PDF(Pubmed)
Abstract：
BACKGROUND: The 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.
OBJECTIVE: This 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.
METHODS: In 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.
RESULTS: Of 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.
CONCLUSIONS: The 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.
OBJECTIVE: This 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.
METHODS: In 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.
RESULTS: Of 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.
CONCLUSIONS: The 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.
摘要：
背景：COVID-19大流行严重扰乱了食品零售环境。然而,它对新鲜水果和蔬菜供应商的影响尚不清楚；这些通常较小，更加以社区为中心，并且可能缺乏抵御此类危机引起的供需变化的金融基础设施。
目的：本研究记录了在COVID-19大流行开始后，纽约市（NYC）关闭新鲜水果和蔬菜供应商的方法，使用Google街景，新的苹果环顾四周数据库，和亲自检查。
方法：总共，选择了6个纽约市社区（曼哈顿和布鲁克林）进行分析；其中包括两个具有社会经济优势的社区（上东区，公园斜坡)，两个社会经济弱势社区(东哈林区，布朗斯维尔），和两个中国民族社区(唐人街，日落公园）。对于每个社区，谷歌街景被用来几乎走在每条街道上，识别供应商(商店，店面，街头小贩,或批发商)在2019年开放和活跃(即，生产人员和供应商人员都在一个地点)。过去的供应商监控（可用时）用于指导这些虚拟步行。每个确定的供应商都被地理标记为GoogleMaps，指出研究助理随后亲自访问。使用谷歌地图的“注释”功能作为数据收集工具，关于每个供应商描述得最好的三个类别中的哪一个：(1)开放，(2)以更有限的设置打开(例如，在2019年开放和活跃的供应商单位的某些部分在亲自检查期间丢失或关闭)，或（3）关闭/缺席。
结果：在2019年图像数据中确定的135个开放供应商中，在COVID-19大流行开始后，35%(n=47)缺席/关闭，10%(n=13)开放，设置更有限。当比较行政区时，曼哈顿35%(28/80)的供应商缺席/关闭，布鲁克林35%(19/55)的供应商也是如此。尽管Google街景能够为大多数社区提供2019年的街景图像数据，苹果环顾四周是2019年公园斜坡某些地区的图像数据所必需的。过去的监视数据有助于确定唐人街上另外3家在街景图像中遗漏的老牌供应商。谷歌地图“notes”功能被多个研究助理同时用于快速收集移动设备上的观测数据。
结论：所采用的方法能够识别新鲜水果和蔬菜零售环境中的关闭情况，并可用于评估其他环境中的关闭情况。使用过去的基线监视数据来帮助供应商识别对于识别在街景图像数据中可能不存在或在视觉上受到阻碍的供应商是有价值的。使用GoogleMaps进行数据收集同样有可能在未来的研究中提高实地考察的效率。
目的：本研究记录了在COVID-19大流行开始后，纽约市（NYC）关闭新鲜水果和蔬菜供应商的方法，使用Google街景，新的苹果环顾四周数据库，和亲自检查。
方法：总共，选择了6个纽约市社区（曼哈顿和布鲁克林）进行分析；其中包括两个具有社会经济优势的社区（上东区，公园斜坡)，两个社会经济弱势社区(东哈林区，布朗斯维尔），和两个中国民族社区(唐人街，日落公园）。对于每个社区，谷歌街景被用来几乎走在每条街道上，识别供应商(商店，店面，街头小贩,或批发商)在2019年开放和活跃(即，生产人员和供应商人员都在一个地点)。过去的供应商监控（可用时）用于指导这些虚拟步行。每个确定的供应商都被地理标记为GoogleMaps，指出研究助理随后亲自访问。使用谷歌地图的“注释”功能作为数据收集工具，关于每个供应商描述得最好的三个类别中的哪一个：(1)开放，(2)以更有限的设置打开(例如，在2019年开放和活跃的供应商单位的某些部分在亲自检查期间丢失或关闭)，或（3）关闭/缺席。
结果：在2019年图像数据中确定的135个开放供应商中，在COVID-19大流行开始后，35%(n=47)缺席/关闭，10%(n=13)开放，设置更有限。当比较行政区时，曼哈顿35%(28/80)的供应商缺席/关闭，布鲁克林35%(19/55)的供应商也是如此。尽管Google街景能够为大多数社区提供2019年的街景图像数据，苹果环顾四周是2019年公园斜坡某些地区的图像数据所必需的。过去的监视数据有助于确定唐人街上另外3家在街景图像中遗漏的老牌供应商。谷歌地图“notes”功能被多个研究助理同时用于快速收集移动设备上的观测数据。
结论：所采用的方法能够识别新鲜水果和蔬菜零售环境中的关闭情况，并可用于评估其他环境中的关闭情况。使用过去的基线监视数据来帮助供应商识别对于识别在街景图像数据中可能不存在或在视觉上受到阻碍的供应商是有价值的。使用GoogleMaps进行数据收集同样有可能在未来的研究中提高实地考察的效率。
