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      Descriptive analysis of social determinant factors in urban communities affected by COVID-19

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          ABSTRACT

          Objectives

          To provide a descriptive analysis of communities severely impacted by COVID-19 to that of communities moderately affected by COVID-19, with an emphasis on the social determinant factors within them.

          Methods

          To compare the communities with extremely high COVID-19 rates to that of communities with moderate COVID-19 cases, we selected six community districts in Queens, New York using public data from New York City Health Department that provides the percentage of positive COVID-19 cases by zip codes from March 1st, 2020 to April 17th, 2020.

          Results

          The results of the study showed that COVID-19 cases were 30% greater in communities with extremely high cases than in communities with moderate cases. There were also the several outstanding social determinants commonalities that were found in communities with extremely high COVID-19 cases. These include severe overcrowding, lower educational status, less access to healthcare, and more chronic diseases.

          Conclusion

          This study adds to existing literature on vulnerable urban communities affected by COVID-19. Future studies should focus on the underlying factors in each social determinant discussed in this study to better understand its association with the spread of COVID-19.

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          Most cited references5

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          Disparities in diabetes: the nexus of race, poverty, and place.

          Darrell Gaskin, Roland Thorpe, Emma Mcginty … (2014)
          We sought to determine the role of neighborhood poverty and racial composition on race disparities in diabetes prevalence. We used data from the 1999-2004 National Health and Nutrition Examination Survey and 2000 US Census to estimate the impact of individual race and poverty and neighborhood racial composition and poverty concentration on the odds of having diabetes. We found a race-poverty-place gradient for diabetes prevalence for Blacks and poor Whites. The odds of having diabetes were higher for Blacks than for Whites. Individual poverty increased the odds of having diabetes for both Whites and Blacks. Living in a poor neighborhood increased the odds of having diabetes for Blacks and poor Whites. To address race disparities in diabetes, policymakers should address problems created by concentrated poverty (e.g., lack of access to reasonably priced fruits and vegetables, recreational facilities, and health care services; high crime rates; and greater exposures to environmental toxins). Housing and development policies in urban areas should avoid creating high-poverty neighborhoods.
          Article 0 comments Cited 141 times – based on 0 reviews     Review now
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            Risk Factors for SARS among Persons without Known Contact with SARS Patients, Beijing, China

            Jiang Wu, Fujie Xu, Weigong Zhou … (2004)
            Most cases of severe acute respiratory syndrome (SARS) have occurred in close contacts of SARS patients. However, in Beijing, a large proportion of SARS cases occurred in persons without such contact. We conducted a case-control study in Beijing that compared exposures of 94 unlinked, probable SARS patients with those of 281 community-based controls matched for age group and sex. Case-patients were more likely than controls to have chronic medical conditions or to have visited fever clinics (clinics at which possible SARS patients were separated from other patients), eaten outside the home, or taken taxis frequently. The use of masks was strongly protective. Among 31 case-patients for whom convalescent-phase (>21 days) sera were available, 26% had immunoglobulin G to SARS-associated coronavirus. Our finding that clinical SARS was associated with visits to fever clinics supports Beijing’s strategy of closing clinics with poor infection-control measures. Our finding that mask use lowered the risk for disease supports the community’s use of this strategy.
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              Changing prevalence of tuberculosis infection with increasing age in high-burden townships in South Africa.

              T Oni, Anna H. Wu, Stephen D Lawn … (2010)
              Crowded townships of Cape Town, South Africa, where human immunodeficiency virus (HIV) prevalence and tuberculosis (TB) notification rates are among the highest in the world. To determine age-specific prevalence rates of latent tuberculosis infection (LTBI) among HIV-negative individuals, and the annual risk and force of infection during childhood and adolescence. A cross-sectional survey using a standardised tuberculin skin test (TST) in HIV-negative individuals aged 5-40 years. A TST diameter of > or =10 mm was defined as indicative of LTBI. Among 1061 individuals, only 4.7% had low-grade TST responses of 1-9 mm. However, the proportions of individuals with TST > or =10 mm increased from 28.0% in the 5-10 year age stratum to 88.0% in the 31-35 year age stratum. The mean annual risk of infection was 3.9% up to 5 years of age. The estimated force of infection (the rate of acquisition of LTBI among the residual pool of non-infected individuals) increased throughout childhood to a maximum of 7.9% per year at age 15 years. Extremely high rates of infection in childhood and adolescence result in very high LTBI prevalence rates in young adults who are most at risk of acquiring HIV infection. This may be an important factor fuelling the high rates of HIV-associated TB in southern Africa.
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                Author and article information

                Journal
                Journal ID (nlm-ta): J Public Health (Oxf)
                Journal ID (iso-abbrev): J Public Health (Oxf)
                Journal ID (publisher-id): pubmed
                Title: Journal of Public Health (Oxford, England)
                Publisher: Oxford University Press
                ISSN (Print): 1741-3842
                ISSN (Electronic): 1741-3850
                Publication date (Electronic): 12 June 2020
                Electronic Location Identifier: fdaa078
                Affiliations
                [1] Department of Pharmacy Administration and Public Health , St. John's University, 175-05 Horace Harding Epresswat Room 211 Fresh Meadows, New York 11365, US
                Author notes
                Address correspondence to Gunness Harlem, E-mail: gunnessh@ 123456stjohns.edu , hjgunness@ 123456gmail.com
                Author information
                http://orcid.org/0000-0003-0583-1068
                Article
                Publisher ID: fdaa078
                DOI: 10.1093/pubmed/fdaa078
                PMC ID: 7313894
                PubMed ID: 32530033
                SO-VID: 0d923798-6cdc-485a-b05d-aacb03afee07
                Copyright © © The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
                License:

                This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model ( https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

                This article is made available via the PMC Open Access Subset for unrestricted re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the COVID-19 pandemic or until permissions are revoked in writing. Upon expiration of these permissions, PMC is granted a perpetual license to make this article available via PMC and Europe PMC, consistent with existing copyright protections.

                History
                Date received : 12 May 2020
                Date revision received : 14 May 2020
                Date accepted : 14 May 2020
                Page count
                Pages: 4
                Categories
                Subject: AcademicSubjects/MED00860
                Subject: Short Report
                Custom metadata
                article-lifecycle PAP

                ScienceOpen disciplines: Public health
                Keywords: covid-19,descriptive analysis,social determinants,health disparities,severely affected communities
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: covid-19, descriptive analysis, social determinants, health disparities, severely affected communities

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