Stratification of the risk of developing severe or lethal Covid-19 using a new score from a large Italian population: A population-based cohort study

Objectives To develop a population-based risk stratification model (COVID-19 Vulnerability Score) for predicting severe/fatal clinical manifestations of SARS-CoV-2 infection, using the multiple source information provided by the healthcare utilisation databases of the Italian National Health Service. Design Retrospective observational cohort study. Setting Population-based study using the healthcare utilisation database from five Italian regions. Participants Beneficiaries of the National Health Service, aged 18-79 years, who had the residentship in the five participating regions. Residents in a nursing home were not included. The model was built from the 7 655 502 residents of Lombardy region. Main outcome measure The score included gender, age and 29 conditions/diseases selected from a list of 61 conditions which independently predicted the primary outcome, that is, severe (intensive care unit admission) or fatal manifestation of COVID-19 experienced during the first epidemic wave (until June 2020). The score performance was validated by applying the model to several validation sets, that is, Lombardy population (second epidemic wave), and the other four Italian regions (entire 2020) for a total of about 15.4 million individuals and 7031 outcomes. Predictive performance was assessed by discrimination (areas under the receiver operating characteristic curve) and calibration (plot of observed vs predicted outcomes). Results We observed a clear positive trend towards increasing outcome incidence as the score increased. The areas under the receiver operating characteristic curve of the COVID-19 Vulnerability Score ranged from 0.85 to 0.88, which compared favourably with the areas of generic scores such as the Charlson Comorbidity Score (0.60). A remarkable performance of the score on the calibration of observed and predicted outcome probability was also observed. Conclusions A score based on data used for public health management accurately predicted the occurrence of severe/fatal manifestations of COVID-19. Use of this score may help health decision-makers to more accurately identify high-risk citizens who need early preventive or treatment interventions

Grid-Tie and Off-Grid Operations for an Innovative Microgrid Realized in Leonardo Campus of Politecnico di Milano

In the paper, a novel Microgrid deployed in Leonardo Campus of Politecnico di Milano is described. The Microgrid hosts a Combined Cooling, Heating and Power plant (2 MWel) and two backup generators (1.6 MWel), plus some smaller PV plants. The advanced load management solution implemented is based on Schweitzer Engineering Laboratories (SEL) components. It provides new capacity for facing network requirements in case of emergency and allows maintaining a high level of quality of service for the local network. Moreover, it enables the participation of the Campus to the Italian Ancillary Services Market as a virtual unit. The focus of the paper is on the protection scheme in place and on the energy management procedure that has been developed in order to allow both a grid-tie and an off-grid operation of the Microgrid