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http://krishi.icar.gov.in/jspui/handle/123456789/46584
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Thyagaraju BPC | en_US |
dc.contributor.author | Gowda S | en_US |
dc.contributor.author | Patil S | en_US |
dc.contributor.author | Srikantiah C | en_US |
dc.contributor.author | Suresh KP | en_US |
dc.date.accessioned | 2021-04-22T04:20:34Z | - |
dc.date.available | 2021-04-22T04:20:34Z | - |
dc.date.issued | 2020-10-01 | - |
dc.identifier.citation | Thyagaraju BPC, Gowda S, Patil S, Srikantiah C and Suresh KP. (2020). Future trends of COVID-19 disease outbreak in different states in India: a periodic regression analysis. Highlights in Bioscience, 3: 1-6. doi:10.36462/H. BioSci.20224. | en_US |
dc.identifier.issn | 2682-4043 | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/46584 | - |
dc.description | Not Available | en_US |
dc.description.abstract | COVID-19 (Coronavirus disease 19) is the deadliest pandemic, and by August 2, >18.2 million population worldwide were infected with SARS-CoV-2 virus causing burden on human life and economic loss. Disease outbreak analysis has become a priority for the Indian government to initiate necessary healthcare measures in lowering the impact of this deadly pandemic viral disease. In this study, time series data for COVID-19 disease was extracted from the website www.covid19india.org, analysed by using periodic regression model, the expected number of cases till 02 October 2020 was predicted and to develop a stochastic models using periodic regression in the top 15 highly infected states in India. The analysis reported increasing pattern at initial days of prediction and showed a decreasing trend for the number of reporting cases, which may reduce in future days for states like West Bengal, Karnataka, Uttar Pradesh, Bihar, Telangana, Assam and Odisha. However, for the states of Maharashtra, Tamil Nadu, Gujarat, Rajasthan, Haryana and Madhya Pradesh, showed a rapid phase of increase in disease outbreak that is likely to infect more population and indicates the pandemic nature of this disease over a period. Presently, Delhi shows a drastic reduction in the number of cases, that may increase in the future, which can be controlled if appropriate preventive measures are followed strictly and effectively. Our model highlights that continuous and constant efforts are needed for the prevention of new infections of the disease in all states that helps to effectively mitigate the disease and to allocate scarce resources effectively in the future that could improve the economic wealth in India. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | International Library of Science | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | COVID-19 | en_US |
dc.subject | Disease | en_US |
dc.subject | Outbreaks | en_US |
dc.subject | Periodic regression | en_US |
dc.subject | SARS-CoV-2 | en_US |
dc.title | Future trends of COVID-19 disease outbreak in different states in India: a periodic regression analysis | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Highlights in Bioscience | en_US |
dc.publication.volumeno | 3 | en_US |
dc.publication.pagenumber | 1-6 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | http://highlightsin.org/index.php/bioscience/article/view/69 | en_US |
dc.publication.authorAffiliation | ICAR- National Institute of Veterinary Epidemiol- ogy and Disease Informatics, Bengaluru, Karnataka, India | en_US |
dc.publication.authorAffiliation | Chanre Rheumatology and Immunology Centre and Research, Bengaluru, Karnataka, India | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | International Journal | en_US |
Appears in Collections: | AS-NIVEDI-Publication |
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