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COVID-19 Risk Mitigation and Management

The COVID-19 pandemic is an unprecedented global shock, generating a massive social, human, and economic crisis. Identifying risk factors and assessing the effectiveness of containment strategies and cognitive measures are crucial to prevent the spread of COVID-19 by implementing appropriate countermeasures. This study:

  • Investigated local newspaper coverage of COVID-19 to identify key themes related to the pandemic and their discussion timeline using the Latent Dirichlet Allocation (LDA) model. Integrated the results to propose a pandemic management framework.

  • Identified demographic, economic, built environment, and facility-related risk factors influencing COVID-19 incidence rates at the district level in Bangladesh using spatial regression models.

  • Evaluated the effectiveness of various containment strategies and cognition measures to control traffic volume during the COVID-19 pandemic in Dhaka. Utilized real-time Google Maps data to calculate journey speed, serving as a proxy variable for traffic volume in the research.


  • Zafri, N. M., Afroj, S., Nafi, I. M., & Hasan, M. M. U. (2021). A content analysis of newspaper coverage of COVID-19 pandemic for developing a pandemic management framework. Heliyon, Elsevier. [DOI]

  • Zafri, N. M., Afroj, S., Ali, M. A., Hasan, M. M. U., & Rahman, M. H. (2021). Effectiveness of containment strategies and local cognition to control vehicular traffic volume in Dhaka, Bangladesh during COVID-19 pandemic: Use of Google Map based real-time traffic data. PLOS One. [DOI]

  • Rahman, M. H. *, Zafri, N. M. *, Ashik, F. R., Waliullah, M., & Khan, A. (2021). Identification of risk factors contributing to COVID-19 incidence rates in Bangladesh: A GIS-based spatial modeling approach. Heliyon, Elsevier. [DOI] [*Shared First Author]


Average daily journey speed (ADJS) by containment strategies and the month of Ramadan. (GHLDY= Declaration of general holiday, EDUCTN= Closure of educational institutions, FORCE= Deployment of force, RELIGN= Restriction on religious gathering, MALL= Closure of market and shopping mall, GRMT= Closures of garments factories, and RMDN= Month of Ramadan)


Timeline of twelve topics regarding COVID-19 from January to October 2020.

Spatial distribution of the coefficient values of urban population percentage, monthly consumption, number of health workers, and distance from the capital in describing COVID-19 incidence rates using GWR model.

Project Details

Project Timeline: 2020-2021

Project Type: Collaborative Research 

Main Team Members:

  • Niaz Mahmud Zafri, Assistant Professor, Department of Urban and Regional Planning, BUET

  • Sadia Afroj, Assistant Professor, Department of Urban and Regional Planning, BUET

  • Dr. Asif-Uz-Zaman Khan, Professor, Department of Urban and Regional Planning, BUET

  • Dr. Musleh Uddin Hasan, Professor, Department of Urban and Regional Planning, BUET

  • Fajle Rabbi Ashik, Graduate Research Assistant, Department of Geography, McGill University (Principal Investigator)

  • Md Hamidur Rahman, PhD Student in Community and Regional Planning, University of Texas at Austin

  • Imtiaz Mahmud Nafi, Department of Electrical and Electronic Engineering, Islamic University of Technology (IUT)

  • Mohammad Ashraf Ali, Department of Urban and Regional Planning, BUET

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