The COVID-19 epidemic hit Italy particularly hard, yielding the implementation of strict national lockdown rules. Previous modelling studies at the national level overlooked the fact that Italy is divided into administrative regions which can independently oversee their own share of the Italian National Health Service. Here, we show that heterogeneity between regions is essential to understand the spread of the epidemic and to design effective strategies to control the disease. We model Italy as a network of regions and parameterize the model of each region on real data spanning over two months from the initial outbreak. We confirm the effectiveness at the regional level of the national lockdown strategy and propose coordinated regional interventions to prevent future national lockdowns, while avoiding saturation of the regional health systems and mitigating impact on costs. Our study and methodology can be easily extended to other levels of granularity to support policy- and decision-makers.

In standard clinical protocols, the result of neuromotor rehabilitation programs is evaluated through validated clinical scales and tests able to measure the motor performance of the patients and monitor their improvements over time. The Timed Up and Go (TUG) test is one of the most common assessments used to evaluate patients’ dynamic balance, as well as their mobility. However, in its traditional version, the TUG test does not provide quantitative information on gait performances—only subjectively observed by the clinician—and does not measure the timing of the different phases involved in its execution. The availability of additional quantitative information would indeed be useful for the clinicians to formulate a more accurate assessment of patient performance and define a personalized treatment plan. In this sense, the use of Socially Assistive Robots (SARs) could help improving the assessment of patient performance, relieving at the same time the physiotherapists from time consuming tasks. The goal of this feasibility study is twofold: (1) to assess the quality of the TUG functionality implemented on the robot from a technical standpoint and (2) to evaluate the perception of the “R1-TUG” solution from its potential end-users point of view, in terms of usability and acceptability. A set of tests involving a sample of healthy volunteers revealed that the adoption of a SAR as an assessment tool, could improve the ability of the physiotherapist to objectively assess the subject’s movement performance while ensuring an adequate level of usability and acceptability from the participants. This work represents a promising result for the future use of the robotic solutions within a rehabilitation context.