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With the emergence of social distancing, the shutdown of schools and restaurants, and increased anxieties about in- person farmers markets in early 2020, local farmers and food distributors quickly pivoted to digital tools to manage their farms and connect with buyers. In this paper, we explore the role of a seemingly simple digital tool in shaping alternative agrarian relations during the pandemic- induced local food boom: the spreadsheet. Through interviews with farmers and food distributors across urban, periurban, and rural landscapes in the United States (U.S.), we show how spreadsheets and other digital tools have helped farmers manage demand during the COVID- 19 pandemic while also presupposing costs, benefits, and efficiencies for these alternative agricultural food spaces. Ultimately, many local farmers found themselves pursuing goals of simplicity, labor efficiency, and expansion- oriented growth as they made sense of their farm data. Reflecting on these values, and the spreadsheet data underlying them, became a point of tension for farmers who place a high importance on diversification, stability, and interpersonal interactions. By attending to how these data are tracked, we gain deeper insights into how farmers and other stakeholders think about agrarian futures: who does the work, what gets planted, who's buying, and who benefits. [ABSTRACT FROM AUTHOR]

This paper first explores spatial distributions and patterns of COVID-19 case rates (cases/100,000 people) and mortality rates (deaths/100,000 people) and their disparities between urban and rural counties in the contiguous US. A county-level social vulnerability index was created using principal component analysis. Social vulnerability components were regressed against both county case and mortality rates. Results suggest that hotspots of case and mortality rates are clustered in Midwest and Upper-Midwest US. We found substantial disparities in case and mortality rates between urban and rural counties. County social vulnerability was positively correlated with both case and mortality rates suggesting counties with higher social vulnerability had higher case and mortality rates. Relationships between social vulnerability components and case and mortality rates vary across the conterminous US. Additionally, counties with increased racial and ethnic minorities, higher percentages of minors, and lower median household income are associated with higher COVID-19 case and mortality rates. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic and related restrictions led to major transit demand decline for many public transit systems in the United States. This paper is a systematic analysis of the dynamics and dimensions of this unprecedented decline. Using transit demand data derived from a widely used transit navigation app, we fit logistic functions to model the decline in daily demand and derive key parameters: base value, the apparent minimal level of demand and cliff and base points, representing the initial date when transit demand decline began and the final date when the decline rate attenuated. Regression analyses reveal that communities with higher proportions of essential workers, vulnerable populations (African American, Hispanic, Female, and people over 45 years old), and more coronavirus Google searches tend to maintain higher levels of minimal demand during COVID-19. Approximately half of the agencies experienced their decline before the local spread of COVID-19 likely began; most of these are in the US Midwest. Almost no transit systems finished their decline periods before local community spread. We also compare hourly demand profiles for each system before and during COVID-19 using ordinary Procrustes distance analysis. The results show substantial departures from typical weekday hourly demand profiles. Our results provide insights into public transit as an essential service during a pandemic. [ABSTRACT FROM AUTHOR]