Indian Journal of Science and Technology
DOI: 10.17485/ijst/2019/v12i17/115214
Year: 2019, Volume: 12, Issue: 17, Pages: 1-12
Original Article
Philemon Manliura Datilo1,2 and Zuhaimy Ismail1*
1Department of Mathematical Sciences, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Johor, Malaysia; [email protected], [email protected]
2Department of Information Technology, Modibbo Adama University of Technology, Yola Adamawa State, Nigeria
*Author for correspondence
Zuhaimy Ismail
Department of Mathematical Sciences, Universiti Teknologi Malaysia, 81310 UTM, Johor Bahru, Johor, Malaysia.
Email: [email protected]
Objectives: While studies had established standard epidemic models, variants of those standards, which define unique and characteristic behavior of some of disease amidst interventions and population dynamics, are continually developed to represent epidemic dynamics in different ways. Methods: In this study, a compartmental susceptible-susceptible quarantine-vaccinated-exposed-quarantined-infectious-hospitalized-funeral-recovered (SSQVEQIHFR) epidemic model is formulated and analyzed. Model stability was analyzed and found to be both stable for disease-freeand endemic equilibrium. Findings: In order to determine its threshold (basic reproduction number), the next generation matrix approach was applied, and was found to represented average secondary transmissions of cases in the community, hospital and at funerals during the entire period of the epidemic. A numerical simulation was used to validate the disease-free and endemic equilibrium stability of the model. Applications: In order to determine influential parameters, a forward sensitivity index analysis was carried out on the model threshold and endemic points. This model has more classes which can be used to investigate infectious diseases outbreak with such characteristic dynamics. Preventive or control measures that averts transmission in the community, hospital and at funeral will stall the growth of epidemic in the population.
Keywords: Epidemic Model, Reproduction Number, Sensitivity Analysis and Stability Model, Stability Analysis
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