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Integration of Kalman filter in the epidemiological model: A robust approach to predict COVID-19 outbreak in Bangladesh

Author

Listed:
  • Md. Shariful Islam

    (Department of Mathematics and Physics, North South University, Bashundhara, Dhaka 1229, Bangladesh)

  • Md. Enamul Hoque

    (Computational Physics Group, Department of Physics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh)

  • Mohammad Ruhul Amin

    (Computer and Information Science, Fordham University, New York, USA)

Abstract

As one of the most densely populated countries in the world, Bangladesh has been trying to contain the impact of a pandemic like coronavirus disease 2019 (COVID-19) since March, 2020. Although government announced an array of restricted measures to slow down the diffusion in the beginning of the pandemic, the lockdown has been lifted gradually by reopening all the industries, markets and offices with a notable exception of educational institutes. As the physical geography of Bangladesh is highly variable across the largest delta, the population of different regions and their lifestyle also differ in the country. Thus, to get the real scenario of the current pandemic and a possible second wave of COVID-19 transmission across Bangladesh, it is essential to analyze the transmission dynamics over the individual districts. In this paper, we propose to integrate the Unscented Kalman Filter (UKF) with classic SIRD model to explain the epidemic evolution of individual districts in the country. We show that UKF-SIRD model results in a robust prediction of the transmission dynamics for 1–4 months. Then we apply the robust UKF-SIRD model over different regions in Bangladesh to estimates the course of the epidemic. Our analysis demonstrates that in addition to the densely populated areas, industrial areas and popular tourist spots will be in the risk of higher COVID-19 transmission if a second wave of COVID-19 occurs in the country. In the light of these outcomes, we also provide a set of suggestions to contain the future pandemic in Bangladesh.

Suggested Citation

  • Md. Shariful Islam & Md. Enamul Hoque & Mohammad Ruhul Amin, 2021. "Integration of Kalman filter in the epidemiological model: A robust approach to predict COVID-19 outbreak in Bangladesh," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 32(08), pages 1-16, August.
    • Handle: RePEc:wsi:ijmpcx:v:32:y:2021:i:08:n:s0129183121501084
    DOI: 10.1142/S0129183121501084
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    Cited by:

    1. Lazebnik, Teddy, 2023. "Computational applications of extended SIR models: A review focused on airborne pandemics," Ecological Modelling, Elsevier, vol. 483(C).

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