IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i15p9323-d876026.html
   My bibliography  Save this article

Effects of Meteorological Factors and Air Pollutants on COVID-19 Transmission under the Action of Control Measures

Author

Listed:
  • Fei Han

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Xinqi Zheng

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Peipei Wang

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Dongya Liu

    (School of Information Engineering, China University of Geosciences, Beijing 100083, China)

  • Minrui Zheng

    (School of Public Administration and Policy, Renmin University of China, Beijing 100872, China)

Abstract

At present, COVID-19 is still spreading, and its transmission patterns and the main factors that affect transmission behavior still need to be thoroughly explored. To this end, this study collected the cumulative confirmed cases of COVID-19 in China by 8 April 2020. Firstly, the spatial characteristics of the COVID-19 transmission were investigated by the spatial autocorrelation method. Then, the factors affecting the COVID-19 incidence rates were analyzed by the generalized linear mixed effect model (GLMMs) and geographically weighted regression model (GWR). Finally, the geological detector (GeoDetector) was introduced to explore the influence of interactive effects between factors on the COVID-19 incidence rates. The results showed that: (1) COVID-19 had obvious spatial aggregation. (2) The control measures had the largest impact on the COVID-19 incidence rates, which can explain the difference of 34.2% in the COVID-19 incidence rates, while meteorological factors and pollutant factors can only explain the difference of 1% in the COVID-19 incidence rates. It explains that some of the literature overestimates the impact of meteorological factors on the spread of the epidemic. (3) The influence of meteorological factors was stronger than that of air pollution factors, and the interactive effects between factors were stronger than their individual effects. The interaction between relative humidity and NO 2 was stronger. The results of this study will provide a reference for further prevention and control of COVID-19.

Suggested Citation

  • Fei Han & Xinqi Zheng & Peipei Wang & Dongya Liu & Minrui Zheng, 2022. "Effects of Meteorological Factors and Air Pollutants on COVID-19 Transmission under the Action of Control Measures," IJERPH, MDPI, vol. 19(15), pages 1-19, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:15:p:9323-:d:876026
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/15/9323/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/15/9323/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dongya Liu & Xinqi Zheng & Lei Zhang, 2021. "Simulation of Spatiotemporal Relationship between COVID-19 Propagation and Regional Economic Development in China," Land, MDPI, vol. 10(6), pages 1-15, June.
    2. A. Stewart Fotheringham & Taylor M. Oshan, 2016. "Geographically weighted regression and multicollinearity: dispelling the myth," Journal of Geographical Systems, Springer, vol. 18(4), pages 303-329, October.
    3. Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
    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. Pulugurtha, Srinivas S. & Mathew, Sonu, 2021. "Modeling AADT on local functionally classified roads using land use, road density, and nearest nonlocal road data," Journal of Transport Geography, Elsevier, vol. 93(C).
    2. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    3. Hongli Liu & Xiaoyu Yan & Jinhua Cheng & Jun Zhang & Yan Bu, 2021. "Driving Factors for the Spatiotemporal Heterogeneity in Technical Efficiency of China’s New Energy Industry," Energies, MDPI, vol. 14(14), pages 1-21, July.
    4. Hoehun Ha & Wei Tu, 2018. "An Ecological Study on the Spatially Varying Relationship between County-Level Suicide Rates and Altitude in the United States," IJERPH, MDPI, vol. 15(4), pages 1-16, April.
    5. Li Gao & Mingjing Huang & Wuping Zhang & Lei Qiao & Guofang Wang & Xumeng Zhang, 2021. "Comparative Study on Spatial Digital Mapping Methods of Soil Nutrients Based on Different Geospatial Technologies," Sustainability, MDPI, vol. 13(6), pages 1-19, March.
    6. Alexis Comber & Paul Harris, 2018. "Geographically weighted elastic net logistic regression," Journal of Geographical Systems, Springer, vol. 20(4), pages 317-341, October.
    7. Li, Mengya & Kwan, Mei-Po & Hu, Wenyan & Li, Rui & Wang, Jun, 2023. "Examining the effects of station-level factors on metro ridership using multiscale geographically weighted regression," Journal of Transport Geography, Elsevier, vol. 113(C).
    8. Oshan, Taylor M., 2022. "Navigating the methodological landscape in spatial analysis: a comment on ‘A Route Map for Successful Applications of Geographically-Weighted Regression’," OSF Preprints rckzj, Center for Open Science.
    9. Salma Hamza & Imran Khan & Linlin Lu & Hua Liu & Farkhunda Burke & Syed Nawaz-ul-Huda & Muhammad Fahad Baqa & Aqil Tariq, 2021. "The Relationship between Neighborhood Characteristics and Homicide in Karachi, Pakistan," Sustainability, MDPI, vol. 13(10), pages 1-14, May.
    10. Jie Li & Kun Jia & Yanxu Liu & Bo Yuan & Mu Xia & Wenwu Zhao, 2021. "Spatiotemporal Distribution of Zika Virus and Its Spatially Heterogeneous Relationship with the Environment," IJERPH, MDPI, vol. 18(1), pages 1-14, January.
    11. Christos Agiakloglou & Cleon Tsimbos & Apostolos Tsimpanos, 2019. "Evidence of spurious results along with spatially autocorrelated errors in the context of geographically weighted regression for two independent SAR(1) processes," Empirical Economics, Springer, vol. 57(5), pages 1613-1631, November.
    12. Xin Lao & Hengyu Gu, 2020. "Unveiling various spatial patterns of determinants of hukou transfer intentions in China: A multi‐scale geographically weighted regression approach," Growth and Change, Wiley Blackwell, vol. 51(4), pages 1860-1876, December.
    13. Rongbing Liu & Afifa Qadeer & Junqi Liu & Suleman Sarwar & Muhammad Wasim Hussan, 2024. "The Paradox of Progress towards SDG7: Governance Quality and Energy Poverty Dynamics in Pakistan," Sustainability, MDPI, vol. 16(19), pages 1-27, September.
    14. Jiaxing Pang & Xue Li & Xiang Li & Ting Yang & Ya Li & Xingpeng Chen, 2022. "Analysis of Regional Differences and Factors Influencing the Intensity of Agricultural Water in China," Agriculture, MDPI, vol. 12(4), pages 1-20, April.
    15. Liu, Yang & Min, Shisheng & Shi, Zhuangbin & He, Mingwei, 2024. "Exploring students' choice of active travel to school in different spatial environments: A case study in a mountain city," Journal of Transport Geography, Elsevier, vol. 115(C).
    16. Yuan Gao & Chuanrong Zhang & Qingsong He & Yaolin Liu, 2017. "Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China," IJERPH, MDPI, vol. 14(6), pages 1-20, June.
    17. Chengcheng Xu & Yuxuan Wang & Wei Ding & Pan Liu, 2020. "Modeling the Spatial Effects of Land-Use Patterns on Traffic Safety Using Geographically Weighted Poisson Regression," Networks and Spatial Economics, Springer, vol. 20(4), pages 1015-1028, December.
    18. Paul Harris & Bruno Lanfranco & Binbin Lu & Alexis Comber, 2020. "Influence of Geographical Effects in Hedonic Pricing Models for Grass-Fed Cattle in Uruguay," Agriculture, MDPI, vol. 10(7), pages 1-17, July.
    19. Nana Yang & Jiansong Li & Binbin Lu & Minghai Luo & Linze Li, 2019. "Exploring the Spatial Pattern and Influencing Factors of Land Carrying Capacity in Wuhan," Sustainability, MDPI, vol. 11(10), pages 1-16, May.
    20. Abulibdeh, Ammar, 2021. "Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar," Applied Energy, Elsevier, vol. 304(C).

    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:19:y:2022:i:15:p:9323-:d:876026. 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.