Leveraging Administrative Data for Bias Audits

Coston, Amanda; Guha, Neel; Ouyang, Derek; Lu, Lisa; Chouldechova, Alexandra; Ho, Daniel E.

doi:10.1145/3442188.3445881

Cited by 44 publications

(23 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With respect to cell phone data, all of the typical limitations of geo-tracking apply, with certain groups such as older residents less likely to be represented (Coston et al, 2021). Overall, although only 10% of urban residents are represented in SafeGraph data, the company's sampling is highly correlated with true census populations (Kang et al, 2020;SafeGraph, 2021b).…”

Section: Limitations and Future Researchmentioning

confidence: 99%

Urban Park Use During the COVID-19 Pandemic: Are Socially Vulnerable Communities Disproportionately Impacted?

Larson

Zhang

et al. 2021

Front. Sustain. Cities

View full text Add to dashboard Cite

The COVID-19 pandemic altered human behavior around the world. To maintain mental and physical health during periods of lockdown and quarantine, people often engaged in outdoor, physically distanced activities such as visits to parks and greenspace. However, research tracking outdoor recreation patterns during the pandemic has yielded inconsistent results, and few studies have explored the impacts of COVID-19 on park use across diverse neighborhoods. We used a mixed methods approach to examine changes in park use patterns in cities across North Carolina, USA, during the COVID-19 pandemic, with an emphasis on impacts in socially vulnerable communities (based on racial/ethnic composition and socioeconomic status). First, we surveyed a demographically representative sample of 611 urban residents during August 2020 to assess their use of outdoor park spaces before and during the pandemic. Second, we used cell phone location (i.e., geo-tracking) data to document changes in park visits within 605 socioeconomically diverse urban census tracts before (July 2019) and during (July 2020) the pandemic. Data from both methods revealed urban park use declined during the pandemic; 56% of survey respondents said they stopped or reduced park use, and geo-tracked park visits dropped by 15%. Park users also became more homogenous, with visits increasing the most for past park visitors and declining the most in socially vulnerable communities and among individuals who were BIPOC or lower-income. Our results raise concerns about urban park use during the COVID-19 pandemic and suggest pre-existing health disparities in socially vulnerable communities might be exacerbated by inequitable access and utilization of parks and greenspace.

show abstract

Section: Limitations and Future Researchmentioning

confidence: 99%

Urban Park Use During the COVID-19 Pandemic: Are Socially Vulnerable Communities Disproportionately Impacted?

Larson

Zhang

et al. 2021

Front. Sustain. Cities

View full text Add to dashboard Cite

show abstract

“…Based on an analysis done by Safegraph, the panel is representative of race, educational attainment, and income ( Fox, 2019 ). On the other hand, a recent independent analysis shows that older and non-white individuals are less likely to be captured in the panel for POI-specific analyses ( Coston et al, 2021 ). It is important to note that both studies are associative in nature as the devices in the panel are fully anonymized, so no device-level demographic data exists.…”

Section: Discussionmentioning

confidence: 99%

“…It is important to note that both studies are associative in nature as the devices in the panel are fully anonymized, so no device-level demographic data exists. Continued work to understand the sampling biases of such datasets will be needed so that improved bias correction approaches can be developed ( Coston et al, 2021 ). Additionally, we limit our scope in this study to consider only the number of visits and do not incorporate information about visit duration.…”

Section: Discussionmentioning

confidence: 99%

Disentangling the rhythms of human activity in the built environment for airborne transmission risk: An analysis of large-scale mobility data

Susswein

Rest

Bansal

2023

eLife

View full text Add to dashboard Cite

Background: Since the outset of the COVID-19 pandemic, substantial public attention has focused on the role of seasonality in impacting transmission. Misconceptions have relied on seasonal mediation of respiratory diseases driven solely by environmental variables. However, seasonality is expected to be driven by host social behavior, particularly in highly susceptible populations. A key gap in understanding the role of social behavior in respiratory disease seasonality is our incomplete understanding of the seasonality of indoor human activity.Methods: We leverage a novel data stream on human mobility to characterize activity in indoor versus outdoor environments in the United States. We use an observational mobile app-based location dataset encompassing over 5 million locations nationally. We classify locations as primarily indoor (e.g. stores, offices) or outdoor (e.g. playgrounds, farmers markets), disentangling location-specific visits into indoor and outdoor, to arrive at a fine-scale measure of indoor to outdoor human activity across time and space.Results: We find the proportion of indoor to outdoor activity during a baseline year is seasonal, peaking in winter months. The measure displays a latitudinal gradient with stronger seasonality at northern latitudes and an additional summer peak in southern latitudes. We statistically fit this baseline indoor-outdoor activity measure to inform the incorporation of this complex empirical pattern into infectious disease dynamic models. However, we find that the disruption of the COVID-19 pandemic caused these patterns to shift significantly from baseline, and the empirical patterns are necessary to predict spatiotemporal heterogeneity in disease dynamics.Conclusions: Our work empirically characterizes, for the first time, the seasonality of human social behavior at a large scale with high spatiotemporal resolution, and provides a parsimonious parameterization of seasonal behavior that can be included in infectious disease dynamics models. We provide critical evidence and methods necessary to inform the public health of seasonal and pandemic respiratory pathogens and improve our understanding of the relationship between the physical environment and infection risk in the context of global change.Funding: Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM123007.

show abstract

“…Another limitation of MPS data is that some minor groups (e.g. children or the elderly) are likely to be underrepresented ( Coston et al, 2021 ), and only 5% of Shenzhen residents are employed for measure the park visits in our study. The combination of multiple sources of MPS big data and surveyed data of specific subpopulations might be a solution to these representative issues in the future.…”

Section: Discussionmentioning

confidence: 99%

A quasi-experimental analysis on the causal effects of COVID-19 on urban park visits: The role of park features and the surrounding built environment

Zhang¹,

Li²

2023

Urban Forestry & Urban Greening

View full text Add to dashboard Cite

Leveraging Administrative Data for Bias Audits

Cited by 44 publications

References 24 publications

Urban Park Use During the COVID-19 Pandemic: Are Socially Vulnerable Communities Disproportionately Impacted?

Urban Park Use During the COVID-19 Pandemic: Are Socially Vulnerable Communities Disproportionately Impacted?

Disentangling the rhythms of human activity in the built environment for airborne transmission risk: An analysis of large-scale mobility data

A quasi-experimental analysis on the causal effects of COVID-19 on urban park visits: The role of park features and the surrounding built environment

Contact Info

Product

Resources

About