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All Journal International Journal of Electrical and Computer Engineering
Ni'matut Tamimah
Shipbuilding Institute of Polytechnic Surabaya
Computer Science & IT Electrical & Electronics Engineering

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The susceptible-infected-recovered-dead model for long-term identification of key epidemiological parameters of COVID-19 in Indonesia Muhammad Achirul Nanda; Anifatul Faricha; Siti Maghfirotul Ulyah; Ni'matut Tamimah; Enny Indasyah; Muhammad Falahudin Malich Salaz; Qurrotun 'Ayun Mawadatur Rohmah; Ulfah Abqari
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i3.pp2900-2910

Abstract

The COVID-19 epidemic has spread massively to almost all countries including Indonesia, in just a few months. An important step to overcoming the spread of the COVID-19 is understanding its epidemiology through mathematical modeling intervention. Knowledge of epidemic dynamics patterns is an important part of making timely decisions and preparing hospitals for the outbreak peak. In this study, we developed the susceptible-infected-recovered-dead (SIRD) model, which incorporates the key epidemiological parameters to model and estimate the long-term spread of the COVID-19. The proposed model formulation is data-based analysis using public COVID-19 data from March 2, 2020 to May 15, 2021. Based on numerical analysis, the spread of the pandemic will begin to fade out after November 5, 2021. As a consequence of this virus attack, the cumulative number of infected, recovered, and dead people were estimated at ≈ 3,200,000, ≈ 3,437,000 and ≈ 63,000 people, respectively. Besides, the key epidemiological parameter indicates that the average reproduction number value of COVID-19 in Indonesia is 7.32. The long-term prediction of COVID-19 in Indonesia and its epidemiology can be well described using the SIRD model. The model can be applied in specific regions or cities in understanding the epidemic pattern of COVID-19.
Co-Authors Anifatul Faricha Indasyah, Enny Muhammad Falahudin Malich Salaz Nanda, Muhammad Achirul Qurrotun 'Ayun Mawadatur Rohmah Siti Maghfirotul Ulyah Ulfah Abqari