ArticleResearch square2024
Inequities in food access during the COVID19 pandemic: a multilevel, mixed methods pilot study.
Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
The trial behind it
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Authors and funding
10 authors.
Funding
Abstract
Background: Innovative data integration may serve to inform rapid, local responses to community needs. We conducted a mixed methods pilot study among communities of color or low-income in the San Francisco Bay Area amid the COVID-19 pandemic to assess a hypothesized data model to inform rapid response efforts. Methods: Between 2020-2021, we collected (1) qualitative data through neighborhood reports submitted via Streetwyze, a mobile neighborhood mapping platform; (2) survey data on social and economic circumstances; and (3) geospatial data among residents of three counties. Qualitative data were coded and then integrated with survey and geospatial data. We used descriptive analyses to examine participants' experiences with food in their neighborhoods. Results: Seventy percent of participants reported food insecurity before and after the pandemic began in March 2020. Within neighborhood reports, Conclusion: Individuals who were food insecure reported a constellation of needs beyond food, including needs related to safety and greater social equity. Our data model illustrates the potential for rapid assessment of community residents' experiences to provide enhanced understanding of community-level needs and effective support in the face of changing circumstances.
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