Spatial Variation in COVID-19 Mortality in New York City and Its Association with Neighborhood Race, Ethnicity, and Nativity Status

We examined the association between variation in COVID-19 deaths and spatial differences in the racial, ethnic, and nativity-status composition of New York City neighborhoods, which has received little scholarly attention. Using COVID-19 mortality data (through 31 May 2021) and socioeconomic and demographic data from the American Community Survey at the Zip Code Tabulation Area level as well as United-Hospital-Fund-level neighborhood data from the Community Health Survey of the New York City Department of Health and Mental Hygiene, we employed multivariable Poisson generalized estimating equation models and assessed the association between COVID-19 mortality, racial/ethnic/nativity-status composition, and other ecological factors. Our results showed an association between neighborhood-level racial and ethnic composition and COVID-19 mortality rates that is contingent upon the neighborhood-level nativity-status composition. After multivariable adjustment, ZCTAs with large shares of native-born Blacks and foreign-born Hispanics and Asians were more likely to have higher COVID-19 mortality rates than areas with large shares of native-born Whites. Areas with more older adults and essential workers, higher levels of household crowding, and population with diabetes were also at high risk. Small-area analyses of COVID-19 mortality can inform health policy responses to neighborhood inequalities on the basis of race, ethnicity, and immigration status.

Interactive impacts of walkability, social vulnerability, & travel behavior on COVID-19 mortality: A hierarchical Bayesian spatial random parameter approach

While existing research highlights the built and social environment impacts on COVID-19 mortality, no empirical evidence exists on how the built and social environments may interact to influence COVID-19 mortality. This study presents a rigorous empirical assessment of the interactive impacts of social vulnerability and walkability on neighborhood-level COVID-19 mortality rates. Based in King County, WA, a unique data infrastructure is created by spatially integrating diverse census tract-level data on COVID-19 mortalities, walkability characteristics, social vulnerability, and travel behavior measures. Advanced Markov Chain Monte Carlo (MCMC) based Full Bayes hierarchical spatial random parameter models are developed to simultaneously capture spatial and unobserved random heterogeneity. Around 46% of the neighborhoods had opposite levels of walkability and social vulnerability. Compared to low walkability and high social vulnerability, neighborhoods with high walkability and low social vulnerability (i.e., best case scenario) had on average 20.2% (95% Bayesian CI: -37.2% to -3.3%) lower COVID-19 mortality rates. Analysis of the interactive impacts when only one of the social and built environment metrics was in a healthful direction revealed significant offsetting effects - suggesting that the underlying structural social vulnerability issues faced by our communities should be addressed first for the infectious disease-related health impacts of walkable urban design to be observed. Concerning travel behavior, the findings indicate that COVID-19 mortality rates may be reduced by discouraging auto use and encouraging active transportation. The study methodologically contributes by simultaneously capturing spatial and unobserved heterogeneity in a holistic Full Bayesian framework.

The effects of audio-visual perceptual characteristics on environmental health of pedestrian streets with traffic noise: A case study in Dalian, China

The COVID-19 pandemic has affected city dwellers’ physical and mental health and has raised concerns about the health of urban public spaces. This field investigation research in Dalian, China, examined the perceived audio-visual environment characteristics of urban pedestrian streets with traffic noise and their influences on the environmental health of the pedestrian streets. Five indicators reflecting psychological responses to environmental characteristics (willingness to walk, relaxation, safety, beauty, and comprehensive comfort) were used to measure environmental health of pedestrian streets with traffic noise. The results showed that safety was rated the highest, and willingness to walk was evaluated as the lowest among health evaluation indicators. The imageability and openness of the streetscape were associated with each health evaluation indicator. In contrast, the rhythm and continuity of the street buildings had a greater effect on willingness to walk than the other health indicators. There were negative correlations between LAeq for traffic noise and health evaluations. Positive health evaluations were observed when LAeq was less than 55 dBA. In contrast, soundscape indicators showed positive correlations with health evaluations, and acoustic comfort and noise annoyance, rather than sound preference and subjective loudness were associated with each health evaluation indicator. In terms of the combined audio-visual factors, acoustic comfort, the quantity of greening, annoyance, sky visibility, spatial scale, and building distance were examined as the determining factors affecting health evaluations, and 55.40% of the variance in health evaluations was explained by the soundscape and streetscape indicators. The findings provide references for better understanding the relationships between healthy experience and audio-visual perceptions. Moreover, they enable environmental health quality optimisation of pedestrian spaces considering audio-visual indicators and approaches in the post-epidemic era.

COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities

COVID-19 has exacerbated endemic health inequalities resulting in a syndemic pandemic of higher mortality and morbidity rates among the most socially disadvantaged. We did a scoping review to identify and synthesise published evidence on geographical inequalities in COVID-19 mortality rates globally. We included peer-reviewed studies, from any country, written in English that showed any area-level (eg, neighbourhood, town, city, municipality, or region) inequalities in mortality by socioeconomic deprivation (ie, measured via indices of multiple deprivation: the percentage of people living in poverty or proxy factors including the Gini coefficient, employment rates, or housing tenure). 95 papers from five WHO global regions were included in the final synthesis. A large majority of the studies (n=86) found that COVID-19 mortality rates were higher in areas of socioeconomic disadvantage than in affluent areas. The subsequent discussion reflects on how the unequal nature of the pandemic has resulted from a syndemic of COVID-19 and endemic inequalities in chronic disease burden.

Interaction between Health and Financial Status on Coping Behaviors during the COVID-19 Pandemic

BACKGROUND

The year 2022 started with protests against COVID-19 restrictions throughout North America. These events manifest the fact that some segments of the population are not compliant with the preventive measures of COVID-19, and the reasons of the disobedience against public health regulation remain unclear. The current paper examined the joint effect of financial and health status on people's likelihood of pursuing active coping efforts (i.e., following preventive measures) and giving up coping with the COVID-19 pandemic.

METHOD

We conducted a large-scale survey study in China (N = 3834) in May 2020.

RESULTS

Our results showed that people with low financial status were less likely to manifest active coping behavior and more likely to give up coping with the pandemic. People's self-confidence in coping with the pandemic mediated this effect. We showed that one's health status could interact with their financial status in a way that healthy people with low financial status would have less confidence in their coping abilities and thus become less likely to pursue active coping efforts and more likely to give up coping with the pandemic.

CONCLUSIONS

Our results call for policymakers to find more effective solutions for noncompliant groups so that they can abide by the general guidelines in the COVID-19 context and other social crises that may emerge in the future. We suggest that governments should concentrate their support efforts on healthy populations of low financial segments to prevent COVID-19 and other infectious diseases in the future from spreading further.

Impact of the COVID-19 Pandemic on Walkability in the Main Urban Area of Xi’an

The COVID-19 pandemic has greatly affected the mobility of individuals everywhere. This has been especially true in China, where many restrictions, including lockdowns, have been widely applied. This paper discusses the impact of the pandemic on walkability, an important factor in promoting urban neighborhoods, in the main urban area of Xi’an, China, one of China’s four great ancient capitals. Based on the street view data obtained before and after the pandemic, the paper quantitatively compares changes in specific components of selected streetscapes through a deep learning (DL) street view analysis. The aim is to identify the impact of the pandemic on walkability and determine the elements that influence increased walkability in Xi’an’s historical area, using a walkability evaluation model based on a regression analysis involving three factors (streetscape components, walkability check scores, and street connectivity of space syntax for every image). Although Xi’an’s urban structure did not change significantly, the pandemic has clearly impacted street vitality, especially in terms of reducing pedestrian flow and commercial value. Based on study results, the street environment has great room for improvement, especially in the city’s historical blocks, by reconsidering safety measures to pedestrians and the important role of atmospheric aspects on the streets.

Conceptualizing Walking and Walkability in the Smart City through a Model Composite w2 Smart City Utility Index

This paper explores walking and walkability in the smart city and makes a case for their centrality in the debate on the resilience and sustainability of smart cities, as outlined in the United Nations’ (UN) Sustainable Development Goals (SDGs). It is argued that, while the human/inhabitant-centric paradigm of urban development consolidates, and research on walking, walkability, and pedestrian satisfaction flourishes, the inroads of ICT render it necessary to reflect on these issues in the conceptually- and geographically-delimited space of the smart city. More importantly, it becomes imperative to make respective findings useful and usable for policymakers. To this end, by approaching walking and walkability through the lens of utility, the objective of this paper is to develop a conceptual framework in which the relevance of walking and walkability, hereafter referred to as w2, as a distinct subject of research in the smart cities debate is validated. This framework is then employed to construct a model of a composite w2 smart city utility index. With the focus on the development of the conceptual framework, in which the w2 utility index is embedded, this paper constitutes the first conceptual step of the composite index development process. The value added of this paper is three-fold: First, the relevance of walking and walkability as a distinct subject of research in the realm of smart cities research is established. Second, a mismatch between end-users’ satisfaction derived from walking and their perception of walkability and the objective factors influencing walking and walkability is identified and conceptualized by referencing the concept of utility. Third, a model smart city w2 utility index is proposed as a diagnostic and prognostic tool that, in the subsequent stages of research and implementation, will prove useful for decisionmakers and other stakeholders involved in the process of managing smart cities.

Understanding the Impact of Walkability, Population Density, and Population Size on COVID-19 Spread: A Pilot Study of the Early Contagion in the United States

The novel coronavirus disease 2019 (COVID-19) pandemic is an unprecedented global event that has been challenging governments, health systems, and communities worldwide. Available data from the first months indicated varying patterns of the spread of COVID-19 within American cities, when the spread was faster in high-density and walkable cities such as New York than in low-density and car-oriented cities such as Los Angeles. Subsequent containment efforts, underlying population characteristics, variants, and other factors likely affected the spread significantly. However, this work investigates the hypothesis that urban configuration and associated spatial use patterns directly impact how the disease spreads and infects a population. It follows work that has shown how the spatial configuration of urban spaces impacts the social behavior of people moving through those spaces. It addresses the first 60 days of contagion (before containment measures were widely adopted and had time to affect spread) in 93 urban counties in the United States, considering population size, population density, walkability, here evaluated through walkscore, an indicator that measures the density of amenities, and, therefore, opportunities for population mixing, and the number of confirmed cases and deaths. Our findings indicate correlations between walkability, population density, and COVID-19 spreading patterns but no clear correlation between population size and the number of cases or deaths per 100 k habitants. Although virus spread beyond these initial cases may provide additional data for analysis, this study is an initial step in understanding the relationship between COVID-19 and urban configuration.

Pandemics Initially Spread Among People of Higher (Not Lower) Social Status: Evidence From COVID-19 and the Spanish Flu

According to a staple in the social sciences, pandemics particularly spread among people of lower social status. Challenging this staple, we hypothesize that it holds true in later phases of pandemics only. In the initial phases, by contrast, people of higher social status should be at the center of the spread. We tested our phase-sensitive hypothesis in two studies. In Study 1, we analyzed region-level COVID-19 infection data from 3,132 U.S. regions, 299 English regions, and 400 German regions. In Study 2, we analyzed historical data from 1,159,920 U.S. residents who witnessed the 1918/1919 Spanish Flu pandemic. For both pandemics, we found that the virus initially spread more rapidly among people of higher social status. In later phases, that effect reversed; people of lower social status were most exposed. Our results provide novel insights into the center of the spread during the critical initial phases of pandemics.

Impact of COVID-19 Pandemic on Home Range in a Suburban City in the Osaka Metropolitan Area

This study aims to clarify the impact of the COVID-19 pandemic on home range. The home range is the area that individuals traverse in conducting their daily activities, such as working and shopping. In Japan, the central government declared the first state of emergency in April 2020. This study analyzed the panel data for mobile phone GPS location history from April 2019 to April 2020 in Ibaraki City, Osaka Metropolitan area. The study applied the minimum convex polygon method to analyze the data. The results show that the home range decreased significantly between April 2019 and April 2020. Specifically, the home range in 2020 decreased to approximately 50% of that in 2019 because of COVID-19 infection control measures, preventing people from traveling far from their homes and only allowing them to step outside for the bare minimum of daily activities and necessities. The results suggest that the emergency reduced people’s home ranges to the neighborhood scale. Therefore, it is necessary to consider designing new walkable neighborhood environments after the COVID-19 pandemic era.

Changes in Walkable Streets during the COVID-19 Pandemic in a Suburban City in the Osaka Metropolitan Area

The purpose of this study was to identify the walkable streets where traffic behavior changed according to each residential cluster during the COVID-19 pandemic. By elucidating the changes, it is possible to identify streets that should be redesigned following the changes in traffic behavior in relation to human mobility. This study analyzed Ibaraki City, a suburban city located in the Osaka Metropolitan Area. The analysis compared the panel data of the GPS Location History for April 2020 and April 2019. The analysis method used was Empirical Bayesian kriging. The results show that the speed significantly increased in the dense, sprawl, mountain, and old NT clusters. It was also found that the number of cyclists increased during the COVID-19 pandemic. The results suggest a need to design walkable streets according to each residential cluster for the post-COVID-19 pandemic era. For example, some car lanes need to be converted to bike lanes in the main neighborhood to create walkable streets in the clusters.