counts along elliptical habitat contours: hierarchical modelling using Poisson-lognormal mixtures with nonstationary spatial structure, Alexandra M. Schmidt, Marco A. Rodríguez and Estelina S. Capistrano (with Supplementary Material) (2015). Annals of Applied Statistics, 9, 1372-1393.

• Modelling categorized levels of precipitation, Patricia L. Velozo, Mariane B. Alves and Alexandra M. Schmidt (2014). Brazilian Journal of Probability and Statistics, 28, 2, 190-208.

• Accounting for spatially varying directional effects in spatial covariance structures, Joaquim H. Vianna Neto, Alexandra M. Schmidt and Peter Guttorp (2014). Journal of the Royal Statistical Society, Series C (Applied Statistics), 63, 1, 102-122.

• An efficient sampling scheme for dynamic generalized models, Helio S. Migon, Alexandra M. Schmidt, Romy R. Ravines and João B. M. Pereira (2013). Computational Statistics, 28, 2267-2293.

• A hierarchical model for aggregated functional data, Ronaldo Dias, Nancy L. Garcia and Alexandra M. Schmidt (2013). Technometrics, 55, 321-334.

• Covariance structure of spatial and spatio-temporal processes, Peter Guttorp and Alexandra M. Schmidt (2013). WIREs Computational Statistics, 5, 279-287

• Measuring the vulnerability of the Uruguayan population to vector-borne diseases via spatially hierarchical factor models, Hedibert F.Lopes, Alexandra M. Schmidt, Esther Salazar, Mariana Gómez and Marcel Achcar (2012). Annals of Applied Statistics, 6, 1, 284-303.

• Evolutionary Markov chain Monte Carlo algorithms for optimal monitoring network designs, Ramiro Ruiz C., Marco A. R. Ferreira and Alexandra M. Schmidt (2012). Statistical Methodology, 9, 185-194.

• A class of covariate-dependent spatiotemporal covariance functions, Brian J. Reich, Jo Eidvisk, Michele Guindani, Amy J. Nail and Alexandra M. Schmidt (2011). Annals of Applied Statistics, 5 (4), 2425–2447.

• Spatially varying autoregressive processes, Aline A. Nobre, Bruno Sansó and Alexandra M. Schmidt (2011). Technometrics, 53 (3), 310–321

• Considering covariates in the covariance structure of spatial processes, Alexandra M. Schmidt, Peter Guttorp and Anthony O’Hagan (2011). Environmetrics, 22, 487-500.

• Modelling time series of counts in epidemiology Alexandra M. Schmidt and João Batista M. Pereira (2011). International Statistical Review, 79, 48-69.

• Stochastic search algorithms for optimal monitoring network designs, Ramiro Ruiz C., Marco A. R. Ferreira and Alexandra M. Schmidt (2010). Environmetrics, 21, 102-112.

• Modelling zero-inflated spatio-temporal processes, Marcus Vinicius Fernandes, Alexandra M. Schmidt and Helio S. Migon (2009). Statistical Modelling, 9(1), 3-25

• Spatial stochastic frontier models: accounting for unobserved local determinants of inefficiency, Alexandra M. Schmidt, Ajax R. B. Moreira, Steven M. Helfand, and Thais C. O. Fonseca (2009). Journal of Productivity Analysis, 31, 101-112

• Investigating the sensitivity of Gaussian processes to the choice of their correlation function and prior specifications, Alexandra M. Schmidt, Ma. de Fátima da G. Conceição and Guido A. Moreira (2008). Journal of Statistical Computation and Simulation, 78, 8, 681-699.

• Bayesian Spatio-temporal models based on discrete convolutions, Bruno Sansó, Alexandra M. Schmidt and Aline A. Nobre (2008). Canadian Journal of Statistics, 36, 239-258.

• A joint model for rainfall-runoff: the case of Rio Grande Basin, Romy R. Ravines, Alexandra M. Schmidt, Helio S. Migon and Camilo D. Rennó (2008). Journal of Hydrology, 353, 189-200.

• Spatial modelling of the relative risk of dengue fever in Rio de Janeiro for the epidemic period between 2001 and 2002, Gustavo S. Ferreira and Alexandra M. Schmidt (2006). Brazilian Journal of Probability and Statistics, 20, 1, 29-47.

• Revisiting distributed lag models through a Bayesian perspective, Romy R. Ravines, Alexandra M. Schmidt and Helio S. Migon (2006). Applied Stochastic Models in Business and Industry, 22, 2, 193-210.

• Spatio-temporal models for mapping the incidence of malaria in Pará, Aline A. Nobre, Alexandra M. Schmidt and Hedibert F. Lopes (2005). Environmetrics, 16, 291-304.

• Explaining Species Diversity Through Species Level Hierarchical Modeling, Alan E. Gelfand, Alexandra M. Schmidt, Shanshan Wu, John A. Silander Jr., Andrew Latimer and Anthony G. Rebelo (2005). Journal of the Royal Statistical Society, Series C (Applied Statistics), 54, 1, 1-20.

• Nonstationary Multivariate Process Modeling through Spatially Varying Coregionalization (with discussion), Alan E. Gelfand, Alexandra M. Schmidt, Sudipto Banerjee and C.F. Sirmans (2004). TEST, 13, 2, 1-50.

• Bayesian Inference for Nonstationary Spatial Covariance Structures via Spatial Deformations, Alexandra M. Schmidt and Anthony O’Hagan (2003). Journal of the Royal Statistical Society Series B, 65, 3, 743-758.

• A Bayesian Coregionalization Approach for Multivariate Pollutant Data, Alexandra M. Schmidt and Alan E. Gelfand (2003). Journal of Geophysical Research-Atmospheres, 108.

• An Adaptive Resampling Scheme for Cycle Estimation, Alexandra M. Schmidt, Dani Gamerman and Ajax R. B. Moreira (1999). Journal of Applied Statistics, 26, 5, 619-641.

• Hyperparameter Estimation in Forecast Models, Hedibert Freitas Lopes, Ajax R. B. Moreira and Alexandra M. Schmidt (1999). Computational Statistics & Data Analysis, 29, 387-410.

• Temporal Aggregation in Dynamic Linear Models, Alexandra M. Schmidt and Dani Gamerman (1997). Journal of Forecasting, vol. 16, 293-310.

Book chapters

• Dynamic models Alexandra M. Schmidt and Hedibert F. Lopes (2019). Handbook of Environmental and Ecological Statistics, pp. 57-80. Chapman & Hall/CRC, editors Alan E. Gelfand, Montserrat Fuentes, Jennifer Hoeting, and Richard Smith.
• Conditional autoregressive (CAR) model, Alexandra M. Schmidt and Widemberg S. Nobre (2018). In Wiley StatsRef: Statistics Reference Online, editors N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri and J. L. Teugels.
• Modelling multivariate counts varying continuously in space, Alexandra M. Schmidt and Marco A. Rodríguez (2011), pp. 611-628 in Bayesian Statistics 9. Oxford: Oxford University Press, editors J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West.
• Rejoinder to the discussion of Boys, Farrow and German, Alexandra M. Schmidt and Marco A. Rodríguez (2011), pp. 630-638 in Bayesian Statistics 9. Oxford: Oxford University Press, editors J. M. Bernardo, M. J. Bayarri, J. O. Berger, A. P. Dawid, D. Heckerman, A. F. M. Smith and M. West.
• Mapping Malaria in the Amazon Rainforest: a Spatio-Temporal Mixture Model, Alexandra M. Schmidt, Jennifer A. Hoeting, João B. M. Pereira and Pedro P. Vieira (2010), pp. 90-117 in The Oxford Handbook of Applied Bayesian Analysis, eds A. O’Hagan and M. West, Oxford University Press.

Invited Discussions

• Discussion on “A combined estimate of global temperature” by Peter Craigmile and Peter Guttorp, Alexandra M. Schmidt and Marco A. Rodríguez (2022). Environmetrics, 33(3), e2720.
• Discussion on “Spatial+: a novel approach to spatial confounding” by Emiko Dupont, Simon N. Wood, and Nicole H. Augustin", Alexandra M. Schmidt (2022). Biometrics, 78 (4), 1300–1304.
• Discussion on “An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differentiation approach”, Alexandra M. Schmidt, Journal of the Royal Statistical Society Series B, 73(4), 423-498
• Comment on Article by Craigmile et al., (2009) Alexandra M. Schmidt, Bayesian Analysis, 4, 45 - 54.
• Some Further Aspects of Spatio-Temporal Modeling, (2003) Alexandra M. Schmidt. Discussion of the paper Spatial hierarchical Bayesian models in ecological applications, Antti Penttinen, Fabio Divino and Anne Riiali, in Highly Structured Stochastic Systems, edited by P. Green, N. Hjort and S. Richardson, Oxford University Press.

PhD Thesis

Bayesian Spatial Interpolation of Pollution Monitoring Stations, Alexandra M. Schmidt. Unpublished PhD thesis, Department of Probability and Statistics, University of Sheffield, UK, June 2001.

Post-Doc

• Jéssica Pavani (2025-2026) Complex behavioural-change in epidemic models (with Rob Deardon)
• Dirk Douwes-Schultz (2024-2026) Hidden Markov spatial epidemic models (with Rob Deardon)
• Rishikesh Yadav (2023-2024) (with Aurélie Labbe and Pratheepa Jeganathan)
• Sara Zapata-Marin (2022-2023) Hurdle models for temporally misaligned spatio-temporal processes
• Raja Ben Hajria (2021-2023) Hidden Markov Individual-level Models of Disease Transmission (with Rob Deardon)
• Hiroshi Mamiya (2020-2022) Building precision retail grocery strategies to promote healthy food purchasing using massive consumer panel data (with Erica E. M . Moodie)
• Caitlin E. Ward (2021-2022) Behavioural Change in Infectious Disease Systems (with Rob Deardon)
• Hassan Rezaee (2019-2022) Spatio-temporal models for the analysis of GPS traces, application in road safety (with Aurélie Labbe)
• Renato Silva (2019-2021) Modelling the impact of water pressure on water main breaks using a spatially explicit Bayesian model (Mitacs - Cann Forecast) (with Sophie Duchesne)

PhD

Current

• Victor Silveira (2025 - 2026) (Public Health, Federal University of Maranhão, Brazil) Heterogeneity in the consumption of ultraprocessed foods: contributions from Brazilian epidemiological surveys (with Alcione M. dos Santos and Ana Karina T. C. Franca, Federal University of Maranhão, Brazil)
• Rafael Cabral Fernandez (2024 - 2028) (Statistics, Federal University of Rio de Janeiro, Brazil) Bayesian inference for physcis informed surrogate models (with Helio S. Migon and Carlos Zanini, Federal University of Rio de Janeiro, Brazil)
• Sébastien Garneau (2023-2027) (Biostatistics, EBOH, McGill University) (with Carlos Zanini, Federal University of Rio de Janeiro, Brazil)
• Mingchi Xu (2023-2027) (Biostatistics, EBOH, McGill University) (with Qihuang Zhang)
• Mariana Carmona Baez (2021-2025) (QLS, McGill University) (with Shirin Golchi)

Former students

• Renaud Alie (Statistics, McGill University) (2024) (with David A. Stephens) Tractability and scalability in multitype Gaussian Cox process models
• Paritosh Kumar Roy (Biostatistics, EBOH, McGill University) (2024) Non-Gaussian models for spatial and spatio-temporal processes
• Victoire Michal (Biostatistics, EBOH, McGill University) (2024) Areal data: disease mapping and small area estimation (with Jon Wakefield)
• Dirk Douwes-Schultz (Biostatistics, EBOH, McGill University) (2024) Coupled Markov Switching Models for Spatio-temporal Count Data
• Sara Zapata-Marin (QLS, McGill University) (2022) Land-use regression and spatio-temporal hierarchical models for environmental processes
• Widemberg S. Nobre (Department of Statistics, UFRJ, Brazil) (2021) A Bayesian view on causal inference for observational data (with David A. Stephens, Erica E. M. Moodie and, Helio S. Migon)
• Laís P. Freitas (ENSP, Fiocruz, Brazil) (2020) Environment, space and time: the incidence of dengue, zika and chikungunya in an intra urban scenario (with Marília S. Carvalho and Oswaldo G. Cruz)
• Hiroshi Mamiya (Epidemiology, EBOH, McGill University) (2020) Advancing community foodscape assessment: characterizing the interaction between people and food environments using grocery point-of-purchase data (with David Buckeridge)
• Estelina S. M. Capistrano (Department of Statistics, UFRJ, Brazil) (2019) Inference on average treatment effect on the treated from a Bayesian perspective (with Erica E. M. Moodie)
• Renata Bueno (Department of Statistics, UFRJ, Brazil) (2016) Spatio-temporal models for asymmetric and heavy-tailed processes (with Thais C. O. Fonseca)
• João Batista M. Pereira (Department of Statistics, UFRJ, Brazil) (2015) Process convolution models for spatially referenced count data (with Marco A. Rodríguez and Bruno Sansó)
• Josiane da Silva Cordeiro (Department of Statistics, UFRJ, Brazil) (2014) Hierarchical models: applications and extensions (with Helio S. Migon)
• Patrícia L. Velozo (Department of Statistics, UFRJ, Brazil) (2014) Modeling spatio-temporal asymmetric processes
• Alexandre Sousa da Silva (Department of Statistics, UFRJ, Brazil) (2012) Spatio-temporal models for temporally aggregated processes
• Joaquim Henriques Vianna Neto (Department of Statistics, UFRJ, Brazil) (2012) Including covariates in the covariance structure of spatial processes
• Aline Araújo Nobre (Department of Statistics, UFRJ, Brazil) (2007) Spatially varying AR processes (with Bruno Sansó)
• Ramiro Ruiz Cárdenas (Department of Statistics, UFRJ, Brazil) (2007) Optimal monitoring network designs (with Marco A. R. Ferreira)
• Mariana Gómez (ENSP, Fiocruz, Brazil) (2006) Modelling the vulnerability of some cities of Uruguay to dengue fever (with Ulisses Confalonieri)
• Romy R. Ravines (Department of Statistics, UFRJ, Brazil) (2006) An efficient sampling scheme in generalized dynamic models with applications to transfer function models (with Helio S. Migon)

MSc

Current

• Xinyue Cui (2025-2026) (Thesis, Biostatistics, EBOH McGill University)

Former students

• Molly Potter (Thesis, Epidemiology, EBOH, McGill University) (2024) The impact of improved air quality on childhood health and equity – A health impact assessment study conducted at the census block level (with Carole Dufouil)
• Lily Chafetz (Non-Thesis, Biostatistics, EBOH, McGill University) (2022) Optimal strategies for interim analysis scheduling in Bayesian adaptive clinical trials: a simulation study (with Shirin Golchi)
• Mingchi Xu (Non-Thesis, Biostatistics, EBOH, McGill University) (2022) Zero-state Markov switching count models for chikungunya spread in Rio de Janeiro (with Dirk Douwes-Schultz)
• Gabrielle Virgili-Gervais (Thesis, Biostatistics, EBOH, McGill University) (2022) Estimating socio-economic status through a hierarchical spatial Bayesian model for mixed dichotomous and continuous variables (with Jill Baumgartner and Brian Robinson)
• Tuviere Onookome-Okome (Thesis, Epidemiology, EBOH, McGill University) (2021) Predicting high-resolution spatial and temporal variations in summer air temperatures to support public health interventions during heat emergencies (with Scott Weichenthal)
• Robert McTavish (Thesis, Epidemiology, EBOH, McGill University) (2021) Identification of vulnerable urban areas in Accra, Ghana using census and remote sensing data (with Jill Baumgartner and Brian Robinson)
• Adam Palayew (Thesis, Epidemiology, EBOH, McGill University) (2020) Estimation of an individual-level deprivation index in a cohort of HIV/HCV co-infected Canadians and its relationship with health outcomes (with Marina Klein)
• Qi Zhang (Thesis, Department of Statistics, Concordia University) (2019) Skewed spatial modeling for arsenic contamination in Bangladesh (with Yogen P. Chaubey)
• Zayd Omar (Thesis, Department of Mathematics and Statistics, McGill University) (2019) State-space models with GARCH errors: Application to health data (with David A. Stephens)
• Widemberg da Silva Nobre (Thesis, Department of Statistics, UFRJ, Brazil) (2017) Spatial confounding in hierarchical models (with João B. M. Pereira)
• Ingrid C. Luquett de Oliveira (Thesis, Department of Statistics, UFRJ, Brazil) (2015) Preferential sampling for discrete spatial processes: the Bernoulli and Poisson cases
• Caroline Ponce de Moraes (Thesis, Department of Statistics, UFRJ, Brazil) (2015) An analysis of the performance of Public Schools in the Brazilian Mathematical Olympiads via hierarchical normal and beta models (with Helio S. Migon)
• Rafael M. Barcellos (Thesis, Department of Statistics, UFRJ, Brazil) (2014) Multivariate dynamic linear models applied to the oil refining market
• Estelina S. M. Capistrano (Thesis, Department of Statistics, UFRJ, Brazil) (2012) A hierarchical model for Lévy stochastic processes (with Marco A. Rodríguez)
• João B. M. Pereira (Thesis, Department of Statistics, UFRJ, Brazil) (2010) Models for count data with temporal structure
• Patricia L. C. Velozo (Thesis, Department of Statistics, UFRJ, Brazil) (2009) Models for categorical data with temporal structure
• Josiane da Silva Cordeiro (Thesis, Department of Statistics, UFRJ, Brazil) (2009) Bayesian inference for deterministic models (with Claudio Struchiner)
• Leonardo C. da Costa (Thesis, Department of Statistics, UFRJ, Brazil) (2008) Investigating the inclusion of spatial effects in assymetric models
• Joaquim H. Vianna Neto (Thesis, Department of Statistics, UFRJ, Brazil) (2007) A joint model for mean and variance: an application to the estimation problem in small areas (with Fernando A. S. Moura)
• Carolina P. Ornelas (Thesis, Department of Statistics, UFRJ, Brazil) (2006) Semi-parametric Bayesian models: an application to environmental problems (with Mariane B. Alves)
• Marcus V. M. Fernandes (Thesis, Department of Statistics, UFRJ, Brazil) (2006) Spatio-temporal models for zero-inflated data (with Helio S. Migon)
• Renata L. Estrella (Thesis, Department of Statistics, UFRJ, Brazil) (2005) Analysis of spatially misaligned data
• Gustavo S. Ferreira (Thesis, Department of Statistics, UFRJ, Brazil) (2004) A spatio-temporal analysis of cases of dengue fever in the city of Rio de Janeiro from 1986 until 2002 (with Dani Gamerman)
• Aline A. Nobre (Thesis, Department of Statistics, UFRJ, Brazil) (2003) A spatio-temporal model for the relationship between malaria and rainfall in the state of Pará (with Hedibert Lopes)

I joined the Department of Epidemiology, Biostatistics & Occupational Health at McGill University, Montreal, in August 2016. I am Professor of Biostatistics, and currently, hold the endowed University Chair.

Prizes and Awards

• 2024 Elected Fellow of the International Society for Bayesian Analysis
• 2020 Elected Fellow of the American Statistical Association ( ASA)
• 2018 Excellence in teaching in Epidemiology Core Courses from the Epidemiology, Biostatistics and Occupational Health Student Society (EBOSS)
• 2017 Distinguished Achievement Medal from the American Statistical Association’s Section on Statistics and the Environment ( ENVR)
• 2010 Elected Member of the International Statistical Institute ( ISI)
• 2008 Abdel El-Shaarawi Young Investigator Award, from The International Environmetrics Society ( TIES)

Service

• 2024-2028 Member of the Research Committee of the Health Effects Institute
• 2024-2026 Member of the ASA-ENVR Awards Committee
• 2025 JSM Program Chair, ASA, Nashville, Tennessee
• 2024 Member of the ISI Membership Elections Committee
• Chair of the local organizing committee of the 2022 ISBA World Meeting, Montreal, Canada
• 2021-2025 Elected Council Member of the International Statistical Institute
• 2020-2022 Elected International Rep. to the Board of the American Statistical Association
• 2019-2021 Elected Regional Rep. of Québec to the Board of Directors of the Statistical Society of Canada
• 2018-2022 Member of the Mathematics and Statistics Committee of the Natural Sciences and Engineering Research Council of Canada ( NSERC)
• 2018-2019 Chair-Elect and Chair of the Section on Environmental Sciences of the International Society of Bayesian Analysis ( EnviBayes)
• 2018-2019 Program Chair Elect and Program Chair of the Section Statistics on the Environment of the American Statistical Association ( ENVR)
• 2014-2016 President-Elect, President, Past-President of the International Society for Bayesian Analysis ( ISBA)
• 2014-2016 Vice-Chair of the Mathematics, Probability and Statistics Committee of CAPES
• 2009-2011 Program Chair of ISBA
• 2008-2010 President of the Brazilian Chapter ( ISBrA) of ISBA
• 2007-2009 Elected Board Member of ISBA

Editorships of Journals

• Editor-in-Chief of the Canadian Journal of Statistics (2025-2027)
• Editor of Bayesian Analysis (2019-2024)
• Associate Editor International Statistical Review (2021-2024)
• Associate Editor Environmetrics (2010- )
• Associate Editor of REVSTAT (2019-2025)
• Associate Editor Computational Statistics and Data Analysis (2018-2023)
• Associate Editor Stat (2011-2022)
• Associate Editor Scandinavian Journal of Statistics (2012-2018)
• Editor of Applications The Brazilian Journal of Probability and Statistics (2012-2014)

Professional Memberships

• American Statistical Association
• International Statistical Institute
• International Society for Bayesian Analysis
• Statistical Society of Canada

Former Positions

• 2016-2020 Associate Professor, Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Canada
• 2012-2016 Professor, Department of Statistics, Federal University of Rio de Janeiro, Brazil
• 2005-2012 Associate Professor, Department of Statistics, Federal University of Rio de Janeiro, Brazil
• 2002-2005 Assistant Professor, Department of Statistics, Federal University of Rio de Janeiro, Brazil

Contact me if you are interested to do a Ph.D. or M.Sc. in Biostatistics developing statistical methods for spatial and spatio-temporal processes.

I am a teaching instructor for the following courses at the Department of Epidemiology, Biostatistics and Occupational Health at McGill University:

• BIOS 612 Advanced generalized linear models (Fall 2016, Fall 2017, Fall 2018, Fall 2020, Fall 2021, Fall 2022)
• EPIB 621 Data analysis in the health sciences (Winter 2017, Winter 2018)
• EPIB 675/BIOS 693 Spatial and Spatio-temporal epidemiology (Winter 2019, Winter 2025)
• EPIB679/BIOS 691 Bayesian Analysis in Health Sciences (Fall 2019, Winter 2021, Winter 2023, Fall 2024)
• EPIB 677/BIOS 692 Spatial and Spatio-temporal epidemiology (Winter 2020)

2025

• 25 - 27 October - Invited speaker EnviBayes 2025, Texas A&M University
• 5 - 9 October - Invited speaker in an invited session 65th ISI World Statistics Congress 2025, The Hague
• 2 - 7 August - Invited speaker in an invited session at the JSM 2025 Nashville
• 3 - 6 June - Short course on Spatio-temporal Methods in Environmental Epidemiology at the Applied Bayesian Statistics Summer School
• 25 - 28 May - Invited speaker in an invited session at the 2025 SSC Annual Meeting in Saskatoon

2024

• 25 September - Co-Organizer Webinar Series CIRS-ASA & SWB - The Art of Data Privacy: An Introduction to Statistical Data Privacy and Confidentiality
• 24 July - Co-Organizer Webinar Series CIRS-ASA & SWB - An Overview of Statistical Data Integration in Health Policy
• 1 - 7 July - Plenary Speaker, 2024 ISBA World Meeting, Venice, Italy.
• 25 - 27 June - Short course: ‘‘An introduction to Bayesian spatial regression’’, Workshop on spatio-temporal modelling, Universidad Pública de Navarra, Spain.
• 22 May - Co-Organizer Webinar Series CIRS-ASA & SWB - Introduction to record linkage
• 23 April - Seminar - Dipartimento Metodi e Modelli per l’Economia, il Territorio e la Finanza, La Sapienza, Rome, Italy.
• 9 - 11 April - Invited Speaker, Workshop on complex environmental data and modeling, Pescara, Italy.
• 6 March - Co-Organizer Webinar Series CIRS-ASA & SWB - Bayesian variable selection

2023

• 21 - 24 November - Plenary Speaker, EMR 2023, Belém, Pará, Brazil.
• 13 - 17 November - Plenary Speaker, BAYSM 2023, Connecticut, USA. Online.
• 25 - 27 October- Plenary Speaker, Encontro de Modelagem Computacional, Nova Friburgo, Brazil.
• 18 - 20 October - Plenary Speaker, 13a Semana da Estatística da UFF, Niterói, Brazil.
• 18 - 20 September - Invited Speaker, EnviBayes 2023, Colorado State University, Fort Collins, USA.
• 5 - 10 August - Invited speaker in Contributed Session, JSM 2023, Toronto, Canada.
• 26 July - Co-Organizer Webinar Series CIRS-ASA & SWB - Introduction to Bayesian Modelling of Epidemics: From Population to Individual-level Models
• 18 - 21 July - Plenary speaker, Spatial Statistics 2023: Climate and the Environment
• 16 - 20 July - Invited speaker in invited session, 64th ISI World Statistics Congress, Ottawa, Canada.
• 28 - 31 May - Invited speaker in invited session, 2023 SSC Annual Meeting, Ottawa, Canada.
• 25 May - Plenary Speaker, Celebrating Women in Math, Online, Federal University of Rio de Janeiro, Brazil.
• 22-24 May Contributed Talk, 13th Bayesian Inference for Stochastic Processes, Madrid, Spain.
• 10 May - Co-Organizer Webinar Series CIRS-ASA & SWB - Causal inference in statistics: why, what, and how
• April - May - Chair, 2023 ISI Jan Tinbergen Awards committee.
• 8 March - Co-Organizer Webinar Series CIRS-ASA & SWB - Positioning Household Surveys for the Next Decade: Data Integration and Inclusion

2022

• 17 - 19 December - Invited speaker in invited session, CMStatistics 2022, Kings College, London, UK
• 8 December - Co-Organizer Webinar Series CIRS-ASA & SWB - Deep learning: opening the black box
• 1 - 3 December - ASA’s Keynote speaker at the 4th Conference on Statistics and Data Science
• 12 - 14 October - Invited speaker in invited session GEOMED 2022
• 11 October - Invited speaker in invited session of the International Day of Women in Statistics and Data Science
• 21 September - Co-Organizer Webinar Series CIRS-ASA & SWB and Speaker - An Introduction to Spatial Statistics with Applications to Disease Mapping
• 18 August - Discussant IBS Journal Club
• 20 July - Co-Organizer Webinar Series CIRS-ASA & SWB - An Introduction to Bayesian Inference
• 26 June - 1 July - 2022 ISBA World Meeting - Chair, Local Organizing Committee and member, Scientific Committee, Montreal, Canada
• 22 - 23 - June Discussant at BAYSM 2022
• 11 May - Co-Organizer Webinar Series CIRS-ASA & SWB - An Introduction to Small Area Estimation
• 9 May - Organizer, Session in Statistics of the Celebrating Women in Mathematics meeting, Rio de Janeiro, Brazil
• 27 April - The Mitchell Lecture 2022, School of Mathematics and Statistics, University of Glasgow, Scotland

2021

• 15 - 18 July - Invited Session organizer, 6th Canadian Conference in Applied Statistics
• 11 - 16 July - Invited Session organizer, 63rd ISI World Statistics Congress 2021
• 28 June - 2 July - Invited Session organizer, 2021 ISBA World Meeting, Online.
• 7 - 11 June - Invited speaker in invited session, 2021 SSC Annual Meeting, Online.
• 3 - 5 May - Keynote speaker, I Encontro de Mulheres na Estatística e Ciência de Dados, Brazil.
• Chair, 2021 ISI Jan Tinbergen Awards committee.
• Scientific Committee, 2021 GEOMED Seminar Series.

2020

• 2 - 4 December - TIES 2020 Virtual Conference Frontiers in Statistics, Epidemiology and the Environment
• 23 - 27 August - 41st Annual Conference of the International Society for Clinical Biostatistics , Poland, online.
• 2 - 6 August - JSM 2020, USA, online.
• 8 - 12 June - Advancing knowledge about spatial modeling, infectious diseases, environment and health, Canada, online.

I was born in Nova Friburgo, in the state of Rio de Janeiro, Brazil. I’m the result of a mixture between a German father and a Brazilian mother. From 1977 until 1987 I studied at Colegio Anchieta. In 1988 I moved from Nova Friburgo to the city of Rio de Janeiro to get ready to start my undergrad studies. I lived in Rio until 1997.

I lived in England from September 1997 until July 2001 to do my PhD under the supervision of Anthony O’Hagan. There, I lived in Nottingham for one year, then I moved to Sheffield. Soon after finishing my PhD I moved to Connecticut in the USA, where I did a Post-Doc with Alan E. Gelfand.

From 2002 until 2016 I lived in Rio de Janeiro, Brazil. In August 2016, I followed my heart and moved to Montreal, QC, Canada.