Sains Malaysiana 50(11)(2021): 3439-3453

http://doi.org/10.17576/jsm-2021-5011-26

The Transmission Dynamic of the COVID 19 Outbreak: A Predictive Dashboard

(Dinamik Penyebaran Wabak COVID 19: Suatu Ramalan Papan Pemuka)

MUHAMMAD FAHMI BIN AHMAD ZUBER¹, NORHAYATI ROSLI¹* & NORYANTI MUHAMMAD^1,2

¹Centre for Mathematical Sciences, College of Computing, Universiti Malaysia Pahang, 26300 Gambang, Kuantan, Pahang Darul Makmur, Malaysia

²Centre of Excellence for Data Science & Artificial Intelligence, Universiti Malaysia Pahang, Lebuhraya Tun Razak, 26300 Gambang, Kuantan, Pahang Darul Makmur, Malaysia

Received: 22 April 2021/Accepted: 21 September 2021

ABSTRACT

COVID 19 outbreak gives a great impact worldwide. The disaster of this pandemic has resulted in a large number of human lives being lost. As all countries implemented quarantine and social distancing, the great lockdown all over the world lead to multiple crises including health, economy, financial, and collapse in industrial and educational activities. Movement Control Order (MCO) and social distancing which have been implemented as control measures in Malaysia also affected many sectors. The landscape now has successfully reduced the number of infected people. However, from the economic point of view, the Retail Group Malaysia (RGM) has projected the country’s retail industry suffers a negative growth rate for the first time in 22 years. If the epidemic continues, society will reach an impasse, a time when the lockdown will become more than some of them can tolerate. As recognized by the World Health Organization (WHO), modelling the outbreak based on the prior input data is more appropriate than the ‘risk of bias’ for decision-makers. Thus, this research is conducted to model the outbreak of the disease using the susceptible-infected-recovery-death (SIRD) compartmental model accompanying with the varying infection rate due to changes in MCO measures. The model assumes under the unavailability of the vaccine, recovered people can be reinfected. The epidemic parameters and reproduction numbers are estimated and fitted from the transmission model to the actual data using the Monte Carlo Markov Chain (MCMC) of Metropolis-Hasting. The model is solved using a numerical algorithm of the Runge-Kutta method. The predictive dashboard of a graphical user interface (GUI) is developed, hence monitoring and predicting the outbreak under the control measures of the two different types of MCO scenarios (which are called constant and alternate scenarios) can be performed. GUI for the dynamic transmission of the COVID 19 provides insight for the future outbreak, hence may help the respective stakeholders to propose the best policy of a new norm for all sectors. From the GUI, we can see that, when no or loose MCO is implemented or compliance of the public to the COVID 19 standard operating procedure (SOP), the infected case will increase rapidly up to 7.5 million. With strict MCO regulation or public obedient to the SOP, the infected case will decrease rapidly, but even after a long period of strict regulation, once the quarantine is stopped, the infected case will rise again. An alternative MCO scenario is suggested where a cyclic pattern of strict and loose MCO regulation is upheld, and it shows to flatten the curve while allow periods of less restricted lifestyle. This can be one of the alternatives to balance the life and livelihood.

Keywords: COVID 19; modelling; Monte Carlo Markov Chain; reproduction number; Runge-Kutta

ABSTRAK

Wabak COVID 19 memberi kesan yang besar kepada seluruh dunia. Kemusnahan daripada wabak ini telah mengakibatkan banyak kematian. Semua negara melaksanakan kuarantin, penjarakan sosial dan penutupan negara di seluruh dunia yang akhirnya menyebabkan pelbagai krisis termasuk kesihatan, ekonomi, kewangan dan kelumpuhan sektor industri serta pendidikan. Perintah Kawalan Pergerakan (MCO) dan penjarakan sosial yang telah dilaksanakan sebagai langkah kawalan di Malaysia juga mempengaruhi banyak sektor. Landskap kini berjaya mengurangkan bilangan yang dijangkiti. Namun, dari sudut ekonomi, Kumpulan Peruncitan Malaysia (RGM) telah mengunjurkan industri runcit negara kini mengalami kadar pertumbuhan negatif untuk pertama kalinya dalam tempoh 22 tahun. Sekiranya wabak ini berlanjutan, masyarakat akan menemui jalan buntu dengan penutupan pelbagai sektor tidak lagi dapat ditoleransi oleh mereka. Seperti yang diakui oleh Organisasi Kesihatan Sedunia (WHO), pemodelan berdasarkan input data yang ada adalah lebih baik daripada 'risiko pincangan' oleh pembuat keputusan tanpa menggunakan model ramalan. Oleh itu, penyelidikan ini dilakukan untuk memodelkan epidemik penyakit ini menggunakan model SIRD dengan kadar jangkitan yang berbeza-beza susulan daripada perubahan MCO. Model ini mengandaikan dengan ketiadaan vaksin, orang yang pulih dapat dijangkiti semula. Parameter epidemik dan nombor reproduksi dianggar dan disuaikan dengan data sebenar menggunakan kaedah Monte Carlo Markov Chain (MCMC) Metropolis-Hasting. Penyelesaian model dihitung menggunakan algoritma kaedah berangka Runge-Kutta. Antara muka pengguna grafikal (GUI) dibangunkan bagi peramalan epidemik mengikut dua situasi MCO yang berbeza (situasi tetap dan gantian). GUI bagi transmisi dinamik COVID 19 memberikan gambaran berkaitan keadaan wabak pada masa hadapan, seterusnya dapat membantu pihak berkepentingan untuk mengusulkan kaedah norma baharu yang terbaik bagi semua sektor. Daripada GUI, apabila tiada atau hampir tiada penguatkuasaan MCO atau ketidakpatuhan rakyat kepada prosedur operasi piawai (SOP), kes keberjangkitan meningkat sehingga mencecah 7.5 juta kes. Apabila MCO dikuatkuasakan secara ketat atau kepatuhan rakyat kepada SOP, kes akan menurun secara mendadak, tetapi walaupun setelah menjalankan kuarantin selama tempoh yang panjang, sejurus selepas kuarantin diberhentikan, kes akan meningkat sekali lagi. Suatu cadangan diketengahkan iaitu kekerasan MCO dilakukan secara berfasa berulang alik. Menggunakan kaedah ini, kes positif dapat diratakan manakala wujud tempoh dengan cara hidup yang kurang terikat dibenarkan. Ini boleh menjadi suatu alternatif bagi mengimbangi kehidupan dan punca pendapatan.

Kata kunci: COVID 19; Monte Carlo Markov Chain; nombor reproduksi; pemodelan; Runge-Kutta

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*Corresponding author; email: norhayati@ump.edu.my