Insights from Integrated Geo-Location Data for Pedestrian Crashes, Demographics, and Land Uses

2020 ◽  
Vol 2674 (8) ◽  
pp. 720-731
Author(s):  
Rui Guo ◽  
Zhiqiang Wu ◽  
Yu Zhang ◽  
Pei-Sung Lin ◽  
Zhenyu Wang
Keyword(s):  
Low Income ◽  
Fast Food ◽  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Pedestrian Safety ◽  
Marginal Effect ◽  
Land Uses ◽  
Crash Frequency ◽  
Location Data ◽  
Pedestrian Crashes

This study investigates the effects of demographics and land uses on pedestrian crash frequency by integrating the contextual geo-location data. To address the issue of heterogeneity, three negative binomial models (with fixed parameters, with observed heterogeneity, and with both observed and unobserved heterogeneities) were examined. The best fit with the data was obtained by explicitly incorporating the observed and unobserved heterogeneity into the model. This highlights the need to accommodate both observed heterogeneity across neighborhood characteristics and unobserved heterogeneity in pedestrian crash frequency modeling. The marginal effect results imply that some land-use types (e.g., discount department stores and fast-food restaurants) could be candidate locations for the education campaigns to improve pedestrian safety. The observed heterogeneity of the area indicator suggests that priority should be given to more populated low-income areas for pedestrian safety, but attention is also needed for the higher-income areas with larger densities of bus stops and hotels. Moreover, three normally distributed random parameters (proportion of older adults, proportion of lower-speed roads, and density of convenience stores in the area) were identified as having random effects on the probability of pedestrian crash occurrences. Finally, the identification of pedestrian crash hot zone provides practitioners with prioritized neighborhoods (e.g., a list of areas) for developing effective pedestrian safety countermeasures.

scholarly journals Investigating Pedestrian Injury Crashes on Modern Roundabouts in Addis Ababa, Ethiopia

2015 ◽  
Vol 2512 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Getu Segni Tulu ◽  
M. Mazharul Haque ◽  
Simon Washington ◽  
Mark J. King
Keyword(s):  
Low Income ◽  
Goodness Of Fit ◽  
Negative Binomial ◽  
Addis Ababa ◽  
Random Effect ◽  
Pedestrian Safety ◽  
Fit Statistics ◽  
Traffic Characteristics ◽  
Multiple Observations ◽  
Pedestrian Crashes

Pedestrian crashes represent about 40% of total fatal crashes in low-income developing countries. Although many pedestrian crashes in these countries occur at unsignalized intersections such as roundabouts, studies focusing on this issue are limited. The objective of this study was to develop safety performance functions for pedestrian crashes at modern roundabouts to identify significant roadway geometric, traffic, and land use characteristics related to pedestrian safety. Detailed data, including various forms of exposure, geometric and traffic characteristics, and spatial factors such as proximity to schools and to drinking establishments were collected from a sample of 22 modern roundabouts in Addis Ababa, Ethiopia, representing about 56% of such roundabouts in Addis Ababa. To account for spatial correlation resulting from multiple observations at a roundabout, both the random effect Poisson (REP) and random effect negative binomial (RENB) regression models were estimated. Model goodness-of-fit statistics revealed a marginally superior fit of the REP model to the data compared with the RENB model. Pedestrian crossing volume and the product of traffic volumes along major and minor roads had significant and positive associations with pedestrian crashes at roundabouts. The presence of a public transport (bus or taxi) terminal beside a roundabout was associated with increased pedestrian crashes. Although the maximum gradient of an approach road was negatively associated with pedestrian safety, the provision of a raised median along an approach appeared to increase pedestrian safety at roundabouts. Remedial measures were identified for combating pedestrian safety problems at roundabouts in the context of a developing country.

scholarly journals Pedestrian Safety in Compact and Mixed-Use Urban Environments: Evaluation of 5D Measures on Pedestrian Crashes

2022 ◽  
Vol 14 (2) ◽  
pp. 646
Author(s):  
Hyungun Sung ◽  
Sugie Lee ◽  
SangHyun Cheon ◽  
Junho Yoon
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Pedestrian Safety ◽  
Urban Environments ◽  
Vehicle Crashes ◽  
Traditional Markets ◽  
Major Injury ◽  
Mixed Use ◽  
Pedestrian Crashes ◽  
The Impact

This study examined the impact of density, diversity, design, distance to transit, and destination accessibility, five measures, known as the 5Ds, that characterize the built environment, on pedestrian–vehicle crashes in Seoul, Korea. Using spatial analysis based on 500-m grid cells, this study employed negative binomial regression models on the frequencies of three specific types of pedestrian–vehicle crashes: crashes causing death, major injury, and minor injury to pedestrians. Analysis shows that compact and mixed-use urban environments represented by 5D measures have mixed effects on pedestrian safety. Trade-off effects are found between a higher risk for all types of pedestrian crashes, and a lower risk for fatal pedestrian crashes in 5D urban environments. As a design variable, a higher number of intersections is more likely to increase some types of pedestrian crashes, including fatal crashes, a finding which warrants policy attention to promote pedestrian safety near intersection areas. This study also confirms an urgent need to secure the travel safety of pedestrians near public transit stations due to the higher risk of pedestrian crashes near such facilities. Various destinations, such as retail stores, traditional markets, and hospitals, are associated with pedestrian crashes. Pedestrian safety measures should be implemented to reduce the likelihood of pedestrian crashes near major destination facilities.

scholarly journals Impact of reimbursement rates on the length of stay in tertiary public hospitals: a retrospective cohort study in Shenzhen, China

BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e040066
Author(s):  
Jie Ning ◽  
Lingrui Liu ◽  
Emily Cherlin ◽  
Yarui Peng ◽  
Jingkai Yue ◽  
...  
Keyword(s):  
Cohort Study ◽  
Length Of Stay ◽  
Low Income ◽  
Retrospective Cohort Study ◽  
Retrospective Cohort ◽  
Negative Binomial ◽  
Public Hospitals ◽  
Administrative Database ◽  
Marginal Effect ◽  
Reimbursement Rate

ObjectiveTo examine the association between reimbursement rates and the length of stay (LOS).DesignA retrospective cohort study.SettingThe study was conducted in Shenzhen, China by using health administrative database from 1 January 2015 to 31 December 2017.Participants6583 patients with acute myocardial infarction (AMI), 12 395 patients with pneumonia and 10 485 patients who received percutaneous coronary intervention (PCI) surgery.MeasuresThe reimbursement rate was defined as one minus the ratio of out-of-pocket to the total expenditure, multiplied by 100%. The outcome of interest was the LOS. Multilevel negative binomial regression models were constructed to control for patient-level and hospital-level characteristics, and the marginal effect was reported when non-linear terms were available.ResultsEach additional unit of the reimbursement rate was associated with an average of an additional increase of 0.019 (95% CI, 0.015 to 0.023), 0.011 (95% CI, 0.009 to 0.014) and 0.013 (95% CI, 0.010 to 0.016) in the LOS for inpatients with AMI, pneumonia and PCI surgery, respectively. Adding the interaction term between the reimbursement rate and in-hospital survival, the average marginal effects for the deceased inpatients with AMI and PCI surgery were 0.044 (95% CI, 0.031 to 0.058) and 0.034 (95% CI, 0.017 to 0.051), respectively. However, there was no evidence that higher reimbursement rates prolonged the LOS of the patients who died of pneumonia (95% CI, −0.013 to 0.016).ConclusionsThe findings indicate that the higher the reimbursement rate, the longer the LOS; and implementing dynamic supervision and improving the service capabilities of primary healthcare providers may be an important strategy for reducing moral hazard in low-income and middle-income countries including China.

scholarly journals United States fatal pedestrian crash hot spot locations and characteristics

2021 ◽  
Vol 14 (1) ◽  
pp. 1-23
Author(s):  
Robert James Schneider ◽  
Rebecca Sanders ◽  
Frank Proulx ◽  
Hamideh Moayyed
Keyword(s):  
New York ◽  
New York City ◽  
Low Income ◽  
Hot Spots ◽  
Hot Spot ◽  
Pedestrian Safety ◽  
The Us ◽  
Safety Strategies ◽  
Traffic Volumes ◽  
Pedestrian Crashes

US pedestrian fatalities are at their highest level in nearly three decades and account for an increasing share of total traffic fatalities (16%). To achieve the vision of a future transportation system that produces zero deaths, pedestrian safety must be improved. In this study, we screened the entire US roadway network to identify fatal pedestrian crash “hot spot” corridors: 1,000-meter-long sections of roadway where six or more fatal pedestrian crashes occurred during an eightyear period. We identified 34 hot spot corridors during 2001-2008 and 31 during 2009-2016. While only five corridors were hot spots during both analysis periods, the 60 unique hot spots had remarkably consistent characteristics. Nearly all (97%) were multilane roadways, with 70% requiring pedestrians to cross five or more lanes. More than three-quarters had speed limits of 30 mph or higher, and 62% had traffic volumes exceeding 25,000 vehicles per day. All had adjacent commercial retail and service land uses, 72% had billboards, and three-quarters were bordered by low-income neighborhoods. Corridors with these characteristics clearly have the potential to produce high numbers of pedestrian fatalities. We also used hierarchical clustering to classify the hot spots based on their roadway and surrounding landuse characteristics into three types: regional highways, urban primary arterial roadways, and New York City thoroughfares. Each context may require different safety strategies. Our results support a systemic approach to improve pedestrian safety: Agencies should identify other roadway corridors with similar characteristics throughout the US and take actions to reduce the risk of future pedestrian fatalities.

Mixed Effects Logistic Model to Address Demographics and Neighborhood Environment on Pedestrian Injury Severity

2017 ◽  
Vol 2659 (1) ◽  
pp. 174-181 ◽  
Author(s):  
Rui Guo ◽  
Chunfu Xin ◽  
Pei-Sung Lin ◽  
Achilleas Kourtellis
Keyword(s):  
Low Income ◽  
Logistic Model ◽  
Injury Severity ◽  
Unobserved Heterogeneity ◽  
Pedestrian Safety ◽  
Mixed Effects ◽  
Neighborhood Environment ◽  
Severe Injury ◽  
Pedestrian Injury ◽  
Unsafe Behaviors

This paper examines the effects of demographics and neighborhood environment on pedestrian injury severity to inform proactive countermeasures for improving pedestrian safety. A mixed effects logistic model addressing unobserved heterogeneity was developed from 3,948 pedestrian-involved crashes that occurred in Florida from 2011 to 2014. Six normally distributed random parameters were identified to reflect random effects on the pedestrian injury severity. The heterogeneity of two demographic factors (older and male pedestrians) suggested the need for more customized education programs to improve pedestrian safety awareness and knowledge, especially for older pedestrians. Relative to low-income areas, 67.7% of pedestrians involved in crashes in higher-income areas were less likely to sustain severe injury. Analysis of sample data also indicated that low-income areas tended to have had more unsafe behaviors by pedestrians related to higher injury severity (e.g., crossing at dark in unlighted areas). Higher-income areas tended to have had more unsafe behaviors by drivers related to higher injury severity (e.g., distracted driving). Other significant factors included lighting conditions (daylight, darkness without lighting), speed limit, alcohol or drug impairment, dart or dash behavior, crossing indicator, and traffic control device indicator. Regarding neighborhood land use types, two indicators about the presence of bus stops and department stores or supermarkets nearby were significant, and their effects were also random. Further investigations are needed to identify systematically the need for effective countermeasures in severe injury crash clusters in the future.

Evaluation of Protected Left-Turn Phasing and Leading Pedestrian Intervals Effects on Pedestrian Safety

2021 ◽  
pp. 036119812110255
Author(s):  
Elissa Goughnour ◽  
Daniel Carter ◽  
Craig Lyon ◽  
Bhagwant Persaud ◽  
Bo Lan ◽  
...  
Keyword(s):  
New York ◽  
Empirical Bayes ◽  
Pedestrian Safety ◽  
The United States ◽  
Public Health Issue ◽  
Crash Frequency ◽  
Left Turn ◽  
Crash Modification Factors ◽  
Pedestrian Crashes ◽  
Benefit Cost

Pedestrian safety is an important public health issue for the United States, with pedestrian fatalities representing approximately 16% of all traffic-related fatalities in 2016. Nationwide, transportation agencies are increasing their efforts to implement engineering-based improvements that increase pedestrian safety. These agencies need statistically rigorous crash modification factors (CMFs) to demonstrate the safety effectiveness of such countermeasures, and to apply in benefit–cost analyses to justify their implementation. This study focused on developing CMFs for two countermeasures that show promise for improving pedestrian safety: protected or protected/permissive left-turn phasing, and leading pedestrian intervals (LPIs). Data were acquired from four North American cities that had installed one or both of the countermeasures of interest: Chicago, IL; New York City, NY; Charlotte, NC; and Toronto, ON. The empirical Bayes before–after study design was applied to estimate the change in expected crash frequency for crashes following treatment. The protected left-turn phasing evaluation showed a benefit in reducing vehicle–vehicle injury crashes, but did not produce statistically significant results for vehicle–pedestrian crashes. For those crashes a disaggregate analysis did reveal that this treatment could be especially beneficial where pedestrian volumes exceed 5,500 per day. The LPI evaluation showed a statistically significant reduction in vehicle–pedestrian crashes with an estimated CMF of 0.87.

A Correlated Random Parameters Model with Heterogeneity in Means to Account for Unobserved Heterogeneity in Crash Frequency Analysis

2020 ◽  
Vol 2674 (7) ◽  
pp. 312-322
Author(s):  
Xiaoyan Huo ◽  
Junqiang Leng ◽  
Qinzhong Hou ◽  
Hao Yang
Keyword(s):  
Frequency Analysis ◽  
Negative Binomial ◽  
Unobserved Heterogeneity ◽  
Good Alternative ◽  
Omitted Variables ◽  
Random Parameters ◽  
Safety Factors ◽  
Crash Frequency ◽  
Study Results ◽  
Different Sources

Unobserved heterogeneity induced by omitted variables is a major challenge in developing reliable road safety models. In recent years, the random parameters negative binomial (RPNB) model has been used frequently in crash frequency analysis to account for unobserved heterogeneity. However, the majority of past studies of the RPNB model assumed that there was no correlation between different sources of unobserved heterogeneity, which is not always true given the complex interactions of safety factors. Compared with the RPNB model, a more flexible random parameters model that is the correlated random parameters negative binomial with heterogeneity in means (CRPNBHM) model was proposed in this study. Results indicate that the CRPNBHM model could not only capture the otherwise unobserved heterogeneity, but also track the underlying correlation among different sources of unobserved heterogeneity, thus outperforming the RPNB model. In addition, new insights into the interactions of safety factors (e.g., the joint safety effects of heavy trucks and pavement rutting depth) were obtained from the CRPNBHM model and these are expected to be beneficial in developing effective safety countermeasures. Results from this study demonstrated the CRPNBHM model to be a good alternative for crash frequency analysis, particularly when unobserved heterogeneity was detected.

scholarly journals Supermarket and fast-food outlet exposure in Copenhagen: associations with socio-economic and demographic characteristics

2011 ◽  
Vol 14 (9) ◽  
pp. 1618-1626 ◽  
Author(s):  
Chalida M Svastisalee ◽  
Helene Nordahl ◽  
Charlotte Glümer ◽  
Bjørn E Holstein ◽  
Lisa M Powell ◽  
...  
Keyword(s):  
Low Income ◽  
Fast Food ◽  
Negative Binomial ◽  
Economic Status ◽  
Food Outlet ◽  
Cross Sectional ◽  
Fast Food Outlet ◽  
Food Outlets ◽  
The Usa ◽  
The City

AbstractObjectiveTo investigate whether exposure to fast-food outlets and supermarkets is socio-economically patterned in the city of Copenhagen.DesignThe study was based on a cross-sectional multivariate approach to examine the association between the number of fast-food outlets and supermarkets and neighbourhood-level socio-economic indicators. Food business addresses were obtained from commercial and public business locators and geocoded using a geographic information system for all neighbourhoods in the city of Copenhagen (n 400). The regression of counts of fast-food outlets and supermarkets v. indicators of socio-economic status (percentage of recent immigrants, percentage without a high-school diploma, percentage of the population under 35 years of age and average household income in Euros) was performed using negative binomial analysis.SettingCopenhagen, Denmark.SubjectsThe unit of analysis was neighbourhood (n 400).ResultsIn the fully adjusted models, income was not a significant predictor for supermarket exposure. However, neighbourhoods with low and mid-low income were associated with significantly fewer fast-food outlets. Using backwise deletion from the fully adjusted models, low income remained significantly associated with fast-food outlet exposure (rate ratio = 0·66–0·80) in the final model.ConclusionsIn the city of Copenhagen, there was no evidence of spatial patterning of supermarkets by income. However, we detected a trend in the exposure to fast-food outlets, such that neighbourhoods in the lowest income quartile had fewer fast-food outlets than higher-income neighbourhoods. These findings have similarities with studies conducted in the UK, but not in the USA. The results suggest there may be socio-economic factors other than income associated with food exposure in Europe.

scholarly journals Identifying Temporal Aggregation Effect on Crash-Frequency Modeling

2021 ◽  
Vol 13 (11) ◽  
pp. 6214
Author(s):  
Bumjoon Bae ◽  
Changju Lee ◽  
Tae-Young Pak ◽  
Sunghoon Lee
Keyword(s):  
Traffic Safety ◽  
Negative Binomial ◽  
Random Effect ◽  
Temporal Correlation ◽  
Negative Binomial Regression ◽  
Spatiotemporal Analysis ◽  
Parameter Estimates ◽  
Crash Frequency ◽  
Crash Frequency Modeling ◽  
Using Data

Aggregation of spatiotemporal data can encounter potential information loss or distort attributes via individual observation, which would influence modeling results and lead to an erroneous inference, named the ecological fallacy. Therefore, deciding spatial and temporal resolution is a fundamental consideration in a spatiotemporal analysis. The modifiable temporal unit problem (MTUP) occurs when using data that is temporally aggregated. While consideration of the spatial dimension has been increasingly studied, the counterpart, a temporal unit, is rarely considered, particularly in the traffic safety modeling field. The purpose of this research is to identify the MTUP effect in crash-frequency modeling using data with various temporal scales. A sensitivity analysis framework is adopted with four negative binomial regression models and four random effect negative binomial models having yearly, quarterly, monthly, and weekly temporal units. As the different temporal unit was applied, the result of the model estimation also changed in terms of the mean and significance of the parameter estimates. Increasing temporal correlation due to using the small temporal unit can be handled with the random effect models.

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