TY - JOUR
T1 - COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy
T2 - A data driven model approach
AU - Chintalapudi, Nalini
AU - Battineni, Gopi
AU - Amenta, Francesco
N1 - Publisher Copyright:
© 2020
PY - 2020/6
Y1 - 2020/6
N2 - 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.
AB - 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.
KW - ARIMA
KW - COVID-19 outbreak
KW - Forecasting
KW - Italian population
KW - Lock down
UR - https://www.scopus.com/pages/publications/85083335691
U2 - 10.1016/j.jmii.2020.04.004
DO - 10.1016/j.jmii.2020.04.004
M3 - Article
C2 - 32305271
AN - SCOPUS:85083335691
SN - 1684-1182
VL - 53
SP - 396
EP - 403
JO - Journal of Microbiology, Immunology and Infection
JF - Journal of Microbiology, Immunology and Infection
IS - 3
ER -