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Time Series Analysis for CoVID-19 Projection in Bangladesh

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Vision, Sensing and Analytics: Integrative Approaches

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 207))

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Abstract

The coronavirus disease-19 (CoVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been spreading rapidly at different divisions in Bangladesh since April 12, 2020. As CoVID-19 is highly infectious, the national impact of this disease must be analysed. Therefore, we need to project the spread of infected cases across the country. In this chapter, we discuss different epidemic models for modeling infectious disease. After that, we apply Logistic growth model and SIR (susceptible-infectious-recovered) model to the CoVID-19 time series data publicly available online for modelling CoVID-19 epidemic in Bangladesh. Also, we project the probable ending time of the epidemic. To do this, the CoVID-19 time series data from March 17, 2020 to December 31, 2020 is analysed and after that, the projection is performed.

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Author information

Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, Jatiya Kabi Kazi Nazrul Islam University, Trishal, Mymensingh, Bangladesh

    Kawser Ahammed

  2. Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Mosabber Uddin Ahmed

Authors
  1. Kawser Ahammed
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  2. Mosabber Uddin Ahmed
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Correspondence to Kawser Ahammed .

Editor information

Editors and Affiliations

  1. Professor, Department of Electrical and Electronic Engineering, University of Dhaka, Dhaka, Bangladesh

    Md Atiqur Rahman Ahad

  2. Solutions Architect for Greenfield and Startups, Amazon Web Services, USA, Visiting Professor, Graduate School of Regional Innovation, Mie University, Tsu, Japan

    Atsushi Inoue

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Ahammed, K., Ahmed, M.U. (2021). Time Series Analysis for CoVID-19 Projection in Bangladesh. In: Ahad, M.A.R., Inoue, A. (eds) Vision, Sensing and Analytics: Integrative Approaches. Intelligent Systems Reference Library, vol 207. Springer, Cham. https://doi.org/10.1007/978-3-030-75490-7_14

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