New York – At the first hints of the outbreak of a disease epidemiologists, health professionals, policy makers and scientists are turning to sophisticated forecasting models to determine how the disease is spreading and what should be done to minimize the risk of contagion. A collaborative research between Politecnico di Torino and the New York University Tandon School of Engineering is revolutionizing the traditional modeling process getting easier to calculate forecasts and more effective in a hyper-connected world. All predictive models correlate the movement of disease to the population over time, but today’s simulations do not always reflect effectively an obvious matter: the mobility and activity varies between people and these variations have an impact on chances of contracting or spreading the disease. A new paradigm has been exposed in a paper published in the prestigious journal Physical Review Letters by Alessandro Rizzo, associate professor of the Department of Control and Computer Science of the Politecnico and a visiting professor at New York University Tandon School of Engineering, Lorenzo Zino, PhD student of the Polytechnic in pure and applied mathematics, and Maurizio Porfiri, professor of mechanical and aerospace engineering at New York University Tandon School of Engineering. (9Colonne)
