The LEM Seminar Series of the Institute of Economics restarts with two talks this week, both on COVID-19 spreading (for more information, research and readings on COVID-19 see the EMbeDS page here)
On Tuesday, October 13, 2020, Jacopo Di Iorio, a new research fellow at EMbeDS and the Sant'Anna School, will present the paper The shapes of an epidemic: using Functional Data Analysis to characterize Covid-19 in Italy. This paper investigates patterns of COVID-19 mortality across 20 Italian regions in the period from mid February to to the end of April 2020. These patterns are associated with mobility, positivity, and socio-demographic, infrastructural and environmental covariates -- and significant trends are pinpointed exploiting information in curves and shapes with Functional Data Analysis techniques. The data reveals two starkly different epidemics; an "exponential" one unfolding in Lombardia and the worst hit areas of the north, and a milder, "flat(tened)" one in the rest of the country – including Veneto, where cases appeared concurrently with Lombardia but aggressive testing was implemented early on. The paper finds that mobility and positivity can predict COVID-19 mortality, also when controlling for relevant covariates. Among the latter, primary care appears to mitigate mortality, and contacts in hospitals, schools and work places to aggravate it. The techniques used in the study could capture additional and potentially sharper signals if applied to richer data.
On Wednesday, October 14, 2020, Fabio Vanni from the Observatoire Français des Conjonctures Economiques (OFCE), will present the paper: The epidemic spread potential under physical distancing interventions. Combining the renewal equation with a kinetic collisional model for infection propagation, it is possible to derive a set of predictive equations for the short-to-medium-term behavior of an epidemic. These tools allow one to disentangle the effects of population mobility, physical proximity, test&trace and depletion of susceptibles. The theoretical framework is validated using real-world data on physical distancing with two different data repositories, obtaining consistent results. Knowing the effects of each of these components of the response of the government and society to the CoViD-19 epidemic should allow for less costly and more effective strategies for defeating epidemics. In particular, the collision model approach to estimation of infection risk should allow local, regional, and national governments to better assess the continuing threat of COVID-19 to the public welfare.