Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts

Abstract

Background: Associations between community-level risk factors and COVID-19 incidence are 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. We examined town-level demographic variables, including z-scores of percent Black, Latinx, over 80 years and undergraduate students, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities.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 Black residents (IRR=1.12 CI=(1.12-1.13) in spring, IRR=1.01 CI=(1.00-1.01) in fall). The association with number of long-term care facility beds per capita also decreased over time (IRR=1.28 CI=(1.26-1.31) in spring, IRR=1.07 CI=(1.05-1.09)in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidence of COVID-19 throughout the pandemic (e.g., IRR=1.30 CI=(1.27-1.33) in spring, IRR=1.20, CI=(1.17-1.22) in fall). Towns with higher percentages of Latinx residents also had sustained elevated incidence over time (e.g., IRR=1.19 CI=(1.18-1.21) in spring, IRR=1.14 CI=(1.13-1.15) in fall). Conclusions: Town-level COVID-19 risk factors vary with time. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence have decreased over time, 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.

Community predictors of COVID‐19 cases and deaths in Massachusetts: Evaluating changes over time using geospatially refined data

“…We observed key disparities in models of both cases and death outcomes associated with the proportion of Black and Latinx populations by tract, findings that parallel those at town‐level resolution across a shorter time period, as well as findings from other studies 28,31–34 . The variability observed in the size of these estimates over time reinforces how these race and ethnicity variables reflect social constructs and not biological or constant risk factors.…”

“…We defined “essential services” following the approach of the American Civil Liberties Union (ACLU) Massachusetts 27 . These variables are informed by and consistent with our previous modeling work at the town level, in which we used backwards model selection to select non‐correlated covariates (confirming that none of the independent variables had a correlation of | r | > 0.60) 28 …”

Inequities in COVID-19 vaccine and booster coverage across Massachusetts ZIP codes: large gaps persist after the 2021/22 Omicron wave

“…7 These communities were identified based on COVID-19 case rates, CDC-defined social vulnerability, and the share Black, Indigenous, and people of color. 8 These populations, as well as the overlapping population of essential workers, have been at elevated risk for COVID exposure, infection, morbidity, and mortality throughout the pandemic [9][10][11][12][13][14][15] . The VEI allocated has awarded $46.5 million to 167 community organizations to support vaccine education and outreach.…”

Evolution of COVID-19 Health Disparities in Arizona

“…Unfortunately, current literature mainly contains cross-sectional studies capturing only static snapshots of the disparities, and updates of the COVID-19 disparities are surprisingly rare. To date, we found only one study that investigated the time-varying associations between COVID-19 incidence and community level risk factors during the early 7-month period (March to October 2020) in Massachusetts [12]. Overlooking the fluid nature of COVID-19 disparities impedes prompt responses to newly emerged needs.…”