Predictive models can be applied in different areas, during the emergency of the COVID-19 pandemic, in fact, they have proven important in supporting health systems in planning strategic decisions and in formulating health policies for the containment of the disease.

The Covid-19 pandemic, in particular, has represented a real challenge for our healthcare system. In Italy, it was divided into four main waves, each characterized by different types of patients and different therapeutic approaches progressively improved based on new scientific evidence.

The objective is to carry out a study on the data of patients hospitalized for COVID-19 at the ASST of Lecco during all four pandemic waves, with different degrees of severity of illness, collecting the data of interest and applying it to they use artificial intelligence to identify recurring patterns of clinical outcome in terms of survival and secondary infectious complications, so as to build new reliable predictive statistical models that can be used to predict the outcome of the patients themselves.

The strong ambition of this project is that the application of artificial intelligence to data of such significant quantity can allow us to build valid statistical models which can then be hypothetically applied to any patient to predict, based on anamnestic characteristics, blood chemical parameters. at baseline and at the set treatment, the probability of survival and complications

Inclusion Criteria:

• Age > 18 years;
• Hospitalization for COVID-19 pneumonia at ASST Lecco.

Exclusion Criteria:

• Hospitalization or finding of asymptomatic SARS CoV-2 infection.

For each patient, information will be collected regarding:

• Personal data (i.e. age, sex, nationality);
• Date of hospitalization and discharge (or death)
• Comorbidities;
• Treatments undertaken for Covid19;
• Possible vaccination for Covid19, date and number of doses;
• Possible onset of secondary infections and/or complications;
• Blood chemistry tests upon admission