DOI: https://doi.org/10.14710/medstat.13.2.170-181

SUSCEPTIBLE INFECTED RECOVERED (SIR) MODEL FOR ESTIMATING COVID-19 REPRODUCTION NUMBER IN EAST KALIMANTAN AND SAMARINDA

*Sifriyani Sifriyani orcid scopus  -  Study Program of Statistics, Department of Mathematics, Mulawarman University, Indonesia
Dedi Rosadi orcid scopus  -  Department of Mathematics, Gadjah Mada University, Indonesia
Open Access Copyright (c) 2020 MEDIA STATISTIKA under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Modeling and analysis of Covid-19 data, especially on the modeling the spread and the prediction of the total number of cases for Indonesian data, has been conducted by several researchers. However, to the best of our knowledge, it has not been studied specifically for East Kalimantan Province data. The study of the data on the level of provincial and District/City level could help the government in making policies. In this study, we estimate the Covid-19 reproduction number, calculate the rate of recovery, the rate of infection, and the rate of death of East Kalimantan Province and Samarinda City. We also provide a prediction of the peak of the infection cases and forecast the total incidence of Covid-19 cases until the end of 2020. The model used in this research is the Susceptible Infected Recovered (SIR) model and the data used in the study was obtained from the East Kalimantan Public Health Office.
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Keywords: COVID-19; Estimate; SIR; Simulation; Reproduction

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  1. Diekmann, O., Heesterbeek, H. & Britton, T. (2012). Mathematical Tools for Understanding Infectious Disease Dynamics. doi: 10.23943/princeton/9780691155395.001.0001
  2. Duffy, D. G. (2016). Advanced Engineering Mathematics with Matlab. BMC Bioinformatics
  3. Dinas Kesehatan Provinsi Kalimantan Timur. Accessed May 30, 2020. Data Kasus Covid-19 yang Terkonfirmasi. URL: https://dinkes.kaltimprov.go.id/
  4. Gaspersz, V. (2014). ISO 9001: 2000 and Continual Quality Improvement. Jakarta: Gramedia Pustaka Utama
  5. Gugus Tugas Percepatan Penanganan Covid -19. Accessed June 11, 2020. Kasus Positif Covid-19 Melesat Naik 1.241, Total 34.316. URL: https://covid19.go.id/p/ berita/kasus-positif-Covid-19-melesat-naik-1241-total-34316
  6. Grohskopf, L. et al. (2011). Prevention and Control of Influenza with Vaccines: Recommendations of the Advisory Committee on Immunization Practices (ACIP), 2011. American Journal of Transplantation, 11(10). doi: 10.1111/j.1600-6143.2011.03793.x
  7. Hethcote, H. W. (2000). Mathematics of Infectious Diseases. SIAM Review, 42(4), pp. 599–653. doi: 10.1137/S0036144500371907
  8. Howell, R. D., Bates, D. M. & Watts, D. G. (1990). Nonlinear Regression Analysis & Its Application. Journal of Marketing Research, 27(1). doi: 10.2307/3172558
  9. Karim, M. A. et al. (2018). Solving a Parameter Estimation Problem of Goodwin Model With Fuzzy Initial Values. Far East Journal of Mathematical Sciences (FJMS), 107(2). doi: 10.17654/ms107020321
  10. Karim, M. A. & Gunawan, A. Y. (2020). Parameter Estimations of Fuzzy Forced Duffing Equation: Numerical Performances by the Extended Runge-Kutta Method. Abstract and Applied Analysis, 2020, pp. 1–9. doi: 10.1155/2020/6179591
  11. Keviczky, L. et al. (2019). Introduction to MATLAB. Advanced Textbooks in Control and Signal Processing. doi: 10.1007/978-981-10-8321-1_1
  12. Sifriyani et al. (2018). Development of Nonparametric Geographically Weighted Regression using Truncated Spline Approach. Songklanakarin Journal of Science and Technology, 40(4). doi: 10.14456/sjst-psu.2018.98
  13. Sifriyani, R. & Susanty, F. H. (2019). Evaluation of Forest Productivity and Governance on the Preservation of Tropical Rain Forests in Kalimantan using the NGWR-TS Nonparametric Geospatial Method’, EurAsian Journal of BioSciences, 13(2)
  14. Wallinga, J. (2004). Wallinga and Teunis Respond to “Real-Time Tracking of Infection Control Measures”. American Journal of Epidemiology, 160(6). doi: 10.1093/aje/kwh257
  15. Yulida, Y. and Karim, M. A. (2020). Pemodelan Matematika Penyebaran COVID-19 di Provinsi Kalimantan Selatan. Jurnal Binawakya, 14(10)

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