IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i18p9673-d635197.html
   My bibliography  Save this article

Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina

Author

Listed:
  • Tianchu Lyu

    (Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
    Equal contribution.)

  • Nicole Hair

    (Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA
    Equal contribution.)

  • Nicholas Yell

    (Department of Statistics, College of Arts and Sciences, University of South Carolina, Columbia, SC 29208, USA)

  • Zhenlong Li

    (Department of Geography, College of Arts and Sciences, University of South Carolina, Columbia, SC 29208, USA)

  • Shan Qiao

    (Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA)

  • Chen Liang

    (Department of Health Services Policy and Management, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA)

  • Xiaoming Li

    (Department of Health Promotion, Education, and Behavior, Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA)

Abstract

Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal–geospatial associations between PIDRs and COVID-19 infection at the county level in South Carolina. We used the spatial error model (SEM), spatial lag model (SLM), and conditional autoregressive model (CAR) as global models and the geographically weighted regression model (GWR) as a local model. The data were retrieved from multiple sources including USAFacts, U.S. Census Bureau, and the Population Estimates Program. The percentage of males and the unemployed population were positively associated with geodistributions of COVID-19 infection ( p values < 0.05) in global models throughout the time. The percentage of the white population and the obesity rate showed divergent spatial correlations at different times of the pandemic. GWR models fit better than global models, suggesting nonstationary correlations between a region and its neighbors. Characterized by temporal–geospatial patterns, disparities in COVID-19 infection rate and their PIDRs are different from the mortality and morbidity of COVID-19 patients. Our findings suggest the importance of prioritizing different populations and developing tailored interventions at different times of the pandemic.

Suggested Citation

  • Tianchu Lyu & Nicole Hair & Nicholas Yell & Zhenlong Li & Shan Qiao & Chen Liang & Xiaoming Li, 2021. "Temporal Geospatial Analysis of COVID-19 Pre-Infection Determinants of Risk in South Carolina," IJERPH, MDPI, vol. 18(18), pages 1-18, September.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:18:p:9673-:d:635197
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/18/9673/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/18/9673/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yun Qiu & Xi Chen & Wei Shi, 2020. "Impacts of social and economic factors on the transmission of coronavirus disease 2019 (COVID-19) in China," Journal of Population Economics, Springer;European Society for Population Economics, vol. 33(4), pages 1127-1172, October.
    2. Ziyad Al-Aly & Yan Xie & Benjamin Bowe, 2021. "High-dimensional characterization of post-acute sequelae of COVID-19," Nature, Nature, vol. 594(7862), pages 259-264, June.
    3. Terrie Walmsley & Adam Rose & Dan Wei, 2021. "The Impacts of the Coronavirus on the Economy of the United States," Economics of Disasters and Climate Change, Springer, vol. 5(1), pages 1-52, April.
    4. Moehring, Katja & Weiland, Andreas & Reifenscheid, Maximiliane & Naumann, Elias & Wenz, Alexander & Rettig, Tobias & Krieger, Ulrich & Fikel, Marina & Cornesse, Carina & Blom, Annelies G., 2021. "Inequality in employment trajectories and their socio-economic consequences during the early phase of the COVID-19 pandemic in Germany," SocArXiv m95df, Center for Open Science.
    5. George B Cunningham & Lisa T Wigfall, 2020. "Race, explicit racial attitudes, implicit racial attitudes, and COVID-19 cases and deaths: An analysis of counties in the United States," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Krzysztof Rząsa & Mateusz Ciski, 2022. "Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic—Analysis of the Local Variations Using Geographically Weighted Regression," IJERPH, MDPI, vol. 19(19), pages 1-26, September.
    2. Jessica R. Mosher & Jim E. Banta & Rhonda Spencer-Hwang & Colleen C. Naughton & Krystin F. Kadonsky & Thomas Hile & Ryan G. Sinclair, 2024. "An Environmental Equity Assessment Using a Social Vulnerability Index during the SARS-CoV-2 Pandemic for Siting of Wastewater-Based Epidemiology Locations in the United States," Geographies, MDPI, vol. 4(1), pages 1-11, February.

    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. Chen, Simiao & Jin, Zhangfeng & Bloom, David E., 2020. "Act Early to Prevent Infections and Save Lives: Causal Impact of Diagnostic Efficiency on the COVID-19 Pandemic," IZA Discussion Papers 13749, Institute of Labor Economics (IZA).
    2. Catalina Amuedo-Dorantes & Neeraj Kaushal & Ashley N. Muchow, 2021. "Timing of social distancing policies and COVID-19 mortality: county-level evidence from the U.S," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(4), pages 1445-1472, October.
    3. Cui Zhang & Dandan Zhang, 2023. "Spatial Interactions and the Spread of COVID-19: A Network Perspective," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 383-405, June.
    4. Abu Bakkar Siddique & Kingsley E. Haynes & Rajendra Kulkarni & Meng-Hao Li, 2023. "Regional poverty and infection disease: early exploratory evidence from the COVID-19 pandemic," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 70(1), pages 209-236, February.
    5. Maxim Ananyev & Michael Poyker & Yuan Tian, 2021. "The safest time to fly: pandemic response in the era of Fox News," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(3), pages 775-802, July.
    6. Badi H. Baltagi & Ying Deng & Jing Li & Zhenlin Yang, 2023. "Cities in a pandemic: Evidence from China," Journal of Regional Science, Wiley Blackwell, vol. 63(2), pages 379-408, March.
    7. Indrikis A. Krams & Priit Jõers & Severi Luoto & Giedrius Trakimas & Vilnis Lietuvietis & Ronalds Krams & Irena Kaminska & Markus J. Rantala & Tatjana Krama, 2021. "The Obesity Paradox Predicts the Second Wave of COVID-19 to Be Severe in Western Countries," IJERPH, MDPI, vol. 18(3), pages 1-10, January.
    8. Nicholas W. Papageorge & Matthew V. Zahn & Michèle Belot & Eline Broek-Altenburg & Syngjoo Choi & Julian C. Jamison & Egon Tripodi, 2021. "Socio-demographic factors associated with self-protecting behavior during the Covid-19 pandemic," Journal of Population Economics, Springer;European Society for Population Economics, vol. 34(2), pages 691-738, April.
    9. Lewandowski, Piotr, 2020. "Occupational Exposure to Contagion and the Spread of COVID-19 in Europe," IZA Discussion Papers 13227, Institute of Labor Economics (IZA).
    10. Qiu, Yun & Liu, Yunning & Shi, Wei & Zhou, Maigeng, 2024. "The impact of ozone pollution on mortality: Evidence from China," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    11. Chen, Xi & Qiu, Yun & Shi, Wei & Yu, Pei, 2022. "Key links in network interactions: Assessing route-specific travel restrictions in China during the Covid-19 pandemic," China Economic Review, Elsevier, vol. 73(C).
    12. Borja Gambau & Juan C. Palomino & Juan G. Rodríguez & Raquel Sebastian, 2022. "COVID-19 restrictions in the US: wage vulnerability by education, race and gender," Applied Economics, Taylor & Francis Journals, vol. 54(25), pages 2900-2915, May.
    13. Pawel Dlotko & Simon Rudkin, 2020. "Visualising the Evolution of English Covid-19 Cases with Topological Data Analysis Ball Mapper," Papers 2004.03282, arXiv.org, revised Apr 2020.
    14. Li, Xun & Lai, Weizheng & Wan, Qianqian & Chen, Xi, 2022. "Role of professionalism in response to the COVID-19 pandemic: Does a public health or medical background help?," China Economic Review, Elsevier, vol. 71(C).
    15. Mauro Caselli & Andrea Fracasso & Sergio Scicchitano, 2022. "From the lockdown to the new normal: individual mobility and local labor market characteristics following the COVID-19 pandemic in Italy," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(4), pages 1517-1550, October.
    16. Syed Abul Basher & A. K. Enamul Haque, 2021. "Public policy lessons from the Covid-19 outbreak: How to deal with it in the post-pandemic world?," Journal of Social and Economic Development, Springer;Institute for Social and Economic Change, vol. 23(2), pages 234-247, September.
    17. Ján Palguta & René Levínský & Samuel Škoda, 2022. "Do elections accelerate the COVID-19 pandemic?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 35(1), pages 197-240, January.
    18. Gerritse, Michiel, 2022. "COVID-19 transmission in cities," European Economic Review, Elsevier, vol. 150(C).
    19. Feng Wang & Xing Ge & Danwen Huang, 2022. "Government Intervention, Human Mobility, and COVID-19: A Causal Pathway Analysis from 121 Countries," Sustainability, MDPI, vol. 14(6), pages 1-26, March.
    20. Li, Haizheng & Liu, Qinyi & Ma, Mingyu, 2021. "How the COVID-19 Pandemic Affects Job Stress of Rural Teachers," IZA Discussion Papers 14366, Institute of Labor Economics (IZA).

    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:18:y:2021:i:18:p:9673-:d:635197. 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.