IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2024i1p110-d1554334.html
   My bibliography  Save this article

Significant Driving Factors in the Evolution of the COVID-19 Epidemic

Author

Listed:
  • Jingtao Sun

    (Department of Water Conservancy, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China)

  • Xiuxiu Chen

    (School of Spatial Planning and Design, Hangzhou City University, Hangzhou 310015, China)

  • Lijun Zhang

    (Department of Water Conservancy, Hebei University of Water Resources and Electric Engineering, Cangzhou 061001, China)

Abstract

The progression of the COVID-19 pandemic has demonstrated significant oscillatory characteristics, underscoring the importance of investigating the impact of driving factors on its evolution. This study included an in-depth analysis of the influence of various driving factors on the pandemic’s fluctuations, identifying key elements, to enhance the comprehension of transmission mechanisms and improve scientific precision in formulating mitigation strategies. The experimental outcomes indicate that the Geographically and Temporally Neural Network Weighted Regression (GTNNWR) model achieved commendable accuracy with minimal error in forecasting the number of infected individuals. Leveraging the results from the GTNNWR model, the research meticulously examines the temporal and spatial correlations between the driving factors and the pandemic, delineated the spatiotemporal distribution patterns of each factor’s influence, and quantified their significance. This study reveals the substantial impact of vaccines, masks, and social distancing measures across different regions and periods, with their effects on the number of affected individuals being 2 to 10 times more pronounced than other driving factors. These findings contribute to a deeper understanding of the spatiotemporal transmission dynamics and the influence of driving factors in the COVID-19 pandemic, offering critical decision-making support for control and prevention efforts.

Suggested Citation

  • Jingtao Sun & Xiuxiu Chen & Lijun Zhang, 2024. "Significant Driving Factors in the Evolution of the COVID-19 Epidemic," Sustainability, MDPI, vol. 17(1), pages 1-20, December.
    • Handle: RePEc:gam:jsusta:v:17:y:2024:i:1:p:110-:d:1554334
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/1/110/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/17/1/110/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Xueli & Wang, Lei & Zhang, Xuerong & Fan, Fei, 2022. "The spatiotemporal evolution of COVID-19 in China and its impact on urban economic resilience," China Economic Review, Elsevier, vol. 74(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xinyu Zhang & Congying Tian, 2024. "Measurement and Influencing Factors of Regional Economic Resilience in China," Sustainability, MDPI, vol. 16(8), pages 1-21, April.
    2. Xu Dong & Yang Chen & Qinqin Zhuang & Yali Yang & Xiaomeng Zhao, 2022. "Agglomeration of Productive Services, Industrial Structure Upgrading and Green Total Factor Productivity: An Empirical Analysis Based on 68 Prefectural-Level-and-Above Cities in the Yellow River Basin," IJERPH, MDPI, vol. 19(18), pages 1-19, September.
    3. Lili Yang & Ning Ma, 2022. "Empirical Study on the Influence of Urban Environmental Industrial Structure Optimization on Ecological Landscape Greening Construction," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    4. Fang, Yan & Liu, Yinglin & Yang, Yi & Lucey, Brian & Abedin, Mohammad Zoynul, 2025. "How do Chinese urban investment bonds affect its economic resilience? Evidence from double machine learning," Research in International Business and Finance, Elsevier, vol. 74(C).
    5. Xiekui Zhang & Tongsheng Tang & Erhang Mo, 2024. "Can urban e-commerce transformation improve economic resilience? a quasi-natural experiment from China," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-21, May.
    6. Kaiming Cheng & Xinyu Wang & Shucheng Liu & Yanjie Zhuang, 2024. "Spatial differences and dynamic evolution of economic resilience: from the perspective of China’s eight comprehensive economic zones," Economic Change and Restructuring, Springer, vol. 57(2), pages 1-33, April.
    7. Huiping Wang & Qi Ge, 2023. "Spatial association network of economic resilience and its influencing factors: evidence from 31 Chinese provinces," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-14, December.
    8. Dimitrios Tsiotas & Stefanos Dialesiotis & Olga Christopoulou, 2025. "Examining the relationship between regional economic resilience and epidemiologic spread of COVID-19: evidence from Greece," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 27(4), pages 8433-8469, April.
    9. Song Wang & Yixiao Wang & Chenxin Zhou & Xueli Wang, 2022. "Projections in Various Scenarios and the Impact of Economy, Population, and Technology for Regional Emission Peak and Carbon Neutrality in China," IJERPH, MDPI, vol. 19(19), pages 1-31, September.
    10. Yu Gong, 2023. "The impact of China’s financial policy on economic resilience during the pandemic period," Economic Change and Restructuring, Springer, vol. 56(4), pages 2493-2509, August.
    11. Xiao Shen & Jingbo Liang & Jiangning Cao & Zhengwen Wang, 2022. "How Population Aging Affects Industrial Structure Upgrading: Evidence from China," IJERPH, MDPI, vol. 19(23), pages 1-23, December.
    12. Jia Lv & Hao Zeng & Zhi Liu, 2023. "The Impact of Green Innovation Capacity on Urban Economic Resilience: Evidence from China’s Yangtze River Delta Region," Sustainability, MDPI, vol. 15(21), pages 1-28, October.
    13. Junzhou Yu & Wenzheng Hu & Ting Deng, 2024. "Towards more resilient economy—analyzing the impact of new-type urbanization on urban economic resilience: mechanisms and spatial spillover boundaries," Economic Change and Restructuring, Springer, vol. 57(5), pages 1-41, October.
    14. Zhaoguo Wang & Xuechen Hao & Xishihui Du & Hua Ding & Zhiwei Xie, 2024. "Measurement of economic resilience under the COVID-19 based on nighttime light remote sensing: Case of Hubei province," PLOS ONE, Public Library of Science, vol. 19(9), pages 1-21, September.
    15. Du, Yanan & Wang, Qingxi & Song, Yan & Xin, Yueji, 2025. "How cross-regional collaborative innovation networks affect regional economic resilience: Evidence from 283 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 215(C).
    16. Fen Zhang & Tianyi Song & Xiang Cheng & Tianhao Li & Ziming Yang, 2022. "Transportation Infrastructure, Population Mobility, and Public Health," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
    17. Ziqiong He & Rongguang Zhang & Qiwen Qiu & Zhe Chen, 2024. "Research on industrial structure adjustment and spillover effect in resource-based regions in the post-pandemic era," PLOS ONE, Public Library of Science, vol. 19(1), pages 1-19, January.
    18. Mingxia Liu & Wei Jiang, 2022. "Empirical Research on the Influence Mechanisms of Digital Resources Input on Service Innovation in China’s Finance Industry," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    19. Ma, Liuyun & Niu, Lijuan, 2024. "Mineral resources policy with economic risk: Envisaging the role of mineral resources with inclusive financial development for the US economy," Resources Policy, Elsevier, vol. 95(C).
    20. Juan Hu & Chengjin Ma & Chen Li, 2022. "Can Green Innovation Improve Regional Environmental Carrying Capacity? An Empirical Analysis from China," IJERPH, MDPI, vol. 19(20), pages 1-15, October.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:17:y:2024:i:1:p:110-:d:1554334. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.