# A Modified SIR Model for the COVID-19 Contagion in Italy

arXiv: https://arxiv.org/abs/2003.14391 · HTML: https://mlsanity.com/paper/2003.14391/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Mar 2020.

## Built on by (most cited first, 3 of 3)

- [The Limits to Learning a Diffusion Model](https://mlsanity.com/paper/2006.06373/) (2020)
- [Fine-Grained Population Mobility Data-Based Community-Level COVID-19 Prediction Model](https://mlsanity.com/paper/2202.06257/) (2022)
- [Epidemic modelling of multiple virus strains: a case study of SARS-CoV-2 B.1.1.7 in Moscow](https://mlsanity.com/paper/2106.08048/) (2021)

## Abstract (arXiv)

The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resides in the fact that we considered as model parameters also the initial number of susceptible individuals, as well as the proportionality factor relating the detected number of positives with the actual (and unknown) number of infected individuals. Identifying the contagion, recovery and death rates as well as the mentioned parameters amounts to a non-convex identification problem that we solved by means of a two-dimensional grid search in the outer loop, with a standard weighted least-squares optimization problem as the inner step.