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Space-Time Patterns, Change, and Propagation of COVID-19 Risk Relative to the Intervention Scenarios in Bangladesh

Author

Listed:
  • Arif Masrur

    (The GeoVISTA Center, The Pennsylvania State University, University Park, PA 16802, USA)

  • Manzhu Yu

    (The GeoVISTA Center, The Pennsylvania State University, University Park, PA 16802, USA)

  • Wei Luo

    (10 Akron Street, Cambridge, MA 02138, USA)

  • Ashraf Dewan

    (School of Earth and Planetary Sciences, Curtin University, Perth, WA 6102, Australia)

Abstract

The novel coronavirus (COVID-19) pandemic continues to be a significant public health threat worldwide, particularly in densely populated countries such as Bangladesh with inadequate health care facilities. While early detection and isolation were identified as important non-pharmaceutical intervention (NPI) measures for containing the disease spread, this may not have been pragmatically implementable in developing countries due to social and economic reasons (i.e., poor education, less public awareness, massive unemployment). Hence, to elucidate COVID-19 transmission dynamics with respect to the NPI status—e.g., social distancing—this study conducted spatio-temporal analysis using the prospective scanning statistic at district and sub-district levels in Bangladesh and its capital, Dhaka city, respectively. Dhaka megacity has remained the highest-risk “active” cluster since early April. Lately, the central and south eastern regions in Bangladesh have been exhibiting a high risk of COVID-19 transmission. The detected space-time progression of COVID-19 infection suggests that Bangladesh has experienced a community-level transmission at the early phase (i.e., March, 2020), primarily introduced by Bangladeshi citizens returning from coronavirus epicenters in Europe and the Middle East. Potential linkages exist between the violation of NPIs and the emergence of new higher-risk clusters over the post-incubation periods around Bangladesh. Novel insights into the COVID-19 transmission dynamics derived in this study on Bangladesh provide important policy guidelines for early preparations and pragmatic NPI measures to effectively deal with infectious diseases in resource-scarce countries worldwide.

Suggested Citation

  • Arif Masrur & Manzhu Yu & Wei Luo & Ashraf Dewan, 2020. "Space-Time Patterns, Change, and Propagation of COVID-19 Risk Relative to the Intervention Scenarios in Bangladesh," IJERPH, MDPI, vol. 17(16), pages 1-22, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5911-:d:399222
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    References listed on IDEAS

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    2. Mohammad Tabasi & Ali Asghar Alesheikh & Mohsen Kalantari & Abolfazl Mollalo & Javad Hatamiafkoueieh, 2023. "Spatio-Temporal Modeling of COVID-19 Spread in Relation to Urban Land Uses: An Agent-Based Approach," Sustainability, MDPI, vol. 15(18), pages 1-20, September.
    3. Nushrat Nazia & Zahid Ahmad Butt & Melanie Lyn Bedard & Wang-Choi Tang & Hibah Sehar & Jane Law, 2022. "Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review," IJERPH, MDPI, vol. 19(14), pages 1-28, July.
    4. Syed Ali Asad Naqvi & Muhammad Sajjad & Liaqat Ali Waseem & Shoaib Khalid & Saima Shaikh & Syed Jamil Hasan Kazmi, 2021. "Integrating Spatial Modelling and Space–Time Pattern Mining Analytics for Vector Disease-Related Health Perspectives: A Case of Dengue Fever in Pakistan," IJERPH, MDPI, vol. 18(22), pages 1-30, November.

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