My research interests revolve around the general field of infectious disease epidemiology with a special focus on mathematical modeling and the application of interdisciplinary methods, such as network theory, to the field.

Pandemic forecasting

During my PhD studies, I worked as a member of the GLEAM (Global Epidemic and Mobility Model) Research Team. In particular, during the 2009 A/H1N1 pandemic crisis I joined the team in the effort of predicting the pandemic spread at the global scale through numerical simulations. Eventually, my main contribution has allowed to validate the real-time forecasts made during the early phase of the pandemic, using surveillance data collected for 1 year in more than 50 countries of the world.

Host heterogeneities and spatial epidemic spreading

On a more theoretical side, I am interested in studying epidemic processes occurring between hosts that are characterized by heterogeneities, in terms of mobility patterns and individual interactions. We integrate these real-world features into mathematical and computational epidemic models, and analyze their effects through numerical simulations and analytical calculations. In particular, my recent work has focused on the epidemiological consequences of large fluctuations in the time spent at destination by travelers, and the scaling properties of contacts in urban areas.

Digital Epidemiology

From a broader perspective, I am interested in the application of new technologies to the field of epidemiology and public health. I recently worked on the use of mobile phone data to inform epidemic models and I am involved in the SocioPatterns project whose aim is to collect empirical data on human interactions by proximity sensing devices.