Implementation of safety based incentives in Public Private Partnerships (PPPs): an empirical analysis for the case of Spain

Public Private Partnerships (PPPs) are mostly implemented to circumvent budgetary constraints, and to encourage efficiency and quality in the provision of public infrastructure in order to reach social welfare. One of the ways of reaching the latter objective is by the introduction of performance based standards tied to bonuses and penalties to reward or punish the performance of the contractor. This paper focuses on the implementation of safety based incentives in PPPs in such a way that the better the safety outcome the greater larger will be the economic reward to the contractor. The main aim of this paper is to identify whether the incentives to improve road safety in PPPs are ultimately effective in improving safety ratios in Spain. To that end, Poisson and negative binomial regression models have been applied using information of motorways of the Spanish network of 2006. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.

Analysis of road safety incentives in highway concessions in Spain

Public Private Partnerships (PPPs) are mostly implemented for three reasons: to circumvent budgetary constraints, encourage efficiency and improvement of quality in the provision of public infrastructure. One of the ways of reaching the latter objective is by the introduction of performance-based standards tied to bonuses and penalties to reward or punish the performance of the contractor. These performance based standards often refer to different aspects such as technical, environmental and safety issues. This paper focuses on the implementation of safety based incentives in PPPs. The main aim of this paper is to analyze whether the incentives to improve road safety in PPPs are effective in improving safety ratios in Spain. To this end, negative binomial regression models have been applied using information from the Spanish high capacity network in 2006. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles in the highway, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.

Effectiveness of safety-based incentives in Public Private Partnerships: Evidence from the case of Spain

Many countries around the world are implementing Public?Private?Partnership (PPP) contacts to manage road infrastructure. In some of these contracts the public sector introduces economic incentives to the private operator to foster the accomplishment of social goals. One of the incentives that have been introduced in some PPP contracts is related to safety in such a way that the better the safety outcome the greater will be the economic reward to the contractor. The aim of this paper is at identify whether the incentives to improve road safety in highway PPPs are ultimately effective in improving safety ratios. To this end Poisson and negative binomial regression models have been applied using information from highway sections in Spain. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.

The influence of economic incentives linked to road safety indicators on accidents: The case of toll concessions in Spain

The goal of this paper is to evaluate whether the incentives incorporated in toll highway concession contracts in order to encourage private operators to adopt measures to reduce accidents are actually effective at improving safety. To this end, we implemented negative binomial regression models using information about highway characteristics and accident data from toll highway concessions in Spain from 2007 to 2009. Our results show that even though road safety is highly influenced by variables that are not managed by the contractor, such as the annual average daily traffic (AADT), the percentage of heavy vehicles on the highway, number of lanes, number of intersections and average speed; the implementation of these incentives has a positive influence on the reduction of accidents and injuries. Consequently, this measure seems to be an effective way of improving safety performance in road networks.

Analysis of road safety incentives in highway concessions in Spain

Public Private Partnerships (PPPs) are mostly implemented for three reasons: to circumvent budgetary constraints, encourage efficiency and improvement of quality in the provision of public infrastructure. One of the ways of reaching the latter objective is by the introduction of performance-based standards tied to bonuses and penalties to reward or punish the performance of the contractor. These performance based standards often refer to different aspects such as technical, environmental and safety issues. This paper focuses on the implementation of safety based incentives in PPPs. The main aim of this paper is to analyze whether the incentives to improve road safety in PPPs are effective in improving safety ratios in Spain. To this end, negative binomial regression models have been applied using information from the Spanish high capacity network in 2006. The findings indicate that even though road safety is highly influenced by variables that are not much controllable by the contractor such as the Average Annual Daily Traffic and the percentage of heavy vehicles in the highway, the implementation of safety incentives in PPPs has a positive influence in the reduction of fatalities, injuries and accidents.

Do Public Private Partnerships Improve Road Safety? The Case of Toll Concessions in Spain

El Transportation Research Board es un congreso de reconocido prestigio internacional en el ámbito de la investigación del transporte. Aunque las actas publicadas están en formato digital y sin ISSN ni ISBN, lo consideramos lo suficientemente importante como para que se considere en los indicadores. This paper focuses on the implementation of safety based incentives in Public Private Partnerships (PPPs). The aim of this paper is twofold. First, to evaluate whether PPPs lead to an improvement in road safety, when compared with other infrastructure management systems. Second, is to analyze whether the incentives to improve road safety in PPP contracts in Spain have been effective at improving safety performance. To this end, negative binomial regression models have been applied using information from the Spanish high-capacity network covering years 2007-2009. The results showed that even though road safety is highly influenced by variables that are not manageable by the private concessionaire such as the average annual daily traffic, the implementation of safety incentives in PPPs has a positive influence in the reduction of accidents.

Moderating Variables Impacting Adherence to the Reducing Disability in Alzheimer's Disease (RDAD) Intervention

Thesis (Ph.D.)--University of Washington, 2016-06

Polymorphisms in glutathione S-transferases and non-melanoma skin cancer risk in Australian renal transplant recipients

Caucasian renal transplant recipients from Queensland, Australia have the highest non-melanoma skin cancer (NMSC) risk worldwide. Although ultraviolet light (UVR) exposure is critical, genetic factors also appear important. We and others have shown that polymorphism in the glutathione S-transferases (GST) is associated with NMSC in UK recipients. However, the effect of high UVR exposure and differences in immunosuppressive regimen on these associations is unknown. In this study, we examined allelism in GSTM1, GSTM3, GSTT1 and GSTP1 in 361 Queensland renal transplant recipients. Data on squamous (SCC) and basal cell carcinoma (BCC), UVR/tobacco exposure and genotype were obtained. Associations with both NMSC risk and numbers were examined using logistic and negative binomial regression, respectively. In the total group, GSTM1 AB [P = 0.049, rate ratio (RR) = 0.23] and GSTM3 AA (P = 0.015, RR = 0.50) were associated with fewer SCC. Recipients were then stratified by prednisolone dose (less than or equal to7 versus >7 mg/day). In the low-dose group, GSTT1 null (P = 0.006, RR = 0.20) and GSTP1 Val/Val (P = 0.021, RR = 0.20) were associated with SCC numbers. In contrast, in the high-dose group, GSTM1 AB (P = 0.009, RR = 0.05), GSTM3 AB (P = 0.042, RR = 2.29) and BB (P = 0.014, RR = 5.31) and GSTP1 Val/Val (P = 0.036, RR = 2.98) were associated with SCC numbers. GSTM1 AB (P = 0.016) and GSTP1 Val/Val (P = 0.046) were also associated with fewer BCC in this group. GSTP1 associations were strongest in recipients with lower UVR/tobacco exposure. The data confirm our UK findings, suggesting that protection against UVR-induced oxidative stress is important in NMSC development in recipients, but that this effect depends on the immunosuppressant regimen.

Food intake and risk of squamous cell carcinoma of the skin in a community: The Nambour skin cancer cohort study

There is some evidence that dietary factors may modify the risk of squamous cell carcinoma (SCC) of the skin, but the association between food intake and SCC has not been evaluated prospectively. We examined the association between food intake and SCC incidence among 1,056 randomly selected adults living in an Australian sub-tropical community. Measurement-error corrected estimates of intake in 15 food groups were defined from a validated food frequency questionnaire in 1992. Associations with SCC risk were assessed using Poisson and negative binomial regression to the persons affected and tumour counts, respectively, based on incident, histologically confirmed tumours occurring between 1992 and 2002. After multivariable adjustment, none of the food groups was significantly associated with SCC risk. Stratified analysis in participants with a past history of skin cancer showed a decreased risk of SCC tumours for high intakes of green leafy vegetables (RR = 0.45, 95% CI = 0.22-0.91; p for trend = 0.02) and an increased risk for high intake of unmodified dairy products (RR = 2.53, 95% CI: 1.15-5.54; p for trend = 0.03). Food intake was not associated with SCC risk in persons who had no past history of skin cancer. These findings suggest that consumption of green leafy vegetables may help prevent development of subsequent SCCs of the skin among people with previous skin cancer and that consumption of unmodified dairy products, such as whole milk, cheese and yoghurt, may increase SCC risk in susceptible persons.

Development of safety performance functions for SafetyAnalyst applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency's safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.

Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

UPTAKE OF THE PERIODIC HEALTH EXAM AMONG ADULTS WITH INTELLECTUAL AND DEVELOPMENTAL DISABILITIES FROM 2003 TO 2015

Background: Over the past decade, annual heath exams have been de-emphasized for the general population but emphasized for adults with intellectual and developmental disabilities (IDD). The purpose of this project was to determine if there has been an increase in the uptake of the health exam among adults with IDD in Ontario, to what extent, and the effect on the quality of preventive care provided. Methods: Using administrative health data, the proportion of adults (18-64 years old) with IDD who received a health exam (long appointment, general assessment, and “true” health exam), a high value on the primary care quality composite score (PCQS), and a health exam or high PCQS each year was compared to the proportion in a propensity score matched sample of the general population. Negative binomial and segmented negative binomial regression controlling for age and sex were used to determine the relative risk of having a health exam/high PCQS/health exam or PCQS over time. Results: Pre joinpoint, the long appointment and general assessment health exam definitions saw a decrease and the “true” health exam saw an increase in the likelihood of adults having a health exam. Post joinpoint, all health exam definitions saw a decrease in the likelihood of adults having a health exam. Pre joinpoint, all PCQS measures (high PCQS, long appointment or high PCQS, “true” health exam or high PCQS) saw an increase in the likelihood for adults to achieve a high PCQS or high PCQS/have a health exam. Post joinpoint, all PCQS measures saw a decrease in the likelihood for adults to achieve a high PCQS or high PCQS/have a health exam. Achieving a high PCQS was strongly associated with having a health exam regardless of health exam definition or IDD status. Conclusions: Despite the publication of guidelines, only a small proportion of adults with IDD are receiving health exams. This indicates that the publication of guidelines alone was not sufficient to change practice. More targeted measures, such as the implementation of an IDD-specific health exam fee code, should be considered to increase the uptake of the health exam among adults with IDD.

Estimación del descarte y captura incidental en la pesquería industrial de cerco del stock norte-centro de la anchoveta peruana (Engraulis ringens)

Este estudio presenta la validación de las observaciones que realizó el programa de observación pesquera llamado Programa Bitácoras de Pesca (PBP) durante el periodo 2005 - 2011 en el área de distribución donde operan las embarcaciones industriales de cerco dedicadas a la pesca del stock norte-centro de la anchoveta peruana (Engraulis ringens). Además, durante ese mismo periodo y área de distribución, se estimó la magnitud del descarte por exceso de captura, descarte de juveniles y la captura incidental de dicha pesquera. Se observaron 3 768 viajes de un total de 302 859, representando un porcentaje de 1.2 %. Los datos del descarte por exceso de captura, descarte de juveniles y captura incidental registrados en los viajes observados, se caracterizaron por presentar un alta proporción de ceros. Para la validación de las observaciones, se realizó un estudio de simulación basado en la metodología de Monte Carlo usando un modelo de distribución binomial negativo. Esta permite inferir sobre el nivel de cobertura óptima y conocer si la información obtenida en el programa de observación es contable. De este análisis, se concluye que los niveles de observación actual se deberían incrementar hasta tener un nivel de cobertura de al menos el 10% del total de viajes que realicen en el año las embarcaciones industriales de cerco dedicadas a la pesca del stock norte-centro de la anchoveta peruana. La estimación del descarte por exceso de captura, descarte de juveniles y captura incidental se realizó mediante tres metodologías: Bootstrap, Modelo General Lineal (GLM) y Modelo Delta. Cada metodología estimó distintas magnitudes con tendencias similares. Las magnitudes estimadas fueron comparadas usando un ANOVA Bayesiano, la cual muestra que hubo escasa evidencia que las magnitudes estimadas del descarte por exceso de captura por metodología sean diferentes, lo mismo se presentó para el caso de la captura incidental, mientras que para el descarte de juveniles mostró que hubieron diferencias sustanciales de ser diferentes. La metodología que cumplió los supuestos y explico la mayor variabilidad de las variables modeladas fue el Modelo Delta, el cual parece ser una mejor alternativa para la estimación, debido a la alta proporción de ceros en los datos. Las estimaciones promedio del descarte por exceso de captura, descarte de juveniles y captura incidental aplicando el Modelo Delta, fueron 252 580, 41 772, 44 823 toneladas respectivamente, que en conjunto representaron el 5.74% de los desembarques. Además, con la magnitud de la estimación del descarte de juveniles, se realizó un ejercicio de proyección de biomasa bajo el escenario hipotético de no mortalidad por pesca y que los individuos juveniles descartados sólo presentaron tallas de 8 y 11 cm., en la cual se obtuvo que la biomasa que no estará disponible a la pesca está entre los 52 mil y 93 mil toneladas.

Upgrading Bridge Rails on Low-Volume Roads in Iowa, TR-679, 2016

Building on previous research, the goal of this project was to identify significant influencing factors for the Iowa Department of Transportation (DOT) to consider in future updates of its Instructional Memorandum (I.M.) 3.213, which provides guidelines for determining the need for traffic barriers (guardrail and bridge rail) at secondary roadway bridges—specifically, factors that might be significant for the bridge rail rating system component of I.M. 3.213. A literature review was conducted of policies and guidelines in other states and, specifically, of studies related to traffic barrier safety countermeasures at bridges in several states. In addition, a safety impact study was conducted to evaluate possible non-driver-related behavior characteristics of crashes on secondary road structures in Iowa using road data, structure data, and crash data from 2004 to 2013. Statistical models (negative binomial regression) were used to determine which factors were significant in terms of crash volume and crash severity. The study found that crashes are somewhat more frequent on or at bridges possessing certain characteristics—traffic volume greater than 400 vehicles per day (vpd) (paved) or greater than 50 vpd (unpaved), bridge length greater than 150 ft (paved) or greater than 35 ft (unpaved), bridge width narrower than its approach (paved) or narrower than 20 ft (unpaved), and bridges older than 25 years (both paved and unpaved). No specific roadway or bridge characteristic was found to contribute to more serious crashes. The study also confirmed previous research findings that crashes with bridges on secondary roads are rare, low-severity events. Although the findings of the study support the need for appropriate use of bridge rails, it concludes that prescriptive guidelines for bridge rail use on secondary roads may not be necessary, given the limited crash expectancy and lack of differences in crash expectancy among the various combinations of explanatory characteristics.

Development of Safety Performance Functions for SafetyAnalyst Applications in Florida

In 2010, the American Association of State Highway and Transportation Officials (AASHTO) released a safety analysis software system known as SafetyAnalyst. SafetyAnalyst implements the empirical Bayes (EB) method, which requires the use of Safety Performance Functions (SPFs). The system is equipped with a set of national default SPFs, and the software calibrates the default SPFs to represent the agency’s safety performance. However, it is recommended that agencies generate agency-specific SPFs whenever possible. Many investigators support the view that the agency-specific SPFs represent the agency data better than the national default SPFs calibrated to agency data. Furthermore, it is believed that the crash trends in Florida are different from the states whose data were used to develop the national default SPFs. In this dissertation, Florida-specific SPFs were developed using the 2008 Roadway Characteristics Inventory (RCI) data and crash and traffic data from 2007-2010 for both total and fatal and injury (FI) crashes. The data were randomly divided into two sets, one for calibration (70% of the data) and another for validation (30% of the data). The negative binomial (NB) model was used to develop the Florida-specific SPFs for each of the subtypes of roadway segments, intersections and ramps, using the calibration data. Statistical goodness-of-fit tests were performed on the calibrated models, which were then validated using the validation data set. The results were compared in order to assess the transferability of the Florida-specific SPF models. The default SafetyAnalyst SPFs were calibrated to Florida data by adjusting the national default SPFs with local calibration factors. The performance of the Florida-specific SPFs and SafetyAnalyst default SPFs calibrated to Florida data were then compared using a number of methods, including visual plots and statistical goodness-of-fit tests. The plots of SPFs against the observed crash data were used to compare the prediction performance of the two models. Three goodness-of-fit tests, represented by the mean absolute deviance (MAD), the mean square prediction error (MSPE), and Freeman-Tukey R2 (R2FT), were also used for comparison in order to identify the better-fitting model. The results showed that Florida-specific SPFs yielded better prediction performance than the national default SPFs calibrated to Florida data. The performance of Florida-specific SPFs was further compared with that of the full SPFs, which include both traffic and geometric variables, in two major applications of SPFs, i.e., crash prediction and identification of high crash locations. The results showed that both SPF models yielded very similar performance in both applications. These empirical results support the use of the flow-only SPF models adopted in SafetyAnalyst, which require much less effort to develop compared to full SPFs.