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1. Recreational mobility prior and during the COVID-19 pandemic

   https://doi.org/10.1038/s42005-024-01535-7  

   Ghadiri, Zahra; Mashhadi, Afra; Timme, Marc; Ghanbarnejad, Fakhteh (December 2024, Communications Physics)

   Abstract The COVID-19 pandemic and the resulting economic recession negatively affected many people’s physical, social, and psychological health and has been shown to change population-level mobility, but little attention has been given to park visitations as an indicator. Estimating the frequency of park visitations from aggregated mobility data of all the parks in Washington State (USA), we study trends in park use one year prior to and two years during the COVID-19 pandemic. Our findings indicate that the gravity model is a robust model for the park visitation behavior in different spatial resolutions of city level and state level and different socio-economical classes. Incorporating network structure, our detailed analysis highlights that high-income level residents changed their recreational behavior by visiting their local parks more and a broader recreational options outside of their local census area; whereas the low-income residents changed their visitation behavior by reducing their recreational choices. 

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2. Examining human mobility changes during COVID-19 across socioeconomic groups: a comparative analysis of San Diego County and New York City

   https://doi.org/10.1007/s43762-024-00133-1  

   Park, Jaehee; Tsou, Ming-Hsiang; Nara, Atsushi; Dodge, Somayeh; Cassels, Susan (December 2024, Computational Urban Science)

   Abstract The COVID-19 pandemic brought unprecedented changes to various aspects of daily life, profoundly affecting human mobility. These changes in mobility patterns were not uniform, as numerous factors, including public health measures, socioeconomic status, and urban infrastructure, influenced them. This study examines human mobility changes during COVID-19 in San Diego County and New York City, employing Latent Profile Analysis (LPA) and various network measures to analyze connectivity and socioeconomic status (SES) within these regions. While many COVID-19 and mobility studies have revealed overall reductions in mobility or changes in mobility patterns, they often fail to specify ’where’ these changes occur and lack a detailed understanding of the relationship between SES and mobility changes. This creates a significant research gap in understanding the spatial and socioeconomic dimensions of mobility changes during the pandemic. This study aims to address this gap by providing a comprehensive analysis of how mobility patterns varied across different socioeconomic groups during the pandemic. By comparing mobility patterns before and during the pandemic, we aim to shed light on how this unprecedented event impacted different communities. Our research contributes to the literature by employing network science to examine COVID-19’s impact on human mobility, integrating SES variables into the analysis of mobility networks. This approach provides a detailed understanding of how social and economic factors influence movement patterns and urban connectivity, highlighting disparities in mobility and access across different socioeconomic groups. The results identify areas functioning as hubs or bridges and illustrate how these roles changed during COVID-19, revealing existing societal inequalities. Specifically, we observed that urban parks and rural areas with national parks became significant mobility hubs during the pandemic, while affluent areas with high educational attainment saw a decline in centrality measures, indicating a shift in urban mobility dynamics and exacerbating pre-existing socioeconomic disparities. 

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3. Parks are Critical Urban Infrastructure: Perception and Use of Urban Green Spaces in NYC During COVID-19

   https://doi.org/10.20944/preprints202008.0620.v1  

   Lopez, B. (August 2020, Preprints)

   null (Ed.)

   Urban green spaces provide a range of environmental and health benefits, which may become even more critical during times of crisis such as the current COVID-19 pandemic. However, with a radical shift in mobility, additional concerns over safety, and access temporarily restricted during the implementation of social distancing policies, the experience and use of urban green spaces may be reduced. This is particularly concerning for densely populated cities like New York, considered the first U.S. epicenter or vanguard of the outbreak. To better understand the impact of COVID-19 on the perception and use of urban green spaces, we conducted a social survey during the early months of the Covid-19 pandemic in New York City (May 13 - June 15, 2020). The results of the survey show respondents continued to use urban green spaces during the pandemic and consider them to be more important for mental and physical health than before the pandemic began. However, the study revealed a pattern of concerns residents have about green space accessibility and safety, and found key differences between the concerns and needs of different populations, suggesting a crucial role for inclusive decision-making, support for additional management strategies, and urban ecosystem governance that reflect the differential values, needs and concerns of communities across the City. As urban centers face looming budget cuts and reduced capacity, this study provides some empirical evidence to illustrate the value of urban green spaces as critical urban infrastructure, and may have implications for funding, policy, and management, of urban green spaces in NYC, with potential applications to other cities, particularly during times of crisis. 

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4. Spatiotemporal Patterns of Human Mobility and Its Association with Land Use Types during COVID-19 in New York City

   https://doi.org/10.3390/ijgi10050344  

   Jiang, Yuqin; Huang, Xiao; Li, Zhenlong (May 2021, ISPRS International Journal of Geo-Information)

   The novel coronavirus disease (COVID-19) pandemic has impacted every facet of society. One of the non-pharmacological measures to contain the COVID-19 infection is social distancing. Federal, state, and local governments have placed multiple executive orders for human mobility reduction to slow down the spread of COVID-19. This paper uses geotagged tweets data to reveal the spatiotemporal human mobility patterns during this COVID-19 pandemic in New York City. With New York City open data, human mobility pattern changes were detected by different categories of land use, including residential, parks, transportation facilities, and workplaces. This study further compares human mobility patterns by land use types based on an open social media platform (Twitter) and the human mobility patterns revealed by Google Community Mobility Report cell phone location, indicating that in some applications, open-access social media data can generate similar results to private data. The results of this study can be further used for human mobility analysis and the battle against COVID-19. 

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5. Measuring sensitivity to social distancing behavior during the COVID-19 pandemic

   https://doi.org/10.1038/s41598-022-20198-4  

   Kontokosta, Constantine E.; Hong, Boyeong; Bonczak, Bartosz J. (September 2022, Scientific Reports)

   Abstract Social distancing remains an effective nonpharmaceutical behavioral interventions to limit the spread of COVID-19 and other airborne diseases, but monitoring and enforcement create nontrivial challenges. Several jurisdictions have turned to “311” resident complaint platforms to engage the public in reporting social distancing non-compliance, but differences in sensitivity to social distancing behaviors can lead to a mis-allocation of resources and increased health risks for vulnerable communities. Using hourly visit data to designated establishments and more than 71,000 social distancing complaints in New York City during the first wave of the pandemic, we develop a method, derived from the Weber-Fechner law, to quantify neighborhood sensitivity and assess how tolerance to social distancing infractions and complaint reporting behaviors vary with neighborhood characteristics. We find that sensitivity to non-compliance is lower in minority and low-income neighborhoods, as well as in lower density areas, resulting in fewer reported complaints than expected given measured levels of overcrowding. 

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