My research is based upon the development of Bayesian statistical methods with primary application to environmental and health data.
Current methodological research focuses on spatial and spatio-temporal statistics, time-series analysis, methods for the integration of multi-scale sources of data and models for understanding the health consequences of exposure to (multiple) pollutants and changes in climate.
et al., 2020, A flexible hierarchical framework for improving inference in area-referenced environmental health studies, Biometrical Journal: Journal of Mathematical Methods in Biosciences, ISSN:0323-3847
et al., 2019, Using ecological propensity score to adjust for missing confounders in small area studies, Biostatistics, Vol:20, ISSN:1465-4644, Pages:1-16
et al., 2019, A hierarchical modelling approach to assess multi pollutant effects in time-series studies, Pl O S One, Vol:14, ISSN:1932-6203
et al., 2016, Modelling macronutrient dynamics in the Hampshire Avon river: a Bayesian approach to estimate seasonal variability and total flux, Science of the Total Environment, Vol:572, ISSN:0048-9697, Pages:1449-1460
Morandi G, Periche Tomas E, Pirani M, 2016, Mortality risk in alcoholic patients in northern Italy: comorbidity and treatment retention effects in a 30-year follow-up study, Alcohol and Alcoholism, Vol:51, ISSN:1464-3502, Pages:63-70