TY - JOUR
AU - Law, Kian Boon
AU - Peariasamy, Kalaiarasu M.
AU - Gill, Balvinder Singh
AU - Singh, Sarbhan
AU - Sundram, Bala Murali
AU - Rajendran, Kamesh
AU - Dass, Sarat C.
AU - Lee, Yi Lin
AU - Goh, Pik Pin
AU - Ibrahim, Hishamshah Mohd
AU - Abdullah, Noor Hisham
PY - 2020
DA - December
TI - Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model
JO - Scientific Reports
VL - 10
DO - https://doi.org/10.1038/s41598-020-78739-8
AB - The susceptible-infectious-removed (SIR) model offers the simplest framework to study transmission dynamics of COVID-19, however, it does not factor in its early depleting trend observed during a lockdown. We modified the SIR model to specifically simulate the early depleting transmission dynamics of COVID-19 to better predict its temporal trend in Malaysia. The classical SIR model was fitted to observed total (I total), active (I) and removed (R) cases of COVID-19 before lockdown to estimate the basic reproduction number. Next, the model was modified with a partial time-varying force of infection, given by a proportionally depleting transmission coefficient, βtand a fractional term, z. The modified SIR model was then fitted to observed data over 6 weeks during the lockdown. Model fitting and projection were validated using the mean absolute percent error (MAPE). The transmission dynamics of COVID-19 was interrupted immediately by the lockdown. The modified SIR model projected the depleting temporal trends with lowest MAPE for I total, followed by I, I daily and R. During lockdown, the dynamics of COVID-19 depleted at a rate of 4.7% each day with a decreased capacity of 40%. For 7-day and 14-day projections, the modified SIR model accurately predicted I total, I and R. The depleting transmission dynamics for COVID-19 during lockdown can be accurately captured by time-varying SIR model. Projection generated based on observed data is useful for future planning and control of COVID-19.
PB - Springer Nature
UR - https://researchportal.hw.ac.uk/en/publications/4f3ed735-b012-40cc-ad1b-565773e7756d
KW - Coronavirus (COVID-19)
ER