Ricerc@Sapienza

The ongoing epidemic spread of COVID-19 constitutes a global problem with consequences at different social levels (health and mortality, sanitary systems, public resources allocations, economics, job market, etc). An in-depth analysis of the measures implemented by the different Governments to manage the pandemic is useful to highlight their effectiveness and the social consequences of such decisions. Their examination is relevant not only in case of possible re-infection, but also for possible future epidemic risk events in such a globalized world. The COVID-19 emergency and the consequent reactions inspire this project, representing a case study for understanding the causes-effects relationships and for starting to define a generalization to future pandemics risk management. Epidemic emergency management must be faced from multiple points of view (political, economic, social, medical, sanitary, etc) and requires a highly complex analysis of real data, that sometimes (especially in the pandemic initial stages) are poor and collected inconsistently.
With the techniques of modeling, identification, control and optimization, the virus spread and its effects can be studied at different levels, for example studying categories of a single population ¿ grouping people according to some criteria, (the age, the vulnerability to the virus, the possibility of access to treatments ..) or considering the interactions among populations. Each study provides useful information to understand what happened and, possibly, to predict what could happen in similar cases.
This project aims to provide a deep analysis of the current pandemic emergency and a unified framework for risk management through the definition of optimal decision models and procedures for managing and controlling the spread and the effects of the epidemic. Ready-to-use protocols and possible specific interventions on the population will be proposed to reach optimal economic and social health-driven choices.