IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/d2k5s.html
   My bibliography  Save this paper

Examining Geospatial PPE Waste Patterns and Associations with Neighborhood-level Sociodemographic Indicators and Social Capital in Boston Neighborhoods during Fall 2022

Author

Listed:
  • Schmitz, Gloria M.

Abstract

Personal protective equipment (PPE) litter plagued the urban environment during the COVID-19 pandemic. Based on data from 15 neighborhoods in the Boston, Massachusetts, United States, including primary geocoded PPE waste data, and socioeconomic and social capital data from secondary datasets, this study used hot spots-cold spots analysis and bivariate Spearman correlations to examine spatial patterns, and associations between PPE waste and key variables. The results showed that neighborhoods with lower social capital and lower median household income had higher amounts of PPE litter overall and per 100,000 residents. Areas with more high-tech waste bins had less PPE litter, whereas PPE litter tended to cluster around major hospital and medical facility locations. These findings can help inform urban and regional policymakers about where to place smart Wi-Fi-enabled waste receptacles, ways to target public information campaigns aimed at enhancing urban waste-reduction dynamics, and how to optimize waste collection using geospatial metrics.

Suggested Citation

  • Schmitz, Gloria M., 2024. "Examining Geospatial PPE Waste Patterns and Associations with Neighborhood-level Sociodemographic Indicators and Social Capital in Boston Neighborhoods during Fall 2022," OSF Preprints d2k5s, Center for Open Science.
    • Handle: RePEc:osf:osfxxx:d2k5s
    DOI: 10.31219/osf.io/d2k5s
    as

    Download full text from publisher

    File URL: https://osf.io/download/66be27356217a43eb0dbe13b/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/d2k5s?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:osfxxx:d2k5s. 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: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    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.