Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.
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Abstract
Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.
Keywords
Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us
Bassok, Alon; Hurvitz, Phil M.; Bae, C-H. Christine; Larson, Timothy. (2010). Measuring Neighbourhood Air Pollution: The Case of Seattle’s International District. Journal Of Environmental Planning & Management, 53(1), 23 – 39.
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Abstract
Current US regulatory air quality monitoring networks measure ambient levels of pollutants and cannot capture the effects of mobile sources at the micro-scale. Despite the fact that overall air quality has been getting better, more vulnerable populations (children, the elderly, minorities and the poor) continue to suffer from traffic-related air pollution. As development intensifies in urban areas, more people are exposed to road-related air pollution. However, the only consideration given to air quality, if any, is based on ambient measures. This paper uses an inexpensive, portable Particle Soot Absorption Photometer (PSAP) to measure Black Carbon (BC) emissions, a surrogate for diesel fuels emissions, in Seattle's International District. With the aid of a GPS receiver, street-level BC data were geocoded in real space-time. It was found that pollution levels differed substantially across the study area. The results show the need for street-level air pollution monitoring, revisions in current land use and transportation policies, and air quality planning practice.
Keywords
Emission Standards; Air Pollution; Atmospheric Deposition; Social Groups; Waste Products; Sanitary Landfills; Black Carbon; Freeway Air Pollution Sheds (faps); Land Use; Mobile Monitoring; Neighbourhood Air Quality; Aerosol Light-absorption; Respiratory Health; Coefficient; Exposure; Symptoms; Children; Pollutants; Particles; Exhaust; Asthma
Stover, Victor W.; Bae, C.-H. Christine. (2011). Impact of Gasoline Prices on Transit Ridership in Washington State. Transportation Research Record, 2217, 1 – 10.
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Abstract
Gasoline prices in the United States have been extremely volatile in recent years and rose to record high levels during the summer of 2008. According to the U.S. Energy Information Administration, the average U.S. gasoline price for the year 2008 was $3.26 a gallon, which was the second highest yearly average in history when adjusted for inflation. Transportation agencies reported changes in travel behavior as a result of the price spike, with transit systems experiencing record ridership and state departments of transportation reporting reductions in traffic volumes. This study examined the impact of changing gasoline prices on transit ridership in Washington State by measuring the price elasticity of demand of ridership with respect to gasoline price. Ordinary least-squares regression was used to model transit ridership for transit agencies in 11 counties in Washington State during 2004 to 2008. The price of gasoline had a statistically significant effect on transit ridership for seven systems studied, with elasticities ranging from 0.09 to 0.47. A panel data model was estimated with data from all 11 agencies to measure the overall impact of gasoline prices on transit ridership in the state. The elasticity from the panel data model was 0.17. Results indicated that transit ridership increased as gasoline prices increased during the study period. The findings were consistent with those from previous studies on the topic.
Keywords
Time-series Analysis; Gas Prices; Elasticities; Demand
Hong, Jinhyun; Shen, Qing. (2013). Residential Density and Transportation Emissions: Examining the Connection by Addressing Spatial Autocorrelation and Self-Selection. Transportation Research Part D-transport And Environment, 22, 75 – 79.
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Abstract
This paper examines the effect of residential density on CO2 equivalent from automobile using more specific emission factors based on vehicle and trip characteristics, and by addressing problems of spatial autocorrelation and self-selection. Drawing on the 2006 Puget Sound Regional Council Household Activity Survey data, the 2005 parcel and building database, the 2000 US Census data, and emission factors estimated using the Motor Vehicle Emission Simulator, we analyze the influence of residential density on road-based transportation emissions. In addition, a Bayesian multilevel model with spatial random effects and instrumental variables is employed to control for spatial autocorrelation and self-selection. The results indicate that the effect of residential density on transportation emissions is influenced by spatial correlation and self-selection. Our results still show, however, that increasing residential density leads to a significant reduction in transportation emissions. (C) 2013 Elsevier Ltd. All rights reserved.
Keywords
Urban Form; Travel; Transportation Emissions; Residential Density; Confounding By Location; Self-selection
Hong, Jinhyun; Shen, Qing; Zhang, Lei. (2014). How Do Built-Environment Factors Affect Travel Behavior? A Spatial Analysis at Different Geographic Scales. Transportation, 41(3), 419 – 440.
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Abstract
Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor-if any-influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.
Keywords
Land-use; Urban Form; Multilevel Models; Physical-activity; Neighborhood; Choice; Impact; Specification; Accessibility; Causation; Built Environment; Travel Behavior; Self-selection; Spatial Autocorrelation; Bayesian Hierarchical Model
Estiri, Hossein; Krause, Andy; Heris, Mehdi P. (2015). Phasic Metropolitan Settlers: A Phase-Based Model for the Distribution of Households in US Metropolitan Regions. Urban Geography, 36(5), 777 – 794.
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Abstract
In this article, we develop a model for explaining spatial patterns in the distribution of households across metropolitan regions in the United States. First, we use housing consumption and residential mobility theories to construct a hypothetical probability distribution function for the consumption of housing services across three phases of household life span. We then hypothesize a second probability distribution function for the offering of housing services based on the distance from city center(s) at the metropolitan scale. Intersecting the two hypothetical probability functions, we develop a phase-based model for the distribution of households in US metropolitan regions. We argue that phase one households (young adults) are more likely to reside in central city locations, whereas phase two and three households are more likely to select suburban locations, due to their respective housing consumption behaviors. We provide empirical validation of our theoretical model with the data from the 2010 US Census for 35 large metropolitan regions.
Keywords
Residential-mobility; Life-course; Housing Consumption; Family; Satisfaction; Migration; Geography; Context; Age; Distribution Patterns; Us Metropolitan Regions; Household
Drewnowski, Adam; Aggarwal, Anju; Cook, Andrea; Stewart, Orion; Moudon, Anne Vernez. (2016). Geographic Disparities in Healthy Eating Index Scores (HEI-2005 and 2010) by Residential Property Values: Findings from Seattle Obesity Study (SOS). Preventive Medicine, 83, 46 – 55.
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Abstract
Background. Higher socioeconomic status (SES) has been linked with higher-quality diets. New GIS methods allow for geographic mapping of diet quality at a very granular level. Objective. To examine the geographic distribution of two measures of diet quality: Healthy Eating Index (HEI 2005 and HEI 2010) in relation to residential property values in Seattle-King County. Methods. The Seattle Obesity Study (SOS) collected data from a population-based sample of King County adults in 2008-09. Socio-demographic data were obtained by 20-min telephone survey. Dietary data were obtained from food frequency questionnaires (FFQs). Home addresses were geocoded to the tax parcel and residential property values were obtained from the King County tax assessor. Multivariable regression analyses using 1116 adults tested associations between SES variables and diet quality measured (HEI scores). Results. Residential property values, education, and incomes were associated with higher HEI scores in bivariate analyses. Property values were not collinear with either education or income. In adjusted multivariable models, education and residential property were better associated with HEI, compared to than income. Mapping of HEI-2005 and HEI-2010 at the census block level illustrated the geographic distribution of diet quality across Seattle-King County. Conclusion. The use of residential property values, an objective measure of SES, allowed for the first visual exploration of diet quality at high spatial resolution: the census block level. (C) 2015 Elsevier Inc. All rights reserved.
Keywords
Obesity Treatment; Prevention Of Obesity; Disease Mapping; Socioeconomics; Multivariate Analysis; Population Geography; Census; Diet; Housing; Nutrition Policy; Questionnaires; Research Funding; Socioeconomic Factors; Body Mass Index; Health Equity; Cross-sectional Method; Economics; Seattle (wash.); Washington (state); Diet Quality; Geographic Information Systems; Healthy Eating Index; Residential Property Values; Socio-economic Status; Local Food Environment; Vitamin-e Consumption; Socioeconomic Position; United-states; Social-class; Energy-density; Association; Indicators; Trends
Ren Hong; Wang Peng; Cai Weiguang; Li Dandan; Du Yongjie; Sun Junqiao; Abramson, Daniel. (2016). Visitor Center Design Research Based on Resilience Theory. Open House International, 41(3), 5 – 11.
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Abstract
Visitor center plays an important role in the normal operation and sustainable development of scenic spots, especially as a portal image of its management. This paper presents resilience theory for visitor centers to identify some common issues in designing visitor centers in China scenic spots, including the lack of function, loss of architectural characteristics, and difficultly in adapting to changes in the number of visitors with periodic variations. The framework of resilience theory was set from four dimensions, namely, resilience and match in the composition of ontology function, the extended function, integration of buildings into the surrounding environment, and alternative construction technologies and materials. This theory was explained and analyzed with the application of the theory in practice in combination with the design of Mount Hua visitor center. Results showed that resilience theory yields good application effect.
Keywords
Resilience Theory; Visitor Center; Design Research; Function Space
Gase, Lauren N.; Defosset, Amelia R.; Gakh, Maxim; Harris, Celia; Weisman, Susan R.; Dannenberg, Andrew L. (2017). Review of Education-Focused Health Impact Assessments Conducted in the United States. Journal Of School Health, 87(12), 911 – 922.
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Abstract
BACKGROUNDHealth impact assessment (HIA) provides a structured process for examining the potential health impacts of proposed policies, plans, programs, and projects. This study systematically reviewed HIAs conducted in the United States on prekindergarten, primary, and secondary education-focused decisions. METHODSRelevant HIA reports were identified from web sources in late 2015. Key data elements were abstracted from each report. Four case studies were selected to highlight diversity of topics, methods, and impacts of the assessment process. RESULTSTwenty HIAs completed in 2003-2015 from 8 states on issues related to prekindergarten through secondary education were identified. The types of decisions examined included school structure and funding, transportation to and from school, physical modifications to school facilities, in-school physical activity and nutrition, and school discipline and climate. Assessments employed a range of methods to characterize the nature, magnitude, and severity of potential health impacts. Assessments fostered stakeholder engagement and provided health-promoting recommendations, some of which were subsequently incorporated into school policies. CONCLUSIONSHealth impact assessment is a promising tool that education, health, and other stakeholders can use to maximize the health and well-being of students, families, and communities.
Keywords
Decision Making; Elementary Schools; High Schools; Medical Policy; Medline; Nutrition; Online Information Services; Research Funding; Student Health; Systematic Reviews (medical Research); Search Engines; Physical Activity; Health Impact Assessment; United States; Collaboration; Policy; Public Health; Academic-achievement; Programs
Chen, Peng; Sun, Feiyang; Wang, Zhenbo; Gao, Xu; Jiao, Junfeng; Tao, Zhimin. (2018). Built Environment Effects on Bike Crash Frequency and Risk in Beijing. Journal Of Safety Research, 64, 135 – 143.
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Abstract
Introduction: Building a safe biking environment is crucial to encouraging bicycle use. In developed areas with higher density and more mixed land use, the built environment factors that pose a crash risk may vary. This study investigates the connection between biking risk factors and the compact built environment, using data for Beijing. Method: In the context of China, this paper seeks to answer two research questions. First, what types of built environment factors are correlated with bike-automobile crash frequency and risk? Second, how do risk factors vary across different types of bikes? Poisson lognormal random effects models are employed to examine how land use and roadway design factors are associated with the bike-automobile crashes. Results: The main findings are: (1) bike-automobile crashes are more likely to occur in densely developed areas, which is characterized by higher population density, more mixed land use, denser roads and junctions, and more parking lots; (2) areas with greater ground transit are correlated with more bike-automobile crashes and higher risks of involving in collisions; (3) the percentages of wider streets show negative associations with bike crash frequency; (4) built environment factors cannot help explain factors contributing to motorcycle-automobile crashes. Practical Applications: In China's dense urban context, important policy implications for bicycle safety improvement drawn from this study include: prioritizing safety programs in urban centers, applying safety improvements to areas with more ground transit, placing bike-automobile crash countermeasures at road junctions, and improving bicycle safety on narrower streets. (C) 2018 National Safety Council and Elsevier Ltd. All rights
Keywords
Motorcycling Accidents; Built Environment; Motorcycling; Poisson Distribution; Safety; Beijing (china); Bike-automobile Crash; Frequency; Poisson Lognormal Random Effects Model; Risk; Signalized Intersections; Transportation Modes; Urban Intersections; Bicycle Crashes; Motor-vehicle; Riders; Infrastructure; China; Severity; Frequency Distribution; Risk Factors; Bicycles; Fatalities; Collisions; Traffic Accidents; Safety Programs; Urban Environments; Traffic Safety; Population Density; Crashes; Streets; Environmental Effects; Environmental Engineering; Roads; Land Use; Risk Analysis; Urban Areas; Road Design; Construction; Ecological Risk Assessment; Design Factors; Motorcycles; Urban Transportation; Studies; Safety Management; Beijing China