scholarly journals A GEOGRAPHIC WEIGHTED REGRESSION FOR RURAL HIGHWAYS CRASHES MODELLING USING THE GAUSSIAN AND TRICUBE KERNELS: A CASE STUDY OF USA RURAL HIGHWAYS

2017 ◽  
Vol XLII-4/W4 ◽  
pp. 305-309
Author(s):  
M. Aghayari ◽  
P. Pahlavani ◽  
B. Bigdeli
Keyword(s):  
Spatial Data ◽  
Surface Condition ◽  
Light Condition ◽  
World Health ◽  
Effective Parameters ◽  
Rural Highways ◽  
Explanatory Variables ◽  
Geographic Space ◽  
Health Organization ◽  
Highway Crashes

Based on world health organization (WHO) report, driving incidents are counted as one of the eight initial reasons for death in the world. The purpose of this paper is to develop a method for regression on effective parameters of highway crashes. In the traditional methods, it was assumed that the data are completely independent and environment is homogenous while the crashes are spatial events which are occurring in geographic space and crashes have spatial data. Spatial data have spatial features such as spatial autocorrelation and spatial non-stationarity in a way working with them is going to be a bit difficult. The proposed method has implemented on a set of records of fatal crashes that have been occurred in highways connecting eight east states of US. This data have been recorded between the years 2007 and 2009. In this study, we have used GWR method with two Gaussian and Tricube kernels. The Number of casualties has been considered as dependent variable and number of persons in crash, road alignment, number of lanes, pavement type, surface condition, road fence, light condition, vehicle type, weather, drunk driver, speed limitation, harmful event, road profile, and junction type have been considered as explanatory variables according to previous studies in using GWR method. We have compered the results of implementation with OLS method. Results showed that R<sup>2</sup> for OLS method is 0.0654 and for the proposed method is 0.9196 that implies the proposed GWR is better method for regression in rural highway crashes.

scholarly journals Analysis of Nonsevere Crashes on Two- and Four-Lane Urban and Rural Highways: Effects of Wet Pavement Surface Condition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Aschalew Kassu ◽  
Michael Anderson
Keyword(s):  
Negative Binomial ◽  
Surface Condition ◽  
Negative Binomial Regression ◽  
Segment Length ◽  
Mean Values ◽  
Rural Highways ◽  
Explanatory Variables ◽  
Crash Data ◽  
Pavement Surface ◽  
Binomial Regression

This study examines the effects of wet pavement surface conditions on the likelihood of occurrences of nonsevere crashes in two- and four-lane urban and rural highways in Alabama. Initially, sixteen major highways traversing across the geographic locations of the state were identified. Among these highways, the homogenous routes with equal mean values, variances, and similar distributions of the crash data were identified and combined to form crash datasets occurring on dry and wet pavements separately. The analysis began with thirteen explanatory variables covering engineering, environmental, and traffic conditions. The principal terms were statistically identified and used in a mathematical crash frequency models developed using Poisson and negative binomial regression models. The results show that the key factors influencing nonsevere crashes on wet pavement surfaces are mainly segment length, traffic volume, and posted speed limits.

scholarly journals Forecasting Mobility Trends in Southeast Asia during the Coronavirus (Covid-19) Pandemic by Machine Learning Approaches

2021 ◽  
pp. 45-53
Keyword(s):  
Machine Learning ◽  
Southeast Asia ◽  
Spatial Data ◽  
Performance Model ◽  
World Health ◽  
Learning Approaches ◽  
Health Authorities ◽  
Short Period ◽  
Novel Coronavirus ◽  
Health Organization

The novel coronavirus (COVID-19) was declared as the 2019-20 coronavirus pandemic by the World Health Organization (WHO) in March 2020. The COVID-19 virus has rapidly spread nationwide and internationally and caused 188 countries to report more than ten million cases of individuals contracting COVID-19. Typically, the virus is conveyed from person to person via respiratory droplets produced by coughing and sneezing. The time period between exposure and onset of symptoms is typically between two and fourteen days, and on average five days. The COVID-19 pandemic has affected many businesses relating to transportation including tourism, import-export commerce, the aviation business, and so forth. Governmental intervention in each country has had an impact on mobility trends depending on the degree of restriction such as social distancing, sharing mobility, and public transport. A COVID-19 surveillance system is one of the principal methods used for detecting COVID-19 epidemics, using short-period monitoring. However, while these networks present information on the activities of COVID-19, acquiring completed surveillance data from every medical station is profusely difficult due to many factors. This research aims to propose a performance model of machine learning approaches for COVID-19 pandemic forecasting of mobility trends in each country in Southeast Asia. Spatial data and non-spatial data are used to build the machine learning models. The experiments conducted showed that the model gave a forecasting accuracy in walking and driving mobility of 94.40% and 92.00%, respectively. The proposed forecasting model was developed to be of benefits to health authorities in the planning and administration of a suitable strategy to make decisions concerning transportation planning in each country.

scholarly journals Groundwater Quality of Coastal Aquifer Evaluation Using Spatial Analysis Approach

2018 ◽  
Vol 34 (6) ◽  
pp. 2902-2912
Author(s):  
J. Saravanan ◽  
Kishan Singh Rawat ◽  
Sudhir Kumar Singh
Keyword(s):  
Groundwater Quality ◽  
Spatial Data ◽  
Tamil Nadu ◽  
Research Work ◽  
Quality Parameters ◽  
World Health ◽  
Entire Study ◽  
Groundwater Samples ◽  
Health Organization

Groundwater quality of Thiruvallur (district of Tamil Nadu) of coastal areas of the Bay of Bengal has been studied. Standard overlay analysis; techniques have been used for analyzing spatial data in Geographic Information System platform. For this research work, groundwater samples were collected from bore wells and open wells covering the whole study area. The collected samples were analyzed for physical, cations and anions. The thematic maps of groundwater quality parameters of the entire study area were prepared using Inverse Distance Weightage interpolation technique. Further, water quality index was computed for the region on a recommendation of standard permissible limitsrecommended by World Health Organization (WHO) 2006 for the suitability of groundwater for drinking purposes.

scholarly journals Spatial Distribution and Predictive Factors of Antenatal Care in Burundi

2021 ◽  
Author(s):  
Emmanuel BARANKANIRA ◽  
arnaud Iradukunda ◽  
Nestor NTAKABURIMVO ◽  
Willy AHISHAKIYE ◽  
Jean Claude NSAVYIMANA
Keyword(s):  
Spatial Analysis ◽  
Antenatal Care ◽  
Kernel Method ◽  
Obstetric Care ◽  
Well Being ◽  
World Health ◽  
Explanatory Variables ◽  
Data Points ◽  
Health Organization ◽  
Low Prevalence

Abstract Background: The use of obstetric care by pregnant women enables them to receive antenatal and postnatal care. This care includes counseling, health instructions, examinations and tests to avoid pregnancy-related complications or death during childbirth. To avoid these complications, the World Health Organization (WHO) recommends at least four antenatal visits. This study deals with the spatial analysis of antenatal care (ANC) among women aged 15 to 49 with a doctor and associated factors in Burundi.Methods: Data were obtained from the second Demographic and Health Survey (DHS) carried out in 2010. A spatial analysis of the prevalence of ANC made it possible to map this prevalence by region and province, and to interpolate the cluster-based ANC prevalence at unsampled data points using the kernel method with an adaptive window. The dependent variable is the antenatal care (yes / no) with a doctor and the explanatory variables are place of residence, age, level of education, religion, marital status of the woman, the quintile of economic well-being of the household and place of birth of the woman. Factors associated with ANC were assessed using binary mixed logistic regression. Data were analyzed using R software, version 3.5.0.Results: The findings of this study clearly show that ANC prevalence varies from 0 to 16.2% with a median of 0.5%. A pocket of prevalence was observed at the junction between Muyinga and Kirundo provinces. Low prevalence was observed in several locations in all regions of the provinces. They also show that woman’s education level and place of delivery are significantly associated with antenatal care.Conclusion: Prevalence of ANC is not the same across the country. It varies between regions and provinces. Besides, there is intra-regional or intra-provincial heterogeneity in the prevalence of ANC.

scholarly journals Modelling and mapping of the COVID-19 trajectory and pandemic paths at global scale: A geographer’s perspective

2020 ◽  
Vol 12 (1) ◽  
pp. 1603-1616
Author(s):  
Aleksandar Valjarević ◽  
Marija Milić ◽  
Dragana Valjarević ◽  
Zorica Stanojević-Ristić ◽  
Ljiljana Petrović ◽  
...  
Keyword(s):  
Spatial Data ◽  
Road Traffic ◽  
Low Cost ◽  
Global Scale ◽  
Geographical Information ◽  
World Health ◽  
Complete Analysis ◽  
Traffic Networks ◽  
The World ◽  
Health Organization

AbstractIn December 2019, the virus SARS-CoV-2 responsible for the COVID-19 pandemic was detected in the Chinese city of Wuhan. The virus started to spread from China and dispersed over the rest of the world. In March 2020, WHO (World Health Organization) declared COVID-19 a pandemic. The transmission path of the pandemic was accelerated by different types of transportation. With complete analysis of spatial data, population density, types of traffic networks, and their properties, the spatial distribution of COVID-19 was estimated. GIS (Geographical Information System), numerical methods, and software for network analysis were used in this research to model scenarios of virus distribution on a global scale. The analyzed data included air, railway, marine, and road traffic. In the pandemic research, numerous models of possible trajectory of viruses can be created. Many have a stochastic character. This study includes all countries in the world affected by the COVID-19 up to date. In this study, GIS methods such as buffer, interpolations, and numerical analysis were used in order to estimate and visualize ongoing COVID-19 pandemic situation. According to the availability of new data, trajectory of virus paths was estimated. On the other hand, sparsely populated areas with poorly developed and small traffic networks (and isolated island territories) tend to be less or not affected as shown by the model. This low-cost approach can be used in order to define important measures that need to be addressed and implemented in order to successfully mitigate the implications of COVID-19 not only on global, but local and regional scales as well.

Obstacles to Claiming Permanence and Injury-Relatedness for “Posttraumatic” Headache

2009 ◽  
Vol 14 (3) ◽  
pp. 3-6
Author(s):  
Robert J. Barth
Keyword(s):  
Complete Recovery ◽  
World Health ◽  
Related Factors ◽  
Posttraumatic Headache ◽  
Sixth Edition ◽  
Causative Relationship ◽  
Short Period ◽  
The One ◽  
Health Organization ◽  
Subjective Reports

Abstract “Posttraumatic” headaches claims are controversial because they are subjective reports often provided in the complex of litigation, and the underlying pathogenesis is not defined. This article reviews principles and scientific considerations in the AMAGuides to the Evaluation of Permanent Impairment (AMA Guides) that should be noted by evaluators who examine such cases. Some examples in the AMA Guides, Sixth Edition, may seem to imply that mild head trauma can cause permanent impairment due to headache. The author examines scientific findings that present obstacles to claiming that concussion or mild traumatic brain injury is a cause of permanent headache. The World Health Organization, for example, found a favorable prognosis for posttraumatic headache, and complete recovery over a short period of time was the norm. Other studies have highlighted the lack of a dose-response correlation between trauma and prolonged headache complaints, both in terms of the frequency and the severity of trauma. On the one hand, scientific studies have failed to support the hypothesis of a causative relationship between trauma and permanent or prolonged headaches; on the other hand, non–trauma-related factors are strongly associated with complaints of prolonged headache.

Sixth Edition: the New Standard

2008 ◽  
Vol 13 (1) ◽  
pp. 1-12
Author(s):  
Christopher R. Brigham ◽  
Robert D. Rondinelli ◽  
Elizabeth Genovese ◽  
Craig Uejo ◽  
Marjorie Eskay-Auerbach
Keyword(s):  
Review Process ◽  
Peer Review Process ◽  
World Health ◽  
International Classification Of Functioning ◽  
Revision Process ◽  
Sixth Edition ◽  
Impairment Ratings ◽  
Health Organization ◽  
Impairment Severity

Abstract The AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), Sixth Edition, was published in December 2007 and is the result of efforts to enhance the relevance of impairment ratings, improve internal consistency, promote precision, and simplify the rating process. The revision process was designed to address shortcomings and issues in previous editions and featured an open, well-defined, and tiered peer review process. The principles underlying the AMA Guides have not changed, but the sixth edition uses a modified conceptual framework based on the International Classification of Functioning, Disability, and Health (ICF), a comprehensive model of disablement developed by the World Health Organization. The ICF classifies domains that describe body functions and structures, activities, and participation; because an individual's functioning and disability occur in a context, the ICF includes a list of environmental factors to consider. The ICF classification uses five impairment classes that, in the sixth edition, were developed into diagnosis-based grids for each organ system. The grids use commonly accepted consensus-based criteria to classify most diagnoses into five classes of impairment severity (normal to very severe). A figure presents the structure of a typical diagnosis-based grid, which includes ranges of impairment ratings and greater clarity about choosing a discreet numerical value that reflects the impairment.

The Historical Development of Burden of Treatment Compliance

2014 ◽  
Vol 19 (5) ◽  
pp. 13-15
Author(s):  
Stephen L. Demeter
Keyword(s):  
Internal Medicine ◽  
Treatment Compliance ◽  
World Health ◽  
International Classification Of Functioning ◽  
Sixth Edition ◽  
Burden Of Treatment ◽  
Specific Goal ◽  
Surrogate Measure ◽  
Health Organization

Abstract A long-standing criticism of the AMA Guides to the Evaluation of Permanent Impairment (AMA Guides) has been the inequity between the internal medicine ratings and the orthopedic ratings; in the comparison, internal medicine ratings appear inflated. A specific goal of the AMA Guides, Sixth Edition, was to diminish, where possible, those disparities. This led to the use of the International Classification of Functioning, Disability, and Health from the World Health Organization in the AMA Guides, Sixth Edition, including the addition of the burden of treatment compliance (BOTC). The BOTC originally was intended to allow rating internal medicine conditions using the types and numbers of medications as a surrogate measure of the severity of a condition when other, more traditional methods, did not exist or were insufficient. Internal medicine relies on step-wise escalation of treatment, and BOTC usefully provides an estimate of impairment based on the need to be compliant with treatment. Simplistically, the need to take more medications may indicate a greater impairment burden. BOTC is introduced in the first chapter of the AMA Guides, Sixth Edition, which clarifies that “BOTC refers to the impairment that results from adhering to a complex regimen of medications, testing, and/or procedures to achieve an objective, measurable, clinical improvement that would not occur, or potentially could be reversed, in the absence of compliance.

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