Model Matematika SEIPRS Penyebaran Penyakit Pneumonia dengan Pengaruh Vaksinasi dan Pengobatan

Authors

  • Muhammad Afrizal Beta Program Studi Matematika, Universitas Negeri Gorontalo
  • Karmila Mokoginta Program Studi Matematika, Universitas Negeri Gorontalo
  • Ana Nadiyyah Program Studi Matematika, Universitas Negeri Gorontalo

DOI:

https://doi.org/10.55657/rmns.v1i1.6

Keywords:

Pneumonia, Mathematical Model, Vaccination, Basic Reproduction Number, Treatment

Abstract

Pneumonia is an infection or acute inflammation located in the lung tissue and is caused by several microorganisms, such as bacteria, viruses, parasites, fungi and even exposure to chemicals or physical damage. In this article, we discuss the SEIPRS mathematical model on the spread of pneumonia. The SEIPRS mathematical model is formed from five interacting populations, namely the Susceptible population is healthy individuals but susceptible to pneumonia which is denoted by S, the Exposed population is latent individuals or exposed to pneumonia which is denoted by E, the Infected population is individuals infected with pneumonia which is denoted by I, and the treatment population is infected individuals who are given treatment denoted by P, and the recovered population is the recovered population denoted by R. In this article, the search for equilibrium points in the SEIPRS mathematical model and stability analysis is carried out. The analysis in this model produces two equilibrium points, namely the equilibrium point without disease at the condition R0<1, the endemic equilibrium point R0>1, and the basic reproduction number (R0) as the threshold value for the spread of disease. In this study, simulations were carried out with variations in parameter values ​​to see population dynamics. Population results show that increasing rates of vaccination and treatment can reduce the rate of spread of pneumonia.

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Published

20-02-2022

How to Cite

[1]
M. A. Beta, K. Mokoginta, and A. Nadiyyah, “Model Matematika SEIPRS Penyebaran Penyakit Pneumonia dengan Pengaruh Vaksinasi dan Pengobatan”, Res. Math. Nat. Sci., vol. 1, no. 1, pp. 27–38, Feb. 2022.

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