tetano
Editor, Senior Moderator
J Med Internet Res
. 2020 Jul 23.
doi: 10.2196/21081. Online ahead of print.
How Data Analytics and Big Data can Help Scientists in Managing COVID-19 Diffusion: A Model to Predict the COVID-19 Diffusion in Italy and Lombardy Region
Davide Tosi[SUP] 1 [/SUP], Alessandro Campi[SUP] 1 [/SUP]
Affiliations
Abstract
Background: CoronaVirus Disease 2019 (COVID-19) is the main discussed topic world-wide in 2020 and at the beginning of the Italian epidemic, scientists tried to understand the virus diffusion and the epidemic curve of positive cases with controversial findings and numbers.
Objective: In this paper, a data analytics study on the diffusion of COVID-19 in Italy and Lombardy Region is developed in order to define a predictive model tailored to forecast the evolution of the diffusion overtime.
Methods: Starting from all the available official data collected world-wide about the diffusion of COVID-19, we defined a predictive model at the beginning of March 2020 for the Italian country.
Results: The paper aims at showing how this predictive model was actually able to forecast the behavior of the COVID-19 diffusion, and how it well predicted the total number of positive cases in Italy over time. The predictive model forecasted, for the Italian country, the end of the COVID-19 first wave by the beginning of June.
Conclusions: The paper shows that big data and data analytics can help medical experts and epidemiologists in designing promptly accurate and generalized models to predict the different COVID-19 evolutionary phases in other countries, regions, and for second and third possible epidemic waves.
. 2020 Jul 23.
doi: 10.2196/21081. Online ahead of print.
How Data Analytics and Big Data can Help Scientists in Managing COVID-19 Diffusion: A Model to Predict the COVID-19 Diffusion in Italy and Lombardy Region
Davide Tosi[SUP] 1 [/SUP], Alessandro Campi[SUP] 1 [/SUP]
Affiliations
- PMID: 33027038
- DOI: 10.2196/21081
Abstract
Background: CoronaVirus Disease 2019 (COVID-19) is the main discussed topic world-wide in 2020 and at the beginning of the Italian epidemic, scientists tried to understand the virus diffusion and the epidemic curve of positive cases with controversial findings and numbers.
Objective: In this paper, a data analytics study on the diffusion of COVID-19 in Italy and Lombardy Region is developed in order to define a predictive model tailored to forecast the evolution of the diffusion overtime.
Methods: Starting from all the available official data collected world-wide about the diffusion of COVID-19, we defined a predictive model at the beginning of March 2020 for the Italian country.
Results: The paper aims at showing how this predictive model was actually able to forecast the behavior of the COVID-19 diffusion, and how it well predicted the total number of positive cases in Italy over time. The predictive model forecasted, for the Italian country, the end of the COVID-19 first wave by the beginning of June.
Conclusions: The paper shows that big data and data analytics can help medical experts and epidemiologists in designing promptly accurate and generalized models to predict the different COVID-19 evolutionary phases in other countries, regions, and for second and third possible epidemic waves.