Estimasi angka reproduksi Novel Coronavirus (COVID-19), Kasus Indonesia (Estimation of COVID-19 reproductive number, case of Indonesia

Fajar, Muhammad (2020): Estimasi angka reproduksi Novel Coronavirus (COVID-19), Kasus Indonesia (Estimation of COVID-19 reproductive number, case of Indonesia.

Abstract

The purpose of this study is to estimate the COVID-19 reproduction rate, vaccination coverage and forecast the next 20 days, which is useful as an anticipatory step for the COVID-19 pandemic. The benefits of research as a consideration in efforts to stop the spread of COVID-19. The method used in the study is the SIR model, exponential growth rate, maximum likelihood, time-dependent, and sequential bayesian to estimate COVID-19 reproduction rates, and to forecast using extreme learning machines (ELM). The data used in this study is the cumulative number of individual (cases) confirmed positive COVID-19 sourced from www.covid19.go.id. This study produced several conclusions, including: (1) that the R_0 value was 1.728 (> 1) and the R_1value ranged from 2.892 to 5.667 (> 1), meaning that the number of individuals infected with COVID-19 would increase until one day it would reach a stable point, (2) The number of individuals vaccination (if experts find COVID-19 vaccine) based on R_0 (V_(R_0 ) ) is 42.145%, and vaccination coverage based on R (V_R ) from four methods ranges from 75% to 86%, and (3) forecasting results for the next 20 days using ELM, obtained information that the number of cases will continue to increase to the point where the cumulative movement of the individual (cases) confirmed COVID-19 is stable (no trend).

Tujuan studi ini adalah untuk mengestimasi angka reproduksi COVID-19, cakupan vaksinasi dan melakukan peramalan 20 hari kedepan, yang berguna sebagai untuk langkah antisipasi pandemik COVID-19. Manfaat penelitian sebagai bahan pertimbangan dalam upaya menghentikan penyebaran COVID-19. Metode yang digunakan dalam penelitian adalah model SIR, exponential growth rate, maximum likelihood, time dependent, dan bayesian sequential untuk mengestimasi angka reproduksi COVID-19, dan untuk peramalan menggunakan extreme learning machine (ELM). Adapun data yang digunakan dalam penelitian adalah data jumlah kumulatif individu (kasus) terkonfirmasi positif COVID-19 yang bersumber dari www.covid19.go.id. Penelitian ini menghasilkan beberapa kesimpulan antara lain: (1) bahwa nilai R_0 adalah 1.728 (> 1) dan nilai R berkisar antara 2.892 hingga 5.667 (> 1), artinya bahwa jumlah individu terinfeksi COVID-19 akan semakin meningkat hingga suatu saat nanti akan mencapai titik stabil, (2) Banyaknya individu yang perlu dilakukan vaksinasi (jika para ahli menemukan vaksin COVID-19) berdasarkan R_0 (V_(R_0 ) ) adalah sebesar 42.145%, dan cakupan vaksinasi berdasarkan R (V_R )dari empat metode berkisar antara 75% hingga 86%, dan (3) hasil peramalan untuk 20 hari ke depan dengan menggunakan ELM, diperoleh informasi bahwa jumlah kasus ini akan terus meningkat sampai pada titik dimana pergerakan jumlah kumulatif individu (kasus) terkonfirmasi COVID-19 stabil (tidak ada trend).

• Item Type: MPRA Paper
• English Title: ESTIMATION OF COVID-19 REPRODUCTIVE NUMBER (CASE OF INDONESIA)
• Language: Indonesian
• Keywords: COVID-19, angka reproduksi, cakupan vaksinasi, peramalan.
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General; C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General; I - Health, Education, and Welfare > I1 - Health > I19 - Other

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