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arXiv · 2102.07566

A stochastic SIR model for the analysis of the COVID-19 Italian epidemic

Sara Pasquali·Antonio Pievatolo·Antonella Bodini·Fabrizio Ruggeri
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Abstract

We propose a stochastic SIR model, specified as a system of stochastic differential equations, to analyse the data of the Italian COVID-19 epidemic, taking also into account the under-detection of infected and recovered individuals in the population. We find that a correct assessment of the amount of under-detection is important to obtain reliable estimates of the critical model parameters. Moreover, a single SIR model over the whole epidemic period is unable to correctly describe the behaviour of the pandemic. Then, the adaptation of the model in every time-interval between relevant government decrees that implement contagion mitigation measures, provides short-term predictions and a continuously updated assessment of the basic reproduction number.

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Sara Pasquali, Antonio Pievatolo, Antonella Bodini, Fabrizio Ruggeri. 2021-02-15. A stochastic SIR model for the analysis of the COVID-19 Italian epidemic. https://arxiv.org/abs/2102.07566

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