Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Apr 3, 2020
Date Accepted: May 10, 2020
Date Submitted to PubMed: May 11, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020: ARIMA Model with Machine Learning Approach
ABSTRACT
Background:
Mathematical approaches are widely used to infer critical epidemiological transitions and parameters of COVID-19.
Objective:
We here predicted some trajectories of COVID-19 in the coming days (until April 30, 2020) using the most advanced Auto-Regressive Integrated Moving Average Model (ARIMA).
Methods:
We used different statistical phenomenological models in the R-language platform to analyze the disease-based trajectories model for prediction purposes
Results:
Our analysis predicted very frightening outcomes, which defines to worsen the conditions in Iran, entire Europe, especially Italy, Spain, and France. While South Korea, after the initial blast, has come to stability, the same goes for the COVID-19 origin country China with more positive recovery cases and confirm to remain stable. The United States of America (USA) will come as a surprise and going to become the epicenter for new cases during the mid-April 2020.
Conclusions:
Based on our predictions, public health officials should tailor aggressive interventions to grasp the power exponential growth, and rapid infection control measures at hospital levels are urgently needed to curtail the COVID-19 pandemic.
Citation
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Copyright
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