A Heavily Trained Time-Dependent SIRD Model for Local Covid-19 Data in Italy

Giancarlo Manzi received his PhD in statistics from the University of MilanBicocca, Italy. He worked as a biostatistician at the Medical Research Council - Biostatistics Unit, Cambridge, UK. He joined the Department of Economics, Business and Statistics, University of Milan, Italy as a lecturer in statistics and in April 2018 he got an associate professorship in statistics at the Department of Economics, Management and Quantitative Methods, University of Milan. He is a member of the Data Science Research Center and coordinator of the Master’s in Data Science for Economics, Business and Finance at the University of Milan. His main research interests are metaanalysis, multivariate statistical methods, Bayesian hierarchical methods, resampling methods, missing data imputation, SIR-based models.

Alessandra Micheletti is Associate Professor of Probability and Mathematical Statistics at the Dept. of Environmental Science and Policy, Università degli Studi di Milano, Italy. She got a Ph.D. in Computational Mathematics and Operation Research, she is vice-president of the European Consortium for Mathematics in Industry, member of the Data Science Research Center of University of Milan and coordinator of the H2020 MSCA project BIGMATH-‘‘Big data challenges for Mathematics’’. She is managing editor of the Journal of Mathematics in Industry and guest editor of a special issue entitled ‘‘Mathematical models of the spread and consequences of the SARS-CoV-2 pandemics. Effects on health, society, industry, economics and technology’’. Her main research interests are in the field of statistics and topological data analysis applied to industrial and life sciences problems.

Federica Nicolussi received his PhD in statistics and applicants in 2013 from the University of Milan-Bicocca, Italy. She joined the Department of Economics, Business and Statistics, University of Milan, Italy as a research fellow in 2018 at the Department of Economics, Management and Quantitative Methods, University of Milan. She is involved in the research activities at DSRS (Data Science Research Centre) of the University of Milan.
Her main research interests are probabilistic graphical models, multivariate statistical, analysis of categorical data, distributions for financial data, SIR-based models.

Elia Biganzoli is Full Professor in Medical Statistics at the 'Department of Biomedical and Clinical Sciences, University of Milan. He is member of the quality assurance board of the University of Milan, the research board of the Italian Medical Statistics and Epidemiology Society and the steering board of the Computational Intelligence for Bioinformatics and Biostatistics – CIBB. He is also a cofounder member of the Data Science Research Center, University of Milan. He is the Italian representative for the Lobsterpot COST Action CA19138 of the European Commission and he organized numerous workshops and conferences on biomedical sciences and biostatistics. His main research interests are statistical learning methods for survival analysis and high-throughput biological assays, planning and analysis of diagnostic and prognostic studies in cancer, chronic and infectious diseases with special interest on molecular biomarkers and bioprofiles.

Silvia Salini is Associate Professor in Statistics at the University of Milan and she is involved in the research activities at DSRS (Data Science Research Centre) of the University of Milan. She holds a degree in Statistics from the Catholic University of Milan and she obtained a PhD in Statistics from University of Milano-Bicocca. She is the director of the two-years master’s degree in Data Science and Economics of the University of Milan. She has participated in numerous research projects across different fields and her main research interests focus on statistical models for social science, multivariate statistics, statistical learning methods, robust statistics, and scientometrics.