Application of SEIR Model in COVID-19 and The Effect of Lockdown on Reducing The Number of Active Cases
Abstract
The spread of COVID-19 within a region in South East Asia has been modelled using a compartment model called SEIR (Susceptible, Exposed, Infected, Recovered). Actual number of sick people needing treatments, or the number active case data was used to obtain realistic values of the model parameters such as the reproduction number (R0), incubation, and recovery periods. It is shown that at the beginning of the pandemic where most people were still not aware, the R0 was very high as seen by the steep increase of people got infected and admitted to the hospitals. Few weeks after the lockdown of the region was in place and people were obeying the regulation and observing safe distancing, the R0 values dropped significantly and converged to a steady value of about 3. Using the obtained model parameters, fitted on a daily basis, the maximum number of active cases converged to a certain value of about 2500 cases. It is expected that in the early June 2020 that the number of active cases will drop to a significantly low level.
Keywords
Full Text:
PDFReferences
Bavdekar, V. A., & Mesbah, A. (2016). A polynomial chaos-based nonlinear Bayesian ap-proach for estimating state and parameter probability distribution functions. https://ieeexplore.ieee.org/abstract/document/7525220, retrieved on April 17, 2020.
Chen-Charpentier, B. M., & Stanescu, D. (2010). Epidemic models with random coefficients. Mathematical and Computer Modelling, 52(7), 1004–1010.
https://covid19-scenarios.org, retrieved on April 17, 2020.
http://virological.org/t/epidemiological-data-from-the-ncov-2019-outbreak-early-descriptions-from-publicly-available-data/337/3, retrieved on April 17, 2020.
https://www.who.int/news-room/detail/30-01-2020-statement-on-the-second-meeting-of-the-international-health-regulations-(2005)-emergency-committee-regarding-the-outbreak-of-novel-coronavirus-(2019-ncov), retrieved on April 17, 2020
https://www.who.int/dg/speeches/detail/who-director-general-s-remarks-at-the-media-briefing-on-2019-ncov-on-11-february-2020, retrieved on April 17, 2020
Fang, Y., Nie, Y., & Penny, M. (2020). Transmission dynamics of the COVID‐19 outbreak and effectiveness of government interventions: A data‐driven analysis. Journal of Medical Virology, 92(6), 645-659.
Harman, D. B., & Johnston, P. R. (2016). Applying the stochastic Galerkin method to epidem-ic models with uncertainty in the parameters. Mathematical Biosciences, 277, 25–37.
Kucharski, A. J., Russell, T. W., Diamond, C., Liu, Y., Edmunds, J., Funk, S., & Davies, N. (2020). Early dynamics of transmission and control of COVID-19: a mathematical mod-elling study. The Lancet Infectious Diseases, 20(5), 553-558.
Leung, K., Wu, J. T., Liu, D., & Leung, G. M. (2020). First-wave COVID-19 transmissibility and severity in China outside Hubei after control measures, and second-wave scenario planning: a modelling impact assessment. The Lancet, 395(10233), 1382-1393
Prem, K., Liu, Y., Russell, T. W., Kucharski, A. J., Eggo, R. M., Davies, N., & Abbott, S. (2020). The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study. The Lancet Public Health, 5(5), e261-e270
Putra, Z. A. (2016). Use of Process Simulation for Plant Debottlenecking. Indonesian Journal of Science and Technology, 1(1), 74-81.
Santonja, F., & Chen-Charpentier, B. (2012). Uncertainty quantification in simulations of epi-demics using polynomial chaos. Computational and Mathematical Methods in Medi-cine, 2012, 1-8.
Wang, H., Wang, Z., Dong, Y., Chang, R., Xu, C., Yu, X., & Cai, Y. (2020). Phase-adjusted esti-mation of the number of Coronavirus Disease 2019 cases in Wuhan, China. Cell Discov-ery, 6(1), 1–8.
Zhao, S., & Chen, H. (2020). Modeling the epidemic dynamics and control of COVID-19 out-break in China. Quantitative Biology, 8(1), 11–19.
DOI: https://doi.org/10.17509/ijost.v5i2.24432
Refbacks
- There are currently no refbacks.
Copyright (c) 2020 Indonesian Journal of Science and Technology
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Indonesian Journal of Science and Technology is published by UPI.
View My Stats