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. 2023 Jan 17;10(1):38-44.
doi: 10.17294/2330-0698.1967. eCollection 2023 Winter.

Neighborhood Condition Prevalence Rates Correlate With COVID-19 Mortality in Milwaukee County, Wisconsin

Affiliations

Neighborhood Condition Prevalence Rates Correlate With COVID-19 Mortality in Milwaukee County, Wisconsin

George L Morris 3rd. J Patient Cent Res Rev. .

Abstract

Purpose: We sought to determine if census tract-level (ie, neighborhood) COVID-19 death rates in Milwaukee County correlated with the census tract-level condition prevalence rates (CPRs) for individual COVID-19 mortality risk.

Methods: This study used Milwaukee County-reported COVID-19 death rates per 100,000 lives for the 296 census tracts within the county to perform a linear regression with individual COVID-19 mortality risk CPR, mean age, racial composition of census tract (by percentage of non-White residents), and poverty (by percentage within census tract), followed by multiple regression with all 7 CPRs as well as the 7 CPRs combined with the additional demographic variables. CPR estimates were accessed from the Centers for Disease Control and Prevention 500 Cities Project. Demographics were accessed from the U.S. Census. The Milwaukee County Medical Examiner's office identified 898 deaths from COVID-19 in Milwaukee County from March 2020 to June 2021.

Results: Among the variables included, crude death rate demonstrated a statistically significant association with the 7 COVID-19 mortality risk CPRs (as analyzed collectively), census tract mean age, and several of the CPRs individually. The addition of census tract age, race, and poverty in multiple regression did not improve the association of the 7 CPRs with crude death rate.

Conclusions: Results from this population-level study indicated that census tracts with high COVID-19 mortality correlated with high-risk condition prevalence estimates within those census tracts, illustrating how health data collection and analysis at a census tract level could be helpful when planning pandemic-mitigating public health efforts.

Keywords: COVID-19; data science; mortality; neighborhood; pandemic; prevalence; public health; risk model.

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Conflict of interest statement

Conflicts of Interest None.

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