Spatial Clustering of Pedestrian Activity and the Built Environment Characteristics

Promoting pedestrian activity has attracted increasing attention as an important strategy for the improvement of public health and urban revitalization. The impact on physical activity underpinned by built environment has been studied substantially; however, few studies had focused on the geographically varying relationships between pedestrian activity and the built environment characteristics. Built upon previous work, this study looks at the spatial patterns of pedestrian counts and the built environment contributors along two major streets in Buffalo, New York using global and local spatial autocorrelation tests and geographically weighted regression. Pedestrian generators, job density and land use mix are included as independent variables in order to study the impact on them due to the characteristics of built environment. Our findings suggest that (1) there are statistically significant clusters of street intersections with high pedestrian counts along the streets selected in our study; (2) there are some optimal sizes of clusters of pedestrian generators, which attract more pedestrians; (3) geographically weighted Poisson model helps to analyze the geographically varying relationships between the built environment and pedestrian activity with a more pronounced goodness of fit. This research contributes to the understanding of the spatial patterns of pedestrian activity and the geographically varying relationship between the built environment and pedestrian counts. Hopefully this research will help to guide and focus the minds of policy makers and urban planners alike to introduce street vitality through the modifications of the built environment, so as to improve the quality of life in their neighborhoods.

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Spatiotemporal Analysis of Serogroup C Meningococcal Meningitis Spread in Niger and Nigeria and Implications for Epidemic Response

The Journal of Infectious Diseases ◽

10.1093/infdis/jiz343 ◽

2019 ◽

Vol 220 (Supplement_4) ◽

pp. S244-S252 ◽

Cited By ~ 4

Author(s):

Laura V Cooper ◽

Olivier Ronveaux ◽

Katya Fernandez ◽

Clement Lingani ◽

Kadade Goumbi ◽

...

Keyword(s):

Spatial Clustering ◽

Spatiotemporal Analysis ◽

Meningococcal Meningitis ◽

High Coverage ◽

Alternative Strategies ◽

High Incidence ◽

Epidemic Response ◽

Vaccination Campaigns ◽

Global And Local ◽

The Impact

Abstract Background After the re-emergence of serogroup C meningococcal meningitis (MM) in Nigeria and Niger, we aimed to re-evaluate the vaccination policy used to respond to outbreaks of MM in the African meningitis belt by investigating alternative strategies using a lower incidence threshold and information about neighboring districts. Methods We used data on suspected and laboratory-confirmed cases in Niger and Nigeria from 2013 to 2017. We calculated global and local Moran’s I-statistics to identify spatial clustering of districts with high MM incidence. We used a Pinner model to estimate the impact of vaccination campaigns occurring between 2015 and 2017 and to evaluate the impact of 3 alternative district-level vaccination strategies, compared with that currently used. Results We found significant clustering of high incidence districts in every year, with local clusters around Tambuwal, Nigeria in 2013 and 2014, Niamey, Niger in 2016, and in Sokoto and Zamfara States in Nigeria in 2017. We estimate that the vaccination campaigns implemented in 2015, 2016, and 2017 prevented 6% of MM cases. Using the current strategy but with high coverage (85%) and timely distribution (4 weeks), these campaigns could have prevented 10% of cases. This strategy required the fewest doses of vaccine to prevent a case. None of the alternative strategies we evaluated were more efficient, but they would have prevented the occurrence of more cases overall. Conclusions Although we observed significant spatial clustering in MM in Nigeria and Niger between 2013 and 2017, there is no strong evidence to support a change in methods for epidemic response in terms of lowering the intervention threshold or targeting neighboring districts for reactive vaccination.

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Impacts of Physical Environment Perception on the Frailty Condition in Older People

Geospatial health ◽

10.4081/gh.2020.888 ◽

2020 ◽

Vol 15 (1) ◽

Author(s):

Carlos Mena ◽

Yony Ormazabal ◽

Eduardo Fuentes ◽

Iván Palomo

Keyword(s):

Older People ◽

Physical Environment ◽

Spatial Clustering ◽

Physical Environments ◽

Geographic Clustering ◽

Environment Perception ◽

Global And Local ◽

The Impact ◽

The City

Frailty increases the vulnerability of older people who commonly develop a syndrome leading to growing dependence and finally often death. Physical environment conditions may affect the severity of the syndrome positive or negatively. The main objective of this study was to analyse the conditions of different urban physical environments and their relationship with the frailty syndrome in older people. Geographic Information Systems (GIS) analyses were performed to detect global and local geographic clustering. Investigating 284 adults with ages from 60 to 74 years old from Talca City, Chile, we found spatial clustering of frailty conditions registered for older people, with hotspots of high and low values associated with areas of different urban infrastructures and socioeconomic levels into the city. The spatial identifications found should facilitate exploring the impact of mental health programmes in communities exposed to disasters like earthquakes, thereby improving their quality of life as well as reducing overall costs. Spatial correlation has a great potential for studying frailty conditions in older people with regard to better understanding the impact of environmental conditions on health.

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Assessing the impact of the built environment on travel behavior: a case study of Buffalo, New York

Transportation ◽

10.1007/s11116-011-9337-x ◽

2011 ◽

Vol 38 (4) ◽

pp. 663-678 ◽

Cited By ~ 13

Author(s):

Andrew J. Tracy ◽

Peng Su ◽

Adel W. Sadek ◽

Qian Wang

Keyword(s):

New York ◽

Built Environment ◽

Travel Behavior ◽

The Impact

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Adjusting College Costs for Noncredit Enrollments: An Issue for Data Geeks or Policy Makers?

Community College Review ◽

10.1177/0091552119835030 ◽

2019 ◽

Vol 47 (2) ◽

pp. 159-177

Author(s):

Richard M. Romano ◽

Rita J. Kirshstein ◽

Mark D’Amico ◽

Willard Hom ◽

Michelle Van Noy

Keyword(s):

New York ◽

Community Colleges ◽

Postsecondary Education ◽

Full Time ◽

Full Time Equivalent ◽

Policy Makers ◽

College Costs ◽

Education Data ◽

Project Data ◽

The Impact

Objective: In the first study of its kind, the impact of excluding noncredit enrollments in calculations of spending in community colleges is explored. Noncredit enrollments are not reported to Integrated Postsecondary Education Data System (IPEDS), but expenditures for these efforts are. This study corrects for this omission and provides new estimates of spending on community college students in four states. Method: Data on noncredit enrollments were made available from four states—New York, New Jersey, California, and North Carolina. Interviews with campus and state officials within each state helped us verify the findings. In addition, Delta Cost Project data were analyzed and adjusted to account for noncredit enrollments. Results: Our analysis indicates that the expenditure per full-time equivalent (FTE) student measure, which researchers typically use, seriously overstates the resources that community colleges have to spend on educating students; however, great variations exist within and across states. Conclusion: Community colleges are underfunded to an even greater extent than standard IPEDS analyses indicate.

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Towards Pedestrian Microclimatic Comfort: A Rapid Predication Model for Street Winds and Pedestrian Thermal Sensation

Nano LIFE ◽

10.1142/s1793984418400068 ◽

2018 ◽

Vol 08 (02) ◽

pp. 1840006

Author(s):

Jing Li ◽

Mengnan Qi ◽

Qiuhua Duan ◽

Lei Huo ◽

Julian Wang

Keyword(s):

Wind Speed ◽

Built Environment ◽

Thermal Comfort ◽

Air Temperature ◽

Goodness Of Fit ◽

Comfort Level ◽

Outdoor Thermal Comfort ◽

Design Parameters ◽

Rapid Urbanization ◽

The Impact

Significant changes in the urban built environment have occurred due to rapid urbanization and increases in the urban population. Such alterations may produce environmental health-related issues such as urban heat stress, air pollution and traffic noise. This research undertook a field study to collect data including urban design parameters, micro-environmental factors and city climatic information. This work was conducted over a two-year period on three pedestrian streets located in high-density urban areas in Beijing. These areas were selected in order to study the influences of urban street canyon texture within a particular geometric layout, wind flow corridors and variations in air temperature on pedestrian microclimatic comfort. The results will facilitate the work of urban planners by providing them with information for use in improving outdoor thermal comfort through their designs. A total of 60[Formula: see text]485 samples were organized into training, validation and test sets. We confirmed our hypothesis that internal wind speed ([Formula: see text] is attributable mainly to the urban texture coefficient ([Formula: see text], air temperature ([Formula: see text] and leading-in wind speed ([Formula: see text]. The model was tested using the test data collected onsite, which demonstrated a very accurate goodness-of-fit; the model achieved an R-squared value of 0.82, which meant that [Formula: see text] as a dependent variable was 82% correlated to the three predictors as independent variables. With this computer simulation, urban planners can now predict and visualize the impact of changes on the built environment in terms of either the direction of solar radiation received or increases in wind speed, in return for the desired thermal comfort level for residents of the neighborhood.

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Medical Capacity Shortages Facilitated the Rapid Dissemination of COVID-19 in Wuhan, New York State, and Italy

10.21203/rs.3.rs-234709/v1 ◽

2021 ◽

Author(s):

Yuehao Xu ◽

Cheng Zhang ◽

Lixian Qian

Keyword(s):

New York ◽

New York State ◽

The United States ◽

Policy Makers ◽

York State ◽

Proposed Model ◽

Rapid Dissemination ◽

City State ◽

And Control ◽

The Impact

Abstract Background: During the coronavirus disease 2019 (COVID-19) outbreak, every public health system faced the potential challenge of medical capacity shortages. Infections without timely diagnosis or treatment may facilitate the stealth transmission and spread of the virus. Important as the influence of capacity shortages on the epidemic, it is still unclear how they could intensify the spread of the epidemic qualitatively under different circumstances. Our study aims to throw light on this influence.Methods: Using infection and medical capacity information reported in Wuhan in China, New York State in the United States, and Italy, we developed a dynamic susceptible–exposed–infected–recovered (SEIR) model to estimate the impact of medical capacity shortages during the COVID-19 outbreak at the city, state, and country levels.Results: The proposed model can fit data well (R-square > 0.9). Through sensitivity analysis, we found that doubled capacity would lead to a 39% lower peak infected number in Wuhan. Italy and New York State have similar results.Conclusions: The less shortages in medical capacity, the faster decline in the daily infection numbers and the fewer deaths, and more shortage would lead to steepen infection curve. This study provides a method for estimating potential shortages and explains how they may dynamically facilitate disease spreading during future pandemics such as COVID-19. Based on this, policy makers may figure out some way to explore more medical capacity and control the epidemic better.

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Geocoding Error, Spatial Uncertainty, and Implications for Exposure Assessment and Environmental Epidemiology

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17165845 ◽

2020 ◽

Vol 17 (16) ◽

pp. 5845

Author(s):

Ellen J. Kinnee ◽

Sheila Tripathy ◽

Leah Schinasi ◽

Jessie L. C. Shmool ◽

Perry E. Sheffield ◽

...

Keyword(s):

New York ◽

Spatial Patterns ◽

Spatial Clustering ◽

Health Effect ◽

Environmental Epidemiology ◽

Emergency Department Visits ◽

Spatial Uncertainty ◽

Street Segment ◽

Exposure Misclassification ◽

Minimal Impact

Although environmental epidemiology studies often rely on geocoding procedures in the process of assigning spatial exposure estimates, geocoding methods are not commonly reported, nor are consequent errors in exposure assignment explored. Geocoding methods differ in accuracy, however, and, given the increasing refinement of available exposure models for air pollution and other exposures, geocoding error may account for an increasingly larger proportion of exposure misclassification. We used residential addresses from a reasonably large, dense dataset of asthma emergency department visits from all New York City hospitals (n = 21,183; 26.9 addresses/km2), and geocoded each using three methods (Address Point, Street Segment, Parcel Centroid). We compared missingness and spatial patterning therein, quantified distance and directional errors, and quantified impacts on pollution exposure estimates and assignment to Census areas for sociodemographic characterization. Parcel Centroids had the highest overall missingness rate (38.1%, Address Point = 9.6%, Street Segment = 6.1%), and spatial clustering in missingness was significant for all methods, though its spatial patterns differed. Street Segment geocodes had the largest mean distance error (µ = 29.2 (SD = 26.2) m; vs. µ = 15.9 (SD = 17.7) m for Parcel Centroids), and the strongest spatial patterns therein. We found substantial over- and under-estimation of pollution exposures, with greater error for higher pollutant concentrations, but minimal impact on Census area assignment. Finally, we developed surfaces of spatial patterns in errors in order to identify locations in the study area where exposures may be over-/under-estimated. Our observations provide insights towards refining geocoding methods for epidemiology, and suggest methods for quantifying and interpreting geocoding error with respect to exposure misclassification, towards understanding potential impacts on health effect estimates.

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An inhomogeneous Poisson model of the spatial intensity of opioid overdoses, as represented by EMS naloxone use

10.1101/529206 ◽

2019 ◽

Author(s):

Christopher W. Ryan

Keyword(s):

New York ◽

Spatial Clustering ◽

New York State ◽

Poisson Model ◽

The United States ◽

Opioid Overdose ◽

Neighborhood Conditions ◽

Spatial Intensity ◽

South Central ◽

Central New York

1AbstractFrom 1999 to 2017, the age-adjusted annual death rate in the United States from opioid overdose has increased several-fold, to about 18.3 per 100,000 population. The federal government has declared opioid overdose a public health emergency. Spatially-aware analyses and surveillance may contribute to control of this growing problem.As naloxone has only one clinical use—the treatment of opioid overdose—its administration by emergency medical services (EMS) personnel can serve as a surveillance indicator for opioid overdose. I previously demonstrated spatial clustering of naloxone-involved EMS calls, over and above that to be expected fromEMS calls in general. To better understand the nature of that clustering, I modelled the spatial distribution of naloxone-involved EMS calls in a three-county region in south-central New York State as an inhomogeneous Poisson process, using as predictors several census-tract-level sociodemographic variables and the point locations of convenience stores (minimarts). In Monte Carlo simulations, I examined how well the model explained the observed clustering.Although it assumes no interaction between event locations, the inhomogeneous Poisson model was nevertheless able to explain much of the observed spatial clustering. The spatial intensity of EMS calls for opioid overdose, in events per square kilometer, was signficantly higher in census tracts with lower rates of owner-occupancy of housing. Neither the proportion of households in poverty nor the proportion of residents in the 20–44 age band were signficant predictors. Spatial intensity of overdose events decreased by about 10% for each kilometer of distance from the nearest minimart, but this was of borderline signfificance at conventional levels. These findings cast some doubt on the utility of real-time surveillance for apparent spatial clusters of opioid overdose and instead favor a longer-term, systemic strategy comprising efforts to improve neighborhood conditions.

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Impacts of Study Area Spatial Form on Co-location Quotient Analysis: Evidence From Medical Resources Distribution in Wuhan City

10.21203/rs.3.rs-1020355/v1 ◽

2021 ◽

Author(s):

Qiao Chen ◽

Jianquan Cheng ◽

Jianguang Tu

Keyword(s):

Spatial Patterns ◽

Large Scale ◽

Spatial Form ◽

Location Quotient ◽

Wuhan City ◽

Medical Resources ◽

Spatial Associations ◽

Global And Local ◽

The Impact ◽

Natural Barriers

Abstract BackgroundThere is a sharp contradiction between supply and demand of medical resources in provincial capitals of China. Understanding the spatial patterns of medical resources and identifying their spatial association and heterogeneity is a prerequisite to ensuring limited resources are allocated fairly and optimally, which, along with improvements to urban residents’ quality of life, is a key aim of healthy city planning. MethodLocalised co-location quotient (LCLQ) analysis has been used successfully to measure directional spatial associations and heterogeneity between categorical point data. Using point of interest data and the LCLQ method, this paper presents the first analysis of spatial patterns and directional spatial associations between six medical resources across Wuhan city, and evaluates the impact of study area spatial form (considered as a new dimension of spatial scale) on spatial analysis. The unique morphology of Wuhan city, which is bisected by the Yangtze River, is used to assess the impacts on LCLQ analysis and the seeking behaviour of medical resources.ResultsThis paper demonstrated the impacts of the spatial form of a study area on the global and local values of LCLQ of local-level medical resources. When splitting the city into multiple data sets (e.g. regions A and B in this paper), the global and local LCLQ values for pharmacies, clinics and community hospitals changed signficantly in both regions after the spatial partition. The border areas between regions A and B were influenced most.ConclusionThis paper focused on the impacts of the unique spatial form of the study area created by large-scale natural barriers. we should not ignore the impacts of the unique spatial form of the study area created by large-scale natural barriers such as mountains, rivers or lakes. The findings highlight another form of multiscale analysis in urban GIS.

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The impact of neighbourhood environments on quality of life of elderly people: Evidence from Nanjing, China

Urban Studies ◽

10.1177/0042098017702827 ◽

2017 ◽

Vol 55 (9) ◽

pp. 2020-2039 ◽

Cited By ~ 15

Author(s):

Jianxi Feng ◽

Shuangshuang Tang ◽

Xiaowei Chuai

Keyword(s):

Quality Of Life ◽

Life Satisfaction ◽

Built Environment ◽

Elderly People ◽

The Elderly ◽

Structural Equations ◽

Policy Implications ◽

Policy Makers ◽

The Impact

The connections between the built environment and quality of life are major concerns in the fields of geography and urban planning. Given that some developing countries, such as China, have a rapidly aging society, elderly people have become a social group that attracts growing interest among scholars and policy makers. However, the relationship between neighbourhood environments and the quality of life of the elderly has scarcely been referenced in previous literature. Based on a recent survey in Nanjing, China, this article investigates such connections through structural equations models. It notes that population density exerts an insignificant influence on the life satisfaction of the elderly, whereas built year has the largest impact, indicating the importance of interior environment to subjective wellbeing for the elderly in China. The other built environment factors (informal space and danwei) that have Chinese features are negatively related to the quality of life of older people. Among life domains, the effects of health conditions, residential environments and transportation are stronger than those of social interaction, meaning that the elderly in China place greater emphasis on their basic needs than on higher life needs. This article has some policy implications for policy makers, including on urban form, informal spaces and style of residential communities. Relevant policies need to be carried out to promote the life satisfaction of elderly people in urban China.

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