Sensitivity Analysis of Mathematical Model of Coronavirus Disease (COVID-19) Transmission
| Main Authors: | Resmawan, Resmawan, Yahya, Lailany |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang
, 2020
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| Subjects: | |
| Online Access: |
http://ejournal.uin-malang.ac.id/index.php/Math/article/view/9165 http://ejournal.uin-malang.ac.id/index.php/Math/article/view/9165/pdf http://ejournal.uin-malang.ac.id/index.php/Math/article/downloadSuppFile/9165/1241 |
Daftar Isi:
- The study was aimed to introduce a new model construction regarding the transmission of Coronavirus Disease (henceforth, COVID-19) in human population. The mathematical model was constructed by taking into consideration several epidemiology parameters that are closely identical with the real condition. The study further conducted an analysis on the model by identifying the endemicity parameters of COVID-19, i.e., the presence of disease-free equilibrium (DFE) point and basic reproduction number. The next step was to carry out sensitivity analysis to find out which parameter is the most dominant to affect the disease’s endemicity. The results revealed that the parameters η, ζse, α,, and σ in sequence showed the most dominant sensitivity index towards the basic reproduction number. Moreover, the results indicated positive index in parameters η and ζse that represented transmission chances during contact as well as contact rate between vulnerable individuals and exposed individual. This suggests that anincrease in the previous parameter value could potentially enlarge the endemicity of COVID-19. On the other hand, parameters α and σ, representing movement rate of exposedindividuals to the quarantine class and proportion of quarantined exposed individuals, showed negative index. The numbers indicate that an increase in the parameter value could decrease the disease’s endemicity. All in all, the study concludes that treatments for COVID-19 should focus onrestriction of interaction between individuals and optimization of quarantine.