An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia-Reference-Cited by-同舟云学术

An SIR epidemic model for COVID-19 spread with fuzzy parameter: the case of Indonesia

Published:2021-02-11 Issue:1 Volume:2021 Page:
ISSN:1687-1847
Container-title:Advances in Difference Equations
language:en
Short-container-title:Adv Differ Equ

Author:

Abdy Muhammad^ORCID,Side Syafruddin,Annas Suwardi,Nur Wahyuddin,Sanusi Wahidah

Abstract

AbstractThe aim of this research is to construct an SIR model for COVID-19 with fuzzy parameters. The SIR model is constructed by considering the factors of vaccination, treatment, obedience in implementing health protocols, and the corona virus-load. Parameters of the infection rate, recovery rate, and death rate due to COVID-19 are constructed as a fuzzy number, and their membership functions are used in the model as fuzzy parameters. The model analysis uses the generation matrix method to obtain the basic reproduction number and the stability of the model’s equilibrium points. Simulation results show that differences in corona virus-loads will also cause differences in the transmission of COVID-19. Likewise, the factors of vaccination and obedience in implementing health protocols have the same effect in slowing or stopping the transmission of COVID-19 in Indonesia.

Funder

PNBP Grant

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Algebra and Number Theory,Analysis

Link

http://link.springer.com/content/pdf/10.1186/s13662-021-03263-6.pdf

Reference32 articles.

1. Leon, U.A., Perez, A., Vales, E.: An SEIARD epidemic model for COVID-19 in Mexico: mathematical analysis and state-level forecast. Chaos Solitons Fractals 140, 110165 (2020)

2. Urso, D.L.: Coronavirus disease 2019 (COVID-19): a brief report. Clin. Manag. Issues 14(1), 15–19 (2020)

3. Kemenkes: https://covid19.go.id/peta-sebaran. Accessed on November 2020

4. Roosa, K., Lee, Y., Luo, R., Kirpich, A., Rothenberg, R., Hyman, J.M., Yan, P., Chowell, G.: Short-term forecasts of the COVID-19 epidemic in Guangdong and Zhejiang, China: February 13–23, 2020. J. Clin. Forensic Med. 9, 596 (2020)

5. Nuraini, N., Khairuddin, K., Apri, M.: Modeling simulation of COVID-19 in Indonesia based on early endemic data. Commun. Biomath. Sci. 3(1), 1–8 (2020)

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