IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i20p7450-d427232.html
   My bibliography  Save this article

The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases

Author

Listed:
  • Shirui Liu

    (College of Environment and Planning, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Low Yellow River Regions, Henan University, Kaifeng 475004, China)

  • Yaochen Qin

    (College of Environment and Planning, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Low Yellow River Regions, Henan University, Kaifeng 475004, China
    Key Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475001, China)

  • Zhixiang Xie

    (College of Environment and Planning, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Low Yellow River Regions, Henan University, Kaifeng 475004, China)

  • Jingfei Zhang

    (College of Environment and Planning, Henan University, Kaifeng 475004, China
    Key Laboratory of Geospatial Technology for Middle and Low Yellow River Regions, Henan University, Kaifeng 475004, China)

Abstract

The global pandemic of COVID-19 has made it the focus of current attention. At present, the law of COVID-19 spread in cities is not clear. Cities have long been difficult areas for epidemic prevention and control because of the high population density, high mobility of people, and high frequency of contacts. This paper analyzed case information for 417 patients with COVID-19 in Shenzhen, China. The nearest neighbor index method, kernel density method, and the standard deviation ellipse method were used to analyze the spatio-temporal characteristics of the COVID-19 spread in Shenzhen. The factors influencing that spread were then explored using the multiple linear regression method. The results show that: (1) The development of COVID-19 epidemic situation in Shenzhen occurred in three stages. The patients showed significant hysteresis from the onset of symptoms to hospitalization and then to diagnosis. Prior to 27 January, there was a relatively long time interval between the onset of symptoms and hospitalization for COVID-19; the interval decreased thereafter. (2) The epidemic site (the place where the patient stays during the onset of the disease) showed an agglomeration in space. The degree of agglomeration constantly increased across the three time nodes of 31 January, 14 February, and 22 February. The epidemic sites formed a “core area” in terms of spatial distribution and spread along the “northwest–southeast” direction of the city. (3) Economic and social factors significantly impacted the spread of COVID-19, while environmental factors have not played a significant role.

Suggested Citation

  • Shirui Liu & Yaochen Qin & Zhixiang Xie & Jingfei Zhang, 2020. "The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases," IJERPH, MDPI, vol. 17(20), pages 1-13, October.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:20:p:7450-:d:427232
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/20/7450/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/17/20/7450/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yanting Zheng & Jinyuan Huang & Qiuyue Yin, 2021. "What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration," IJERPH, MDPI, vol. 18(6), pages 1-16, March.
    2. 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.

    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:jijerp:v:17:y:2020:i:20:p:7450-:d:427232. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.