Evidence map›Paper›PMID 33539310›Full record

ArticleJMIR formative research2021

Evaluating Closures of Fresh Fruit and Vegetable Vendors During the COVID-19 Pandemic: Methodology and Preliminary Results Using Omnidirectional Street View Imagery.

Shahmir H Ali, Valerie M Imbruce, Rienna G Russo, Samuel Kaplan, Kaye Stevenson, Tamar Adjoian Mezzacca, Victoria Foster, Ashley Radee, Stella Chong, Felice Tsui and 2 more

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.1field-weighted citation impact, top 5% of its field
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

10 citing papers in PubMed, 16 citations in OpenAlex.

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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

12 authors at 4 institutions in 1 country.

Shahmir H AliDepartment of Social and Behavioral Sciences, School of Global Public Health, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-0360-3507
Valerie M ImbruceEnvironmental Studies Program, Binghamton University, State University of New York, New York, NY, United States.ORCID https://orcid.org/0000-0002-3223-5248
Rienna G RussoDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-4502-9360
Samuel KaplanChatham High School, Chatham, NJ, United States.ORCID https://orcid.org/0000-0002-9903-6630
Kaye StevensonChatham High School, Chatham, NJ, United States.ORCID https://orcid.org/0000-0003-0904-6155
Victoria FosterDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0001-8869-9511
Ashley RadeeDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-4038-2026
Stella ChongDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0002-0509-2173
Felice TsuiMailman School of Public Health, Columbia University, New York, NY, United States.ORCID https://orcid.org/0000-0002-4033-7236
Julie KranickDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-0526-0330
Stella S YiDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0002-9943-2609
New York University · USChatham University · USBinghamton University · USColumbia University · US

Funding

Scaling Community-Clinical Linkage Models to Address Diabetes and Hypertension Disparities in the Southeastern U.S.U54MD000538 · NIMHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI KWON, SIMONA, TRINH-SHEVRIN, CHAU · 2017 to 2022
$11.3M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
Assessment of Policies through Prediction of Long-term Effects on Cardiovascular Disease Using Simulation (APPLE CDS)R01HL141427 · NHLBI · NEW YORK ACADEMY OF MEDICINE · PI LIU, BIAN, YI, STELLA S · 2018 to 2021
$3.5M
NHLBI NIH HHS R01 HL141427NIDDK NIH HHS P30 DK111022NIMHD NIH HHS U54 MD000538
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has significantly disrupted the food retail environment. However, its impact on fresh fruit and vegetable vendors remains unclear; these are often smaller, more community centered, and may lack the financial infrastructure to withstand supply and demand changes induced by such crises.

objectiveThis study documents the methodology used to assess fresh fruit and vegetable vendor closures in New York City (NYC) following the start of the COVID-19 pandemic by using Google Street View, the new Apple Look Around database, and in-person checks.

methodsIn total, 6 NYC neighborhoods (in Manhattan and Brooklyn) were selected for analysis; these included two socioeconomically advantaged neighborhoods (Upper East Side, Park Slope), two socioeconomically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, Google Street View was used to virtually walk down each street and identify vendors (stores, storefronts, street vendors, or wholesalers) that were open and active in 2019 (ie, both produce and vendor personnel were present at a location). Past vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was geotagged as a Google Maps pinpoint that research assistants then physically visited. Using the "notes" feature of Google Maps as a data collection tool, notes were made on which of three categories best described each vendor: (1) open, (2) open with a more limited setup (eg, certain sections of the vendor unit that were open and active in 2019 were missing or closed during in-person checks), or (3) closed/absent.

resultsOf the 135 open vendors identified in 2019 imagery data, 35% (n=47) were absent/closed and 10% (n=13) were open with more limited setups following the beginning of the COVID-19 pandemic. When comparing boroughs, 35% (28/80) of vendors in Manhattan were absent/closed, as were 35% (19/55) of vendors in Brooklyn. Although Google Street View was able to provide 2019 street view imagery data for most neighborhoods, Apple Look Around was required for 2019 imagery data for some areas of Park Slope. Past surveillance data helped to identify 3 additional established vendors in Chinatown that had been missed in street view imagery. The Google Maps "notes" feature was used by multiple research assistants simultaneously to rapidly collect observational data on mobile devices.

conclusionsThe methodology employed enabled the identification of closures in the fresh fruit and vegetable retail environment and can be used to assess closures in other contexts. The use of past baseline surveillance data to aid vendor identification was valuable for identifying vendors that may have been absent or visually obstructed in the street view imagery data. Data collection using Google Maps likewise has the potential to enhance the efficiency of fieldwork in future studies.

Indexed as

built environmentCOVID-19demandeconomyfoodfood retail environmentgeographic surveillanceGoogle Street Viewlongitudinalservicesupply chainsurveillancevendor

Identifiers

PMID33539310
PMCPMC7894620
OpenAlexW3127578276

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.