Author: Bodini, Antonella; Pasquali, Sara; Pievatolo, Antonio; Ruggeri, Fabrizio
Title: Underdetection in a stochastic SIR model for the analysis of the COVID-19 Italian epidemic Cord-id: p72g7xq6 Document date: 2021_8_28
ID: p72g7xq6
Snippet: We propose a way to model the underdetection of infected and removed individuals in a compartmental model for estimating the COVID-19 epidemic. The proposed approach is demonstrated on a stochastic SIR model, specified as a system of stochastic differential equations, to analyse data from the Italian COVID-19 epidemic. We find that a correct assessment of the amount of underdetection is important to obtain reliable estimates of the critical model parameters. The adaptation of the model in each t
Document: We propose a way to model the underdetection of infected and removed individuals in a compartmental model for estimating the COVID-19 epidemic. The proposed approach is demonstrated on a stochastic SIR model, specified as a system of stochastic differential equations, to analyse data from the Italian COVID-19 epidemic. We find that a correct assessment of the amount of underdetection is important to obtain reliable estimates of the critical model parameters. The adaptation of the model in each time interval between relevant government decrees implementing contagion mitigation measures provides short-term predictions and a continuously updated assessment of the basic reproduction number.
Search related documents:
Co phrase search for related documents- actual number and additional information: 1
Co phrase search for related documents, hyperlinks ordered by date