A new study of unreported cases of 2019-nCOV epidemic outbreaks. (September 2020)
- Record Type:
- Journal Article
- Title:
- A new study of unreported cases of 2019-nCOV epidemic outbreaks. (September 2020)
- Main Title:
- A new study of unreported cases of 2019-nCOV epidemic outbreaks
- Authors:
- Gao, Wei
Veeresha, P.
Baskonus, Haci Mehmet
Prakasha, D. G.
Kumar, Pushpendra - Abstract:
- Abstract: 2019-nCOV epidemic is one of the greatest threat that the mortality faced since the World War-2 and most decisive global health calamity of the century. In this manuscript, we study the epidemic prophecy for the novel coronavirus (2019-nCOV) epidemic in Wuhan, China by using q -homotopy analysis transform method ( q -HATM). We considered the reported case data to parameterise the model and to identify the number of unreported cases. A new analysis with the proposed epidemic 2019-nCOV model for unreported cases is effectuated. For the considered system exemplifying the model of coronavirus, the series solution is established within the frame of the Caputo derivative. The developed results are explained using figures which show the behaviour of the projected model. The results show that the used scheme is highly emphatic and easy to implementation for the system of nonlinear equations. Further, the present study can confirm the applicability and effect of fractional operators to real-world problems.
- Is Part Of:
- Chaos, solitons and fractals. Volume 138(2020)
- Journal:
- Chaos, solitons and fractals
- Issue:
- Volume 138(2020)
- Issue Display:
- Volume 138, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 138
- Issue:
- 2020
- Issue Sort Value:
- 2020-0138-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-09
- Subjects:
- Coronavirus -- Reported and unreported cases -- Epidemic mathematical model -- Caputo derivative, q-homotopy analysis transform method
Chaotic behavior in systems -- Periodicals
Solitons -- Periodicals
Fractals -- Periodicals
Chaotic behavior in systems
Fractals
Solitons
Periodicals
003.7 - Journal URLs:
- http://www.elsevier.com/journals ↗
http://www.sciencedirect.com/science/journal/09600779 ↗ - DOI:
- 10.1016/j.chaos.2020.109929 ↗
- Languages:
- English
- ISSNs:
- 0960-0779
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3129.716000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 14002.xml