Modeling the effect of contaminated objects for the transmission dynamics of COVID-19 pandemic with self protection behavior changes
Author(s) -
Kassahun Getnet Mekonen,
Tatek Getachew Habtemicheal,
Shiferaw Feyissa Balcha
Publication year - 2020
Publication title -
results in applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.524
H-Index - 3
eISSN - 2590-0382
pISSN - 2590-0374
DOI - 10.1016/j.rinam.2020.100134
Subject(s) - basic reproduction number , equilibrium point , transmission (telecommunications) , population , stability theory , epidemic model , stability (learning theory) , ordinary differential equation , mathematics , control theory (sociology) , nonlinear system , pandemic , statistics , computer science , econometrics , covid-19 , differential equation , disease , control (management) , infectious disease (medical specialty) , physics , mathematical analysis , artificial intelligence , environmental health , telecommunications , medicine , quantum mechanics , pathology , machine learning
A mathematical model for the transmission dynamics of Coronavirus diseases (COVID-19) is proposed using a system of nonlinear ordinary differential equations by incorporating self protection behavior changes in the population. The disease free equilibrium point is computed, and both the local and global stability analysis was performed. The basic reproduction number (R0) of the model is computed using the method of next generation matrix. The disease free equilibrium point is locally asymptotically and globally stable under certain conditions. Based on the available data, the unknown model parameters are estimated using a combination of least square and Bayesian estimation methods for different countries. The forward sensitivity index is applied to determine and identify the key model parameters for the spread of disease dynamics. The sensitive parameters for the spread of the virus vary from country to country. We found out that the reproduction number depends mostly on the infection rates, the threshold value of the force of infection for a population, the recovery rates, and the virus decay rate in the environment. It illustrates that control of the effective transmission rate (recommended human behavioral change towards self-protective measures) is essential to stop the spreading of the virus. Numerical simulations of the model were performed to supplement and verify the effectiveness of the analytical findings.
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