Non-Emergency Medical Transportation Needs of Middle-Aged and Older Adults: A Rural-Urban Comparison in Delaware, USA.

Background: Older adults in rural areas have unique transportation barriers to accessing medical care, which include a lack of mass transit options and considerable distances to health-related services. This study contrasts non-emergency medical transportation (NEMT) service utilization patterns and associated costs for Medicaid middle-aged and older adults in rural versus urban areas. Methods: Data were analyzed from 39,194 NEMT users of LogistiCare-brokered services in Delaware residing in rural (68.3%) and urban (30.9%) areas. Multivariable logistic analyses compared trip characteristics by rurality designation. Results: Rural (37.2%) and urban (41.2%) participants used services more frequently for dialysis than for any other medical concern. Older age and personal accompaniment were more common and wheel chair use was less common for rural trips. The mean cost per trip was greater for rural users (difference of $2910 per trip), which was attributed to the greater distance per trip in rural areas. Conclusions: Among a sample who were eligible for subsidized NEMT and who utilized this service, rural trips tended to be longer and, therefore, higher in cost. Over 50% of trips were made for dialysis highlighting the need to address prevention and, potentially, health service improvements for rural dialysis patients

Minimum commuting distance as a spatial characteristic in a non-monocentric urban system : the case of Flanders

This paper focuses on regional variations in commuting trip lengths by calculating minimum (required) commuting distances, along with excess commuting rates. The study contributes to the excess commuting research framework from a regional perspective, both by stressing the specific characteristics of urban networks with overlapping commute areas, and by putting forward an alternative method for calculating spatially disaggregated values. A case study in the north of Belgium shows that large variations in minimum commuting distances occur. This in turn identifies to a large extent opportunities for shrinking commuting distances by influences such as rising fuel prices, compact urban planning, extreme congestion or dissuasive traffic policies

Ambulance Emergency Response Optimization in Developing Countries

The lack of emergency medical transportation is viewed as the main barrier to the access of emergency medical care in low and middle-income countries (LMICs). In this paper, we present a robust optimization approach to optimize both the location and routing of emergency response vehicles, accounting for uncertainty in travel times and spatial demand characteristic of LMICs. We traveled to Dhaka, Bangladesh, the sixth largest and third most densely populated city in the world, to conduct field research resulting in the collection of two unique datasets that inform our approach. This data is leveraged to develop machine learning methodologies to estimate demand for emergency medical services in a LMIC setting and to predict the travel time between any two locations in the road network for different times of day and days of the week. We combine our robust optimization and machine learning frameworks with real data to provide an in-depth investigation into three policy-related questions. First, we demonstrate that outpost locations optimized for weekday rush hour lead to good performance for all times of day and days of the week. Second, we find that significant improvements in emergency response times can be achieved by re-locating a small number of outposts and that the performance of the current system could be replicated using only 30% of the resources. Lastly, we show that a fleet of small motorcycle-based ambulances has the potential to significantly outperform traditional ambulance vans. In particular, they are able to capture three times more demand while reducing the median response time by 42% due to increased routing flexibility offered by nimble vehicles on a larger road network. Our results provide practical insights for emergency response optimization that can be leveraged by hospital-based and private ambulance providers in Dhaka and other urban centers in LMICs

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

Assessing the recreational demand for agricultural land in Finland

It is widely assumed that the scenic attractiveness and other public good aspects of agricultural land can be utilized as a source of livelihood in rural areas in the form of recreation and tourism. In this study we use two approaches to consider whether agricultural landscapes are preferred as a destination for recreation (day trips) and rural tourism (overnight trips). We first analyse the choice of recreation site type based on a model that aggregates sites using the presence of agricultural land as an aggregation variable. Population survey data on recreation trips reveal an association between the respondent’s living environment, recreational activities and visit characteristics and the probability of choosing a destination with agricultural land. Second, we also estimate the demand functions for trips to agricultural sites and other destination types to consider whether the presence of agricultural land, as opposed to other land use categories, increases the number of trips and the benefits of recreation. The results suggest that agricultural landscapes are inferior to alternative site types in terms of per-trip benefits. However, agricultural landscapes are associated with high annual benefits because of the high rate of visitation

National Multi-Modal Travel Forecasts. Literature Review: Aggregate Models

This paper reviews the current state-of-the-art in the production of National Multi-Modal Travel Forecasts. The review concentrates on the UK travel market and the various attempts to produce a set of accurate, coherent and credible forecasts. The paper starts by a brief introduction to the topic area. The second section gives a description of the background to the process and the problems involved in producing forecasts. Much of the material and terminology in the section, which covers modelling methodologies, is from Ortúzar and Willumsen (1994). The paper then goes on to review the forecasting methodology used by the Department of Transport (DoT) to produce the periodic National Road Traffic Forecasts (NRTF), which are the most significant set of travel forecasts in the UK. A brief explanation of the methodology will be given. The next section contains details of how other individuals and organisations have used, commented on or attempted to enhance the DoT methodology and forecasts. It will be noted that the DoT forecasts are only concerned with road traffic forecasts, with other modes (rail, air and sea) only impacting on these forecasts when there is a transfer to or from the road transport sector. So the following sections explore the attempts to produce explicit travel and transportation forecasts for these other modes. The final section gathers together a set of issues which are raised by this review and might be considered by the project

Sustainability and change in the institutionalized commute in Belgium: exploring regional differences

This paper examines regional differences in commute-energy performance in Belgium, and explores their relationships with spatial characteristics such as the distribution of population and housing, the metropolitan influence of the Brussels agglomeration, and the compactness of cities and towns. We also investigate contradictions between Belgian state-wide commute policy and regional differences in average commuting distance and mode choice. Against a background of long-term federal measures that traditionally encourage long-distance commuting in Belgium, we find striking discrepancies between the structure and the development of commuting patterns in the three administrative regions of Flanders, Wallonia and Brussels. Residents of Brussels show the most sustainable commuting patterns, due to the metropolitan spatial structure. Residents of Wallonia represent the least sustainable commute. Given the rather weak regional economy of Wallonia compared with Flanders, commuters must frequently seek employment far from their residence. Population changes and consequent developments in the housing market seem to exacerbate this competitive disadvantage, since most growth occurs in relatively remote rural areas that are nevertheless within reach of the main employment centres

Economic Valuation of Environmental Benefits and the Targeting of Conservation Programs: The Case of the CRP

The range of environmental problems confronting agriculture has expanded in recent years. As the largest program designed to mitigate the negative environmental effects of agriculture, the Conservation Reserve Program (CRP) has broadened its initial focus on reductions in soil erosion to consider other landscape factors that may also be beneficial. For example, preserving habitats can help protect wildlife, thus leading to more nature-viewing opportunities. This report demonstrates how nonmarket valuation models can be used in targeting conservation programs such as the CRP.Environmental Economics and Policy,