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Article

Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022

by 1,†, 2,*,†, 3,4,† and 4,†
1
Department of Computer Science, Modeling, Electronics and Systems Engineering (DIMES), University of Calabria, 87036 Rende, Italy
2
Department of Health Sciences, University Magna Graecia, 88100 Catanzaro, Italy
3
Guglielmo Marconi University, 00193 Rome, Italy
4
SITO WEB del Gruppo Epidemiologico, EpiData.it, 24121 Bergamo, Italy
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Amal K. Mitra
Diseases 2022, 10(3), 38; https://doi.org/10.3390/diseases10030038
Received: 30 May 2022 / Revised: 23 June 2022 / Accepted: 28 June 2022 / Published: 30 June 2022
(This article belongs to the Special Issue COVID-19 and Global Chronic Disease II)
Despite the stunning speed with which highly effective and safe vaccines have been developed, the emergence of new variants of SARS-CoV-2 causes high rates of (re)infection, a major impact on health care services, and a slowdown to the socio-economic system. For COVID-19, accurate and timely forecasts are therefore essential to provide the opportunity to rapidly identify risk areas affected by the pandemic, reallocate the use of health resources, design countermeasures, and increase public awareness. This paper presents the design and implementation of an approach based on autoregressive models to reliably forecast the spread of COVID-19 in Italian regions. Starting from the database of the Italian Civil Protection Department (DPC), the experimental evaluation was performed on real-world data collected from February 2020 to March 2022, focusing on Calabria, a region of Southern Italy. This evaluation shows that the proposed approach achieves a good predictive power for out-of-sample predictions within one week (R-squared > 0.9 at 1 day, R-squared > 0.7 at 7 days), although it decreases with increasing forecasted days (R-squared > 0.5 at 14 days). View Full-Text
Keywords: SARIMA; time series regression models; forecasting; epidemiology; COVID-19; SARS-CoV-2; Italy; Calabria SARIMA; time series regression models; forecasting; epidemiology; COVID-19; SARS-CoV-2; Italy; Calabria
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MDPI and ACS Style

Branda, F.; Abenavoli, L.; Pierini, M.; Mazzoli, S. Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022. Diseases 2022, 10, 38. https://doi.org/10.3390/diseases10030038

AMA Style

Branda F, Abenavoli L, Pierini M, Mazzoli S. Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022. Diseases. 2022; 10(3):38. https://doi.org/10.3390/diseases10030038

Chicago/Turabian Style

Branda, Francesco, Ludovico Abenavoli, Massimo Pierini, and Sandra Mazzoli. 2022. "Predicting the Spread of SARS-CoV-2 in Italian Regions: The Calabria Case Study, February 2020–March 2022" Diseases 10, no. 3: 38. https://doi.org/10.3390/diseases10030038

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