Residential Segregation and County-Level COVID-19 Booster Coverage in the Deep South: Surveillance Report and Ecological Study

被引:2
|
作者
Zeng, Chengbo [1 ,2 ,3 ]
Zhang, Jiajia [2 ,3 ,4 ]
Li, Zhenlong [2 ,3 ,5 ]
Sun, Xiaowen [2 ,3 ,4 ]
Ning, Huan [3 ,5 ]
Yang, Xueying [1 ,2 ,3 ]
Weissman, Sharon [2 ,6 ]
Olatosi, Bankole [2 ,3 ,7 ]
Li, Xiaoming [1 ,2 ,3 ]
机构
[1] Univ South Carolina, Arnold Sch Publ Hlth, Dept Hlth Promot Educ & Behav, 4th Floor,915 Greene St, Columbia, SC 29208 USA
[2] Univ South Carolina, South Carolina SmartState Ctr Healthcare Qual, Columbia, SC 29208 USA
[3] Univ South Carolina, Big Data Hlth Sci Ctr, Columbia, SC USA
[4] Univ South Carolina, Arnold Sch Publ Hlth, Dept Epidemiol & Biostat, Columbia, SC USA
[5] Univ South Carolina, Coll Arts & Sci, Dept Geog, Geoinformat & Big Data Res Lab, Columbia, SC USA
[6] Univ South Carolina, Sch Med, Dept Internal Med, Columbia, SC USA
[7] Univ South Carolina, Arnold Sch Publ Hlth, Dept Hlth Serv Policy & Management, Columbia, SC USA
来源
关键词
Deep South; COVID-19; vaccine; booster; residential segregation; UNITED-STATES; DISPARITIES;
D O I
10.2196/44257
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: COVID-19 had a greater impact in the Deep South compared with other regions in the United States. While vaccination remains a top priority for all eligible individuals, data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age are sparse. Despite existing evidence of racial and ethnic disparities in COVID-19 vaccinations at the individual level, there is an urgent need for evidence at the population level. Such information could highlight vulnerable communities and guide future health care policy-making and resource allocation. Objective: We aimed to evaluate county-level COVID-19 booster coverage by age group in the Deep South and explore its association with residential segregation. Methods: An ecological study was conducted at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of 5 Deep South states from December 15, 2021, to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster uptake by age group (eg, 12 to 17 years, 18 to 64 years, and at least 65 years) by the end of the study period. The longitudinal relationships were examined between residential segregation, the interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson model. Results: As of October 19, 2022, among the 418 counties, the median of booster uptake was 40% (IQR 37.8%-43%). Compared with older adults (ie, at least 65 years; median 63.1%, IQR 59.5%-66.5%), youth (ie, 12 to 17 years; median 14.1%, IQR 11.3%-17.4%) and adults (ie, 18 to 64 years; median 33.4%, IQR 30.5%-36.5%) had lower percentages of booster uptake. There was geospatial heterogeneity in the county-level COVID-19 booster coverage. We found that higher segregated counties had lower percentages of booster coverage. Such relationships attenuated as time increased. The findings were consistent across the age groups.Conclusions: The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccination strategies should focus on youth and adults. Health care facilities and resources are needed in racial and ethnic minority communities.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] County-Level Mandates Were Generally Effective At Slowing COVID-19 Transmission
    Baird, Courtney E.
    Lake, Derek
    Panagiotou, Orestis A.
    Gozalo, Pedro
    HEALTH AFFAIRS, 2024, 43 (03) : 433 - 442
  • [32] County-level estimates of excess mortality associated with COVID-19 in the United States
    Ackley, Calvin A.
    Lundberg, Dielle J.
    Ma, Lei
    Elo, Irma T.
    Preston, Samuel H.
    Stokes, Andrew C.
    SSM-POPULATION HEALTH, 2022, 17
  • [33] Integrating County-Level Socioeconomic Data for COVID-19 Forecasting in the United States
    Lucic, Michael C.
    Ghazzai, Hakim
    Lipizzi, Carlo
    Massoud, Yehia
    IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY, 2021, 2 : 235 - 248
  • [34] COVID-19 EnsembleVis: Visual Analysis of County-level Ensemble Forecast Models
    Srabanti, Sanjana
    Marai, G. Elisabeta
    Miranda, Fabio
    2021 IEEE WORKSHOP ON VISUAL ANALYTICS IN HEALTHCARE (VAHC 2021), 2021, : 1 - 5
  • [35] COVID-19 and Outpatient Antibiotic Prescriptions in the United States: A County-Level Analysis
    Hamilton, Alisa
    Poleon, Suprena
    Cherian, Jerald
    Cosgrove, Sara
    Laxminarayan, Ramanan
    Klein, Eili
    OPEN FORUM INFECTIOUS DISEASES, 2023, 10 (03):
  • [36] COVID-19 and housing prices: evidence from US county-level data
    Yilmazkuday, Hakan
    REVIEW OF REGIONAL RESEARCH-JAHRBUCH FUR REGIONALWISSENSCHAFT, 2023, 43 (02): : 241 - 263
  • [37] County-Level Association of Social Vulnerability with COVID-19 Cases and Deaths in the USA
    Rohan Khazanchi
    Evan R. Beiter
    Suhas Gondi
    Adam L. Beckman
    Alyssa Bilinski
    Ishani Ganguli
    Journal of General Internal Medicine, 2020, 35 : 2784 - 2787
  • [38] Identifying US County-level characteristics associated with high COVID-19 burden
    Daniel Li
    Sheila M. Gaynor
    Corbin Quick
    Jarvis T. Chen
    Briana J. K. Stephenson
    Brent A. Coull
    Xihong Lin
    BMC Public Health, 21
  • [39] Identifying US County-level characteristics associated with high COVID-19 burden
    Li, Daniel
    Gaynor, Sheila M.
    Quick, Corbin
    Chen, Jarvis T.
    Stephenson, Briana J. K.
    Coull, Brent A.
    Lin, Xihong
    BMC PUBLIC HEALTH, 2021, 21 (01)
  • [40] Variation in COVID-19 booster uptake in England: An ecological study
    Dropkin, Greg
    PLOS ONE, 2022, 17 (06):