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Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.
Tieskens, Koen F; Patil, Prasad; Levy, Jonathan I; Brochu, Paige; Lane, Kevin J; Fabian, M Patricia; Carnes, Fei; Haley, Beth M; Spangler, Keith R; Leibler, Jessica H.
  • Tieskens KF; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Patil P; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • Levy JI; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Brochu P; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Lane KJ; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Fabian MP; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Carnes F; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Haley BM; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Spangler KR; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA.
  • Leibler JH; Department of Environmental Health, Boston University School of Public Health, 715 Albany St, Boston, MA, 02118, USA. jleibler@bu.edu.
BMC Infect Dis ; 21(1): 686, 2021 Jul 16.
Article in English | MEDLINE | ID: covidwho-1571742
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ABSTRACT

BACKGROUND:

Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020.

METHODS:

Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time.

RESULTS:

Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI 1.12-1.13]) in early spring, IRR = 1.01 [95%CI 1.00-1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI 1.26-1.31] in spring, IRR = 1.07 [95%CI 1.05-1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI 1.27-1.33] in spring, IRR = 1.20 [95%CI 1.17-1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI 1.18-1.21] in spring, IRR = 1.14 [95%CI 1.13-1.15] in fall).

CONCLUSIONS:

Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Environment / Transportation / COVID-19 / Occupations Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Country/Region as subject: North America Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: S12879-021-06389-w

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Social Environment / Transportation / COVID-19 / Occupations Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Aged / Female / Humans / Male / Middle aged / Young adult Country/Region as subject: North America Language: English Journal: BMC Infect Dis Journal subject: Communicable Diseases Year: 2021 Document Type: Article Affiliation country: S12879-021-06389-w