Imperial College London


Faculty of MedicineSchool of Public Health

Lecturer in Biostatistics



+44 (0)20 7594 1177monica.pirani




526Norfolk PlaceSt Mary's Campus





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



Blangiardo M, Pirani M, Kanapka L, et al., 2019, A hierarchical modelling approach to assess multi pollutant effects in time-series studies, Plos One, Vol:14, ISSN:1932-6203

Wang Y, Pirani M, Hansell A, 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

Pirani M, Panton A, Purdie DA, 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

Pirani M, Best N, Blangiardo M, et al., 2015, Analysing the health effects of simultaneous exposure to physical and chemical properties of airborne particles, Environment International, Vol:79, ISSN:1873-6750, Pages:56-64

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