Global sensitivity analysis of COVID-19 mathematical model | Zendy

Zizhen Zhang | Zendy; Raheem Gul | Zendy; Anwar Zeb | Zendy

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Global sensitivity analysis of COVID-19 mathematical model

Author(s) -

Zizhen Zhang,

Raheem Gul,

Anwar Zeb

Publication year - 2020

Publication title -

alexandria engineering journal

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.584

H-Index - 58

eISSN - 2090-2670

pISSN - 1110-0168

DOI - 10.1016/j.aej.2020.09.035

Subject(s) - sobol sequence , covid-19 , ranking (information retrieval) , computer science , sensitivity (control systems) , control (management) , key (lock) , econometrics , pandemic , risk analysis (engineering) , operations research , mathematics , engineering , machine learning , artificial intelligence , business , medicine , computer security , disease , pathology , electronic engineering , infectious disease (medical specialty)

In this paper, we applied the Sobol’s method on an already existing mathematical model of coronavirus disease 2019 (covid-19). The objectives of this research work are to study the individual effects of involved parameters as well as combine (mutual) effects of parameters on output variables of covid-19 model. The study is also useful to identify the ranking of key model parameters and factors fixing. The ultimate goal is to identify the controlling parameters, which eventually will help decision makers to explore various policy options to control the covid-19 pandemic. For this purpose, first we present the model with its basic properties that are positivity and existence of solution. Then use the Sobol’s method to discuss the individual effects of involved parameters as well as combine (mutual) effects of parameters on output variables of covid-19 model. Finally, we present the results, discussions and concluding remarks about key model parameters and identifying the controlling parameters, which eventually will help decision makers to explore various policy options to control the covid-19 pandemic.

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