Numerical Approximation for the Solution of COVID-19 Pandemic Model
| dc.contributor.author | Fariha Nawaz | |
| dc.contributor.author | FA19-RMT-106 | |
| dc.contributor.author | Dr. Sadia Arshad | |
| dc.contributor.author | LHR TP 7393 | |
| dc.date.accessioned | 2026-05-05T13:06:41Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Many mathematical models give different strategy for controlling specific diseases. The method of constructing a mathematical model is known as mathematical modelling. Fin- ishing the global disease lacks the use of different measures, such as civil separation, inter- action, and screening. we construct various models to predict the progression of COVID- 19 infection using data from Tunisia and Wuhan in fractional order ν. This epidemiologic analysis model suggests how we may predict the spread of COVID-19 by applying the basic reproduction number R0. The susceptibility of threshold number R0 regarding the frame- work of the epidemic model. R0 can be calculated from different approximative methods in COVID-19 epidemic models. The global elements of equilibria, positivity, boundedness, and stability analysis are all given particular attention. For stability if R0 < 1, an infected person transfer the disease individually in new infected is less than one on average over the lifetime of its infectious time, and the infection cannot spread, while R0 > 1 then disease transfer from each infected person to more than one new infection on average and system will unstable. Using Adams-Bashforth-Moulton method, we get numerical result of the proposed model. In graphical work, we compare actual results with approximate solutions. | |
| dc.identifier.uri | https://repository.cuilahore.edu.pk/123456789/3839 | |
| dc.language.iso | en | |
| dc.publisher | Library Information Services, COMSATS University Islamabad, Lahore Campus | |
| dc.relation.ispartofseries | LHR TP 7393 | |
| dc.subject | Department of Mathematics | |
| dc.subject | FA19 | |
| dc.subject | Mathematics | |
| dc.subject | COVID-19 Model | |
| dc.subject | Numerical Approximation | |
| dc.subject | Epidemiological Model | |
| dc.subject | Dr. Sadia Arshad | |
| dc.title | Numerical Approximation for the Solution of COVID-19 Pandemic Model | |
| dc.type | Thesis |