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http://krishi.icar.gov.in/jspui/handle/123456789/46583| Title: | Coronavirus (COVID-19) forecasting in India: Application of ARIMA and periodic regression models |
| Other Titles: | Not Available |
| Authors: | Prasad CTB Rajamani S Dharshan HV Patil S Roy P Srikantiah C Suresh KP Raghavendra GA |
| ICAR Data Use Licennce: | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf |
| Author's Affiliated institute: | ICAR- National Institute of Veterinary Epidemiology and Disease Informatics, Bengaluru, Karnataka, India Chanre Rheumatology and Immunology Centre and Research, Bengaluru, Karnataka, India Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, KS, United States of America |
| Published/ Complete Date: | 2020-06-13 |
| Project Code: | Not Available |
| Keywords: | ARIMA Model Autocorrelation COVID-19 Disease forecast Periodic regression Prediction |
| Publisher: | ScienSage |
| Citation: | Prasad CTB, Rajamani S, Dharshan, HV, Patil S, Roy P, Srikantiah C, Suresh KP and Raghavendra GA. (2020). Coronavirus (COVID-19) forecasting in India: Application of ARIMA and periodic regression models. International Journal of Advanced Scientific Research. 5(1): 24-28. |
| Series/Report no.: | Not Available; |
| Abstract/Description: | Coronavirus disease, COVID-19 is the deadliest pandemic, which has affected most of the countries worldwide. Disease outbreak analysis has become a priority for the Government to take healthcare measures in reducing the impact of this pandemic. In this study, we attempt to analyse the disease outbreak data collected from 4th March 2020 to 26th May 2020 in India. Auto Regressive Integrated Moving Average (ARIMA) and Periodic Regression models were employed to predict the epidemiological trend of the incidence and probable number of new cases for the next ninety days for COVID-19 in India. The total number of probable daily new cases would be increased in the future as predicted by both ARIMA and Periodic regression models. Both ARIMA and Periodic regression models are best fitted to the observed data on daily incidence of COVID-19 in India. Incidence of COVID-19 expected to increase in next ninety days allowing to employ the stringent infection control measures such as public awareness and social distancing for effective mitigation and spread of disease in India. |
| Description: | Not Available |
| ISSN: | 2456-0421 |
| Type(s) of content: | Research Paper |
| Sponsors: | Not Available |
| Language: | English |
| Name of Journal: | International Journal of Advanced Scientific Research |
| Journal Type: | National Journal |
| Volume No.: | 5(1) |
| Page Number: | 24-28 |
| Name of the Division/Regional Station: | Not Available |
| Source, DOI or any other URL: | http://www.allscientificjournal.com/archives/2020/vol5/issue1/5-3-18 |
| URI: | http://krishi.icar.gov.in/jspui/handle/123456789/46583 |
| Appears in Collections: | AS-NIVEDI-Publication |
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