Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/10816
Title: MODELING DISEASE TRANSMISSION DYNAMICS WITH RANDOM DATA AND HEAVY TAILED RANDOM EFFECTS: THE ZIKA CASE
Authors: Bekiryazici, Z.
Kesemen, T.
Merdan, M.
Khaniyev, T.
Keywords: Pareto Distribution
Random Differential Equation
Random Effect
Simulation
Zika Virus
Issue Date: 2023
Publisher: Isik University
Abstract: In this study, we investigate a compartmental model of Zika Virus transmission under random effects. Random effects enable the analysis of random numerical characteristics of transmission, which cannot be modeled through deterministic equations. Data obtained from Zika studies in the literature are used along with heavy tailed random effects to obtain new random variables for the parameters of the deterministic model. Finally, simulations of the model are carried out to analyze the random dynamics of Zika Virus transmission. Deterministic results are compared with results from the simulations of the random system to underline the advantages of a random modeling approach. It is shown that the random model provides additional results for disease transmission dynamics such as results for standard deviation and coefficients of variation, making it a valuable alternative to deterministic modeling. Random results suggest around 90% - 120% coefficient of variation for the random model underlining the fact that the randomness should not be ignored for the transmission of this disease. © Işık University, Department of Mathematics, 2023; all rights reserved.
URI: https://hdl.handle.net/20.500.11851/10816
ISSN: 2146-1147
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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