A Data Driven Model for Prediction of COVID-19 Outbreak in Bangladesh

Authors

  • Tapan Kumar Roy Professor, Department of Population Science and Human Resource Development, University of Rajshahi, Rajshahi, Bangladesh
  • Brijesh P Singh Associate Professor, Department of Statistics, Institute of Science, Banaras Hindu University, Varanasi, India

DOI:

https://doi.org/10.3329/bjid.v7i1.48673

Keywords:

Covid-19; pandemic; mathematical model

Abstract

COVID-19 disease due to Corona virus of type SARS-CoV-2 has emerged from Wuhan, China in December 2019 and now it has expanded through infection all over the world. Now-a-days, this is a disaster pandemic for almost every nation in the earth. Such novel Corona virus impacts on every country in the world without regarding country's race, nationality and economic status. In this study, an attempt has been made to propose a data driven model to know the present and future Corona virus situation of Bangladesh. It also predicts the cumulative infected people, disease propagation, doubling time and new cases of COVID-19 patients. The result shows that more than two lakh fifty thousand people will be infected by Corona virus and its effect will start to decrease by the mid of July and decline to disappear by the end of August. This study will help policy makers to take plan for healthcare system and management of various aspects related to the control and prevention of Corona virus outspread in Bangladesh.

Bangladesh Journal of Infectious Diseases 2020;7(1):22-26

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Published

2020-08-21

How to Cite

Roy, T. K., & Singh, B. P. (2020). A Data Driven Model for Prediction of COVID-19 Outbreak in Bangladesh. Bangladesh Journal of Infectious Diseases, 7(1), 22–26. https://doi.org/10.3329/bjid.v7i1.48673

Issue

Vol. 7 No. 1 (2020)

Section

Short Communication

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Copyright on any research article in the Bangladesh Journal of Infectious Diseases is retained by the author(s).

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Articles in the Bangladesh Journal of Infectious Diseases are Open Access articles published under the Creative Commons CC BY-NC License (https://creativecommons.org/licenses/by-nc/4.0/)

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