Epidemic Models and Dynamical Systems
Analysis of compartmental epidemic models, including multigroup systems, stability properties and the mathematical behavior of models with different time scales.
Research areas & projects
My research combines mathematical modeling, medical statistics and epidemiology to study health-related questions, from theoretical epidemic dynamics to clinical and population data. The projects below highlight selected research themes, collaborations and related scientific outputs.
Mathematical analysis of dynamical systems, with a focus on stability, multigroup models, multiple time scales and Geometric Singular Perturbation Theory (GSPT).
Analysis of compartmental epidemic models, including multigroup systems, stability properties and the mathematical behavior of models with different time scales.
Epidemic dynamics on networks and graphs, the spread of information and misinformation, and the role of behavioral processes in disease transmission.
Mathematical modeling of epidemic processes coupled with the spread of information and misinformation, using dynamical-systems methods to investigate how fast information dynamics affect epidemic behavior.
Study of epidemic dynamics in heterogeneous and scale-free networks, including the role of network structure and time-varying transmission.
Statistical analysis of clinical, cohort and population-level data, including cancer and cardiovascular epidemiology, survival and longitudinal analysis, risk prediction, and data harmonization in international studies.
Work with international pooled studies and consortia, including data management, quality control, harmonization and statistical analysis. ACC work included research on coffee and tea consumption in relation to pancreatic cancer mortality. Within INHANCE, my work also includes research on occupational exposures and head and neck cancer.
Research focused on global trends in colorectal cancer, within the broader field of cancer epidemiology and statistical analysis of population data.
Statistical and machine-learning methods, including principal component analysis, clustering and random forests, applied to support the analysis of cervical cancer biopsy data.
Statistical and epidemiological analysis of a randomized pilot trial evaluating personalized cardiovascular prevention and its potential implementation in the Italian National Health Service.
Statistical analysis of immune response and antibody kinetics following SARS-CoV-2 vaccination in healthcare workers.
Within project BRIC-2022-ID25, statistical analysis of a patient dataset combining clinical information and interview data, in an interdisciplinary project investigating unemployment risk factors and return to work among liver transplant recipients.
Health technology assessment and economic evaluation of healthcare interventions, particularly cost-effectiveness analyses of influenza vaccination strategies in different populations and healthcare settings.
Health technology assessment and cost-effectiveness analyses of influenza vaccination strategies across different populations and healthcare settings, including pediatric vaccination in Italy, vaccination strategies in Spain, and the evaluation of influenza vaccines for older adults.
Mechanistic mathematical modeling of therapeutic antibody immunogenicity and drug interactions in chronic inflammatory diseases.
Development and analysis of a mechanistic mathematical model investigating the effect of methotrexate on adalimumab immunogenicity in axial spondyloarthritis.
Mathematical modeling and data analysis for vector-borne disease control and infectious disease transmission in animal populations.
Analysis of field data from releases of Wolbachia-infected male mosquitoes to assess fertility reduction in wild mosquito populations in Italy.
Mathematical modeling of avian influenza transmission across poultry farms in Veneto and Lombardy.