Scientific Reports (Dec 2020)

Tracking the early depleting transmission dynamics of COVID-19 with a time-varying SIR model

  • Kian Boon Law,
  • Kalaiarasu M. Peariasamy,
  • Balvinder Singh Gill,
  • Sarbhan Singh,
  • Bala Murali Sundram,
  • Kamesh Rajendran,
  • Sarat Chandra Dass,
  • Yi Lin Lee,
  • Pik Pin Goh,
  • Hishamshah Ibrahim,
  • Noor Hisham Abdullah

DOI
https://doi.org/10.1038/s41598-020-78739-8
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 11

Abstract

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Abstract 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, $$\beta_{t}$$ β t and 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.