Abstract

BackgroundNew York City (NYC) has been one of the hotspots of the COVID‐19 pandemic in the United States. By the end of April 2020, close to 165 000 cases and 13 000 deaths were reported in the city with considerable variability across the city's ZIP codes.ObjectivesIn this study, we examine: (a) the extent to which the variability in ZIP code‐level case positivity can be explained by aggregate markers of socioeconomic status (SES) and daily change in mobility; and (b) the extent to which daily change in mobility independently predicts case positivity.MethodsCOVID‐19 case positivity by ZIP code was modeled using multivariable linear regression with generalized estimating equations to account for within‐ZIP clustering. Daily case positivity was obtained from NYC Department of Health and Mental Hygiene and measures of SES were based on data from the American Community Survey. Changes in human mobility were estimated using anonymized aggregated mobile phone location systems.ResultsOur analysis indicates that the socioeconomic markers considered together explained 56% of the variability in case positivity through April 1 and their explanatory power decreased to 18% by April 30. Changes in mobility during this time period are not likely to be acting as a mediator of the relationship between ZIP‐level SES and case positivity. During the middle of April, increases in mobility were independently associated with decreased case positivity.ConclusionsTogether, these findings present evidence that heterogeneity in COVID‐19 case positivity during NYC’s spring outbreak was largely driven by residents’ SES.

Highlights

  • New York City (NYC) was severely impacted by the global COVID-19 pandemic, with a reported 164 505 cases, 42 417 hospitalizations and 13 000 laboratory-confirmed deaths through April 30, 2020.1 These represented 16.4% (5.3%) of cases and 24.8% (5.9%) of deaths nationally.[2]

  • Following on the observation that the proportion of uninsured adults is the most or second-most important variable in univariate analysis at all four time points, we examined the independent relationship between the proportion uninsured and percent positivity, adjusting for variables thought to act as confounders of the proportion uninsured→COVID-19 positivity relationship

  • On April 1, ZIP codes differing in change in mobility from baseline by 10% had mean case positivity proportions differ by 3.1%, with the higher case positivity among ZIP codes reducing mobility less

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Summary

Introduction

New York City (NYC) was severely impacted by the global COVID-19 pandemic, with a reported 164 505 cases, 42 417 hospitalizations and 13 000 laboratory-confirmed deaths through April 30, 2020.1 These represented 16.4% (5.3%) of cases and 24.8% (5.9%) of deaths nationally (globally).[2] The COVID-19 case positivity (the fraction of viral diagnostic tests that were positive) has been heterogeneous. Individuals living in wealthier ZIP codes may have found it easier to circumvent the restrictive initial testing guidelines on eligibility for a COVID-19 diagnostic test, resulting in a lower proportion receiving the test being COVID-19 positive. Objectives: In this study, we examine: (a) the extent to which the variability in ZIP code-level case positivity can be explained by aggregate markers of socioeconomic status (SES) and daily change in mobility; and (b) the extent to which daily change in mobility independently predicts case positivity. Conclusions: Together, these findings present evidence that heterogeneity in COVID19 case positivity during NYC’s spring outbreak was largely driven by residents’ SES

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