Background: Till 31 March 2020, 105,792 COVID-19 cases were confirmed in Italy including 15,726 deaths which explains how worst the epidemic has affected the country. After the announcement of lockdown in Italy on 9 March 2020, situation was becoming stable since last days of March. In view of this, it is important to forecast the COVID-19 evaluation of Italy condition and the possible effects, if this lock down could continue for another 60 days. Methods: COVID-19 infected patient data has extracted from the Italian Health Ministry website includes registered and recovered cases from mid February to end March. Adoption of seasonal ARIMA forecasting package with R statistical model was done. Results: Predictions were done with 93.75% of accuracy for registered case models and 84.4% of accuracy for recovered case models. The forecasting of infected patients could be reach the value of 182,757, and recovered cases could be registered value of 81,635 at end of May. Conclusions: This study highlights the importance of country lockdown and self isolation in control the disease transmissibility among Italian population through data driven model analysis. Our findings suggest that nearly 35% decrement of registered cases and 66% growth of recovered cases will be possible.

COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach

Nalini Chintalapudi
Primo
;
Gopi Battineni
Secondo
;
2020-01-01

Abstract

Background: Till 31 March 2020, 105,792 COVID-19 cases were confirmed in Italy including 15,726 deaths which explains how worst the epidemic has affected the country. After the announcement of lockdown in Italy on 9 March 2020, situation was becoming stable since last days of March. In view of this, it is important to forecast the COVID-19 evaluation of Italy condition and the possible effects, if this lock down could continue for another 60 days. Methods: COVID-19 infected patient data has extracted from the Italian Health Ministry website includes registered and recovered cases from mid February to end March. Adoption of seasonal ARIMA forecasting package with R statistical model was done. Results: Predictions were done with 93.75% of accuracy for registered case models and 84.4% of accuracy for recovered case models. The forecasting of infected patients could be reach the value of 182,757, and recovered cases could be registered value of 81,635 at end of May. Conclusions: This study highlights the importance of country lockdown and self isolation in control the disease transmissibility among Italian population through data driven model analysis. Our findings suggest that nearly 35% decrement of registered cases and 66% growth of recovered cases will be possible.
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Journal of Microbiology, Immunology and Infection 2020, vol. 53(3) pp. 396-403.pdf

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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11581/481166
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