443 citations · 968 across the 17 of their papers we have counts for
19 papers
Deep Learning for Crime Forecasting: The Role of Mobility at Fine-grained Spatiotemporal Scales
Ariadna Albors Zumel, Michele Tizzoni, Gian Maria Campedelli
Objectives: To develop a deep learning framework to evaluate if and how incorporating micro-level mobility features, alongside historical crime and sociodemographic data, enhances…
Generalized contact matrices for epidemic modeling
Adriana Manna, Lorenzo Dall'Amico, Michele Tizzoni +2
Contact matrices have become a key ingredient of modern epidemic models. They account for the stratification of contacts for the age of individuals and, in some cases, the context…
The limits of human mobility traces to predict the spread of COVID-19
Federico Delussu, Michele Tizzoni, Laetitia Gauvin
Mobile phone data have been widely used to model the spread of COVID-19, however, quantifying and comparing their predictive value across different settings is challenging. Their q…
Modeling adaptive forward-looking behavior in epidemics on networks
Lorenzo Amir Nemati Fard, Alberto Bisin, Michele Starnini +1
Incorporating decision-making dynamics during an outbreak poses a challenge for epidemiology, faced by several modeling approaches siloed by different disciplines. We propose an ep…
Inequality, Crime and Public Health: A Survey of Emerging Trends in Urban Data Science
Massimiliano Luca, Gian Maria Campedelli, Simone Centellegher +2
Urban agglomerations are constantly and rapidly evolving ecosystems, with globalization and increasing urbanization posing new challenges in sustainable urban development well summ…
Estimating household contact matrices structure from easily collectable metadata
Lorenzo Dall'Amico, Jackie Kleynhans, Laetitia Gauvin +9
Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age grou…