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Forecasting the dynamics of COVID-19 Pandemic in Top 15 countries in April 2020: ARIMA Model with Machine Learning Approach | |
Chintan Nanda Meenu Rani Jamal Rahmani Himangshu Kalita Akshaya Srikanth Bhagavathula Shashikanta Patairiya Pavan Kumar Yagya Datt Sharma | |
Novel Coronavirus | |
Acceso Abierto | |
Atribución-NoComercial-SinDerivadas | |
10.1101/2020.03.30.20046227 | |
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). 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. 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. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement None ### Author Declarations All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All the data was obtained from the open-source repository | |
Cold Spring Harbor Laboratory Press | |
2020 | |
Preimpreso | |
https://www.medrxiv.org/content/10.1101/2020.03.30.20046227v2 | |
Inglés | |
VIRUS RESPIRATORIOS | |
Aparece en las colecciones: | Artículos científicos |
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