Author: Celani, Alessandro; Giudici, Paolo
Title: Endemic–epidemic models to understand COVID-19 spatio-temporal evolution Cord-id: 7nq1uvo7 Document date: 2021_7_12
ID: 7nq1uvo7
Snippet: We propose an endemic–epidemic model: a negative binomial space–time autoregression, which can be employed to monitor the contagion dynamics of the COVID-19 pandemic, both in time and in space. The model is exemplified through an empirical analysis of the provinces of northern Italy, heavily affected by the pandemic and characterized by similar non-pharmaceutical policy interventions.
Document: We propose an endemic–epidemic model: a negative binomial space–time autoregression, which can be employed to monitor the contagion dynamics of the COVID-19 pandemic, both in time and in space. The model is exemplified through an empirical analysis of the provinces of northern Italy, heavily affected by the pandemic and characterized by similar non-pharmaceutical policy interventions.
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