Evidence map›Paper›PMID 36049353›Full record

ArticleSocial science & medicine (1982)2022

Inequities in spatial accessibility to COVID-19 testing in 30 large US cities.

Pricila H Mullachery, Ran Li, Steven Melly, Jennifer Kolker, Sharrelle Barber, Ana V Diez Roux, Usama Bilal

Abstract read
In one paragraph

Article in Social science & medicine (1982), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Pricila H MullacheryUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA; Department of Health Services Administration and Policy, Temple University College of Public Health, 1301 Cecil B. Moore Ave, Philadelphia, PA, 19122, USA. Electronic address: pricila.mullachery@temple.edu.
Ran LiUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA.
Steven MellyUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA.
Jennifer KolkerDepartment of Health Management and Policy, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA.
Sharrelle BarberUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA; Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA; Ubuntu Center on Racism, Global Movements, and Population Health Equity, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA.
Ana V Diez RouxUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA; Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA.
Usama BilalUrban Health Collaborative, Drexel Dornsife School of Public Health, 3600 Market St, Philadelphia, PA, 19104, USA; Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, 3215 Market St, Philadelphia, PA, 19104, USA.

Funding

The Health Consequences of Urban ScalingDP5OD026429 · OD · DREXEL UNIVERSITY · PI BILAL, USAMA · 2018 to 2022
$2.7M
NIH HHS DP5 OD026429
6 · The paper itself

Abstract

Testing for SARS-CoV-2 infection has been a key strategy to mitigate and control the COVID-19 pandemic. Wide spatial and racial/ethnic disparities in COVID-19 outcomes have emerged in US cities. Previous research has highlighted the role of unequal access to testing as a potential driver of these disparities. We described inequities in spatial accessibility to COVID-19 testing locations in 30 large US cities. We used location data from Castlight Health Inc corresponding to October 2021. We created an accessibility metric at the level of the census block group (CBG) based on the number of sites per population in a 15-minute walkshed around the centroid of each CBG. We also calculated spatial accessibility using only testing sites without restrictions, i.e., no requirement for an appointment or a physician order prior to testing. We measured the association between the social vulnerability index (SVI) and spatial accessibility using a multilevel negative binomial model with random city intercepts and random SVI slopes. Among the 27,195 CBG analyzed, 53% had at least one testing site within a 15-minute walkshed, and 36% had at least one site without restrictions. On average, a 1-decile increase in the SVI was associated with a 3% (95% Confidence Interval: 2% - 4%) lower accessibility. Spatial inequities were similar across various components of the SVI and for sites with no restrictions. Despite this general pattern, several cities had inverted inequity, i.e., better accessibility in more vulnerable areas, which indicates that some cities may be on the right track when it comes to promoting equity in COVID-19 testing. Testing is a key component of the strategy to mitigate transmission of SARS-CoV-2 and efforts should be made to improve accessibility to testing, particularly as new and more contagious variants become dominant.

Indexed as

COVID-19COVID-19 TestingCitiesHumansPandemicsSARS-CoV-2COVID-19GISHealth disparitiesHealth equityTestingUrban health

Identifiers

PMID36049353
PMCPMC9420026

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.