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



Konstantinoudis G, Cameletti M, Gómez-Rubio, et al., 2022, Regional excess mortality during the 2020 COVID-19 pandemic in five European countries, Nature Communications, ISSN:2041-1723

Huang G, Blangiardo M, Brown PE, et al., 2021, Long-term exposure to air pollution and COVID-19 incidence: A multi-country study, Spatial and Spatio-temporal Epidemiology, Vol:39, ISSN:1877-5845, Pages:1-11

Maes MJA, Pirani M, Booth ER, et al., 2021, Benefit of woodland and other natural environments for adolescents' cognition and mental health, Nature Sustainability, Vol:4, ISSN:2398-9629, Pages:851-+

Pirani M, Mason A, Hansell A, et al., 2020, A flexible hierarchical framework for improving inference in area-referenced environmental health studies, Biometrical Journal: Journal of Mathematical Methods in Biosciences, Vol:62, ISSN:0323-3847, Pages:1650-1669

Blangiardo M, Cameletti M, Pirani M, et al., 2020, Estimating weekly excess mortality at sub-national level in Italy during the COVID-19 pandemic, Plos One, Vol:15, ISSN:1932-6203

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