JMIR Publications

ABSTRACT

Background:

The COVID-19 pandemic has disrupted different facets of the food retail environment, however its impact on smaller fruit and vegetable (FV) vendors (which are often community-based and may not have the financial infrastructure to withstand changes in supply and demand induced by the COVID-19 pandemic) remains unclear.

Objective:

This study documents the methodology used to assess service changes among FV vendors in New York City (NYC) following the COVID-19 pandemic by using Google Street View (GSV), the new Apple Look Around database, and in-person checks.

Methods:

Six NYC neighborhoods were selected for analysis in Manhattan and Brooklyn; two socio-economically advantaged neighborhoods (Upper East Side, Park Slope), two socio-economically disadvantaged neighborhoods (East Harlem, Brownsville), and two Chinese ethnic neighborhoods (Chinatown, Sunset Park). For each neighborhood, GSV and Apple Look Around were used to virtually walk down each street and identify FV vendors (stores, storefronts, street vendors, or wholesalers) which were open and active in 2019 imagery data; past FV vendor surveillance (when available) was used to guide these virtual walks. Each identified vendor was then geotagged as a Google Maps pinpoint. Research assistants then conducted socially distanced in-person checks to each site and, using the “notes” feature of Google Maps as a data collection tool, made notes on whether each vendor was open, open with limited services, or closed/absent.

Results:

A total of 135 vendors confirmed to be open in 2019 were identified; 80 vendors in the Manhattan neighborhoods (56 in Chinatown, 12 on the Upper East side, and 12 in East Harlem) and 55 vendors in the Brooklyn neighborhoods (48 in Sunset Park, 4 in Park Slope, and 3 in Brownsville). Overall, 44% of vendors were either absent/closed or had limited services following COVID-19.

Conclusions:

The triangulated methodology was effective in identifying changes in the FV retail environment and can be employed to assess COVID-19 changes in other contexts. The use of past baseline surveillance to assist GSV-based FV vendor identification was found to be valuable. Apple Look Around was likewise effectively able to provide updated 2019 NYC imagery data when 2019 GSV imagery was not available. The Google Maps “notes” feature was able to provide real-time information to multiple members of the study team; the platform can significantly enhance the efficiency of field work for future studies.