| KEYWORD |
Modeling the new flu wave using data science and complex networks theory
keywords COMPLEX NETWORKS, EPIDEMIC MODELING, EPIDEMIC SPREADING, MATHEMATICAL MODELING, NETWORKS
Reference persons ALESSANDRO RIZZO, LORENZO ZINO
Research Groups Automatica
Description This thesis will leverage data science, mathematical modeling, and complex networks to produce a computational tool for the on-line prediction of the spread of the 2023-24 seasonal flu in Italy. More precisely, the student will develop a network mathematical model for the spread of flu in Italy that uses available data on human mobility and reported cases to produce the predictions.
Required skills Fundamentals of data analysis, good programming and visualization skills, basic knowledge of network theory constitutes a plus
Deadline 25/08/2024
PROPONI LA TUA CANDIDATURA