Generating High-Granularity COVID-19 Territorial Early Alerts Using Emergency Medical Services and Machine Learning.

The pandemic of COVID-19 has posed unprecedented threats to healthcare systems worldwide. Great efforts were spent to fight the emergency, with the widespread use of cutting-edge technologies, especially big data analytics and AI. In this context, the present study proposes a novel combination of geographical filtering and machine learning (ML) for the development and optimization of a COVID-19 early alert system based on Emergency Medical Services (EMS) data, for the anticipated identification of outbreaks with very high granularity, up to single municipalities. The model, implemented for the region of Lombardy, Italy, showed robust performance, with an overall 80% accuracy in identifying the active spread of the disease. The further post-processing of the output was implemented to classify the territory into five risk classes, resulting in effectively anticipating the demand for interventions by EMS. This model shows state-of-art potentiality for future applications in the early detection of the burden of the impact of COVID-19, or other similar epidemics, on the healthcare system.

New solutions for personalised health management: citizens' needs, healthcare changes, and market perspectives round table debate.

The aim with the round table was to give additional inputs and views to the specific technology oriented presentations focusing on issues dealing with the need, patients' view, the use and the business opportunities relating to wearable eHealth systems for personalised health management. Wearable eHealth systems for personalised health management are targeting citizens, patients at health risks and patients enrolled in open care or home care for monitoring, treatment or follow up. The developments so far show promises for these group categories, and in addition, could support developments in health care organisations and systems. However, the ethical issues and data privacy nature have to be seriously taken into account. The market is not yet developed, and this is the situation both in Europe and in the US. To be able to give the customers solid product information a standardised test bed for new equipment and services might speed up the market development. In the round table discussion it was highlighted that one has to differ between needs and demands. Needs are related to the prevalence of the diseases, the health risks, etc. Demands are more related to market developments and customers' willingness to pay for the new products and services. Further, technical interoperability was seen as a fundamental prerequisite for market acceptance. As wearable eHealth systems for personalised health management differ completely from traditional way of deliver healthcare, new reimbursement systems have to be developed and implemented.