COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data
- URL: http://arxiv.org/abs/2405.11121v1
- Date: Fri, 17 May 2024 23:30:20 GMT
- Title: COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data
- Authors: Saad Mohammad Abrar, Kazi Tasnim Zinat, Naman Awasthi, Vanessa Frias-Martinez,
- Abstract summary: This study examines the changes in small urban restaurant visitation patterns following the COVID-19 pandemic.
We investigate differences in visitation pattern changes across Census Block Groups with majority Asian, Black, Hispanic, White, and American Indian populations.
Our results show clear indications of reduced visitation patterns after the pandemic, with slow recoveries.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Early in the pandemic, counties and states implemented a variety of non-pharmacological interventions (NPIs) focused on mobility, such as national lockdowns or work-from-home strategies, as it became clear that restricting movement was essential to containing the epidemic. Due to these restrictions, businesses were severely affected and in particular, small, urban restaurant businesses. In addition to that, COVID-19 has also amplified many of the socioeconomic disparities and systemic racial inequities that exist in our society. The overarching objective of this study was to examine the changes in small urban restaurant visitation patterns following the COVID-19 pandemic and associated mobility restrictions, as well as to uncover potential disparities across different racial/ethnic groups in order to understand inequities in the impact and recovery. Specifically, the two key objectives were: 1) to analyze the overall changes in restaurant visitation patterns in US metropolitan areas during the pandemic compared to a pre-pandemic baseline, and 2) to investigate differences in visitation pattern changes across Census Block Groups with majority Asian, Black, Hispanic, White, and American Indian populations, identifying any disproportionate effects. Using aggregated geolocated cell phone data from SafeGraph, we document the overall changes in small urban restaurant businesses' visitation patterns with respect to racial composition at a granularity of Census Block Groups. Our results show clear indications of reduced visitation patterns after the pandemic, with slow recoveries. Via visualizations and statistical analyses, we show that reductions in visitation patterns were the highest for small urban restaurant businesses in majority Asian neighborhoods.
Related papers
- The Factuality Tax of Diversity-Intervened Text-to-Image Generation: Benchmark and Fact-Augmented Intervention [61.80236015147771]
We quantify the trade-off between using diversity interventions and preserving demographic factuality in T2I models.
Experiments on DoFaiR reveal that diversity-oriented instructions increase the number of different gender and racial groups.
We propose Fact-Augmented Intervention (FAI) to reflect on verbalized or retrieved factual information about gender and racial compositions of generation subjects in history.
arXiv Detail & Related papers (2024-06-29T09:09:42Z) - Mobility Segregation Dynamics and Residual Isolation During Pandemic
Interventions [0.0]
We study the reorganisation of mobility segregation networks due to external shocks during pandemics.
We build on anonymised and privacy-preserved mobility data in four cities: Bogota, Jakarta, London, and New York.
We find that the first lockdowns induced considerable increases in mobility segregation in each city, while loosening mobility restrictions did not necessarily diminished isolation between different socioeconomic groups.
arXiv Detail & Related papers (2023-10-05T14:08:44Z) - Estimating Geographic Spillover Effects of COVID-19 Policies From
Large-Scale Mobility Networks [54.90772000796717]
County-level policies provide flexibility between regions, but may become less effective in the presence of geographic spillovers.
We estimate spillovers using a mobility network with billions of timestamped edges.
We find that county-level restrictions are only 54% as effective as statewide restrictions at reducing mobility.
arXiv Detail & Related papers (2022-12-12T20:16:54Z) - Evaluating shifts in mobility and COVID-19 case rates in U.S. counties:
A demonstration of modified treatment policies for causal inference with
continuous exposures [0.0]
We examined the impact of shifting the distribution of mobility on COVID-19 case rates from June 1 - November 14, 2020.
Ten mobility indices were selected to capture several aspects of behavior expected to influence and be influenced by COVID-19 case rates.
arXiv Detail & Related papers (2021-10-24T21:17:47Z) - Impact of COVID-19 Policies and Misinformation on Social Unrest [0.0]
We focus on the interplay between social unrest (protests), health outcomes, public health orders, and misinformation in eight countries of Western Europe and four regions of the United States.
We created 1-3 week forecasts of both a binary protest metric for identifying times of high protest activity and the overall protest counts over time.
We found that for all regions, except Belgium, at least one feature from our various data streams was predictive of protests.
arXiv Detail & Related papers (2021-10-07T16:05:10Z) - Living in a pandemic: adaptation of individual mobility and social
activity in the US [4.311304158111146]
We study how individuals adapted their daily movements and person-to-person contact patterns over time in response to the COVID-19 pandemic and the NPIs.
We find that local interventions did not just impact the number of visits to different venues but also how people experience them.
Individuals spend less time in venues, preferring simpler and more predictable routines and reducing person-to-person contact activities.
arXiv Detail & Related papers (2021-07-26T14:27:22Z) - Local Black-box Adversarial Attacks: A Query Efficient Approach [64.98246858117476]
Adrial attacks have threatened the application of deep neural networks in security-sensitive scenarios.
We propose a novel framework to perturb the discriminative areas of clean examples only within limited queries in black-box attacks.
We conduct extensive experiments to show that our framework can significantly improve the query efficiency during black-box perturbing with a high attack success rate.
arXiv Detail & Related papers (2021-01-04T15:32:16Z) - C-Watcher: A Framework for Early Detection of High-Risk Neighborhoods
Ahead of COVID-19 Outbreak [54.39837683016444]
C-Watcher aims at screening every neighborhood in a target city and predicting infection risks, prior to the spread of COVID-19 from epicenters to the city.
C-Watcher collects large-scale long-term human mobility data from Baidu Maps, then characterizes every residential neighborhood in the city using a set of features based on urban mobility patterns.
We carried out extensive experiments on C-Watcher using the real-data records in the early stage of COVID-19 outbreaks.
arXiv Detail & Related papers (2020-12-22T17:02:54Z) - COVID-19 and Social Distancing: Disparities in Mobility Adaptation
between Income Groups [0.8599681538174887]
There has been little research on the disparity of mobility adaptation across different income groups during the pandemic.
The study illuminates an equity issue which may be of interest to policy makers and researchers alike in the wake of an epidemic.
arXiv Detail & Related papers (2020-11-25T04:26:08Z) - Effectiveness and Compliance to Social Distancing During COVID-19 [72.94965109944707]
We use a detailed set of mobility data to evaluate the impact that stay-at-home orders had on the spread of COVID-19 in the US.
We show that there is a unidirectional Granger causality, from the median percentage of time spent daily at home to the daily number of COVID-19-related deaths with a lag of 2 weeks.
arXiv Detail & Related papers (2020-06-23T03:36:19Z) - Measuring Spatial Subdivisions in Urban Mobility with Mobile Phone Data [58.720142291102135]
By 2050 two thirds of the world population will reside in urban areas.
This growth is faster and more complex than the ability of cities to measure and plan for their sustainability.
To understand what makes a city inclusive for all, we define a methodology to identify and characterize spatial subdivisions.
arXiv Detail & Related papers (2020-02-20T14:37:46Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.