Planning and evaluation

Introduction: The core business of public health is to protect and promote health in the population. Public health planning is the means to maximise these aspirations. Health professionals develop plans to address contemporary health priorities as the evidence about changing patterns of mortality and morbidity is presented. Officials are also alert to international trends in patterns of disease that have the potential to affect the health of Australians. Integrated planning and preparation is currently underway involving all emergency health services, hospitals and population health units to ensure Australia's quick and efficient response to any major infectious disease outbreak, such as avian influenza (bird flu). Public health planning for the preparations for the Sydney Olympics and Paralympic Games in 2000 took almost three years. ‘Its major components included increased surveillance of communicable disease; presentations to sentinel emergency departments; medical encounters at Olympic venues; cruise ship surveillance; environmental and food safety inspections; bioterrorism surveillance and global epidemic intelligence’ (Jorm et al 2003, 102). In other words, the public health plan was developed to ensure food safety, hospital capacity, safe crowd control, protection against infectious diseases, and an integrated emergency and disaster plan. We have national and state plans for vaccinating children against infectious diseases in childhood; plans to promote dental health for children in schools; and screening programs for cervical, breast and prostate cancer. An effective public health response to a change in the distribution of morbidity and mortality requires planning. All levels of government plan for the public’s health. Local governments (councils) ensure healthy local environments to protect the public’s health. They plan parks for recreation, construct traffic-calming devices near schools to prevent childhood accidents, build shade structures and walking paths, and even embed drafts/chess squares in tables for people to sit and play. Environmental Health officers ensure food safety in restaurants and measure water quality. These public health measures attempt to promote the quality of life of residents. Australian and state governments produce plans that protect and promote health through various policy and program initiatives and innovations. To be effective, program plans need to be evaluated. However, building an integrated evaluation plan into a program plan is often forgotten, as planning and evaluation are seen as two distinct entities. Consequently, it is virtually impossible to measure, with any confidence, the extent to which a program has achieved its goals and objectives. This chapter introduces you to the concepts of public health program planning and evaluation. Case studies and reflection questions are presented to illustrate key points. As various authors use different terminology to describe the same concepts/actions of planning and evaluation, the glossary at the back of this book will help you to clarify the terms used in this chapter.

The rediscovery of traditional urbanism at Melrose Arch

Contemporary urban form, particularly in the cities of South Africa, lacks distinction and quality. The majority of developments are conceived as private and dislocated initiatives, surveiled enclaves with gated access being the only conduit to the outside world. Any concern for a positive contribution to the matrix of public activity is seldom a consideration. The urban form responds to the perception that traffic systems are paramount to the successful flux of the city in satisfying the escalating demands of vehicular movement. In contrast many of the urban centres around the world, the great historical centres of Europe, Americas and the Sub-Continent are admired and considered the ultimate models in urban experience. The colonnades, bazaars and boulevards hosting an abundance of street activity are the characteristics of such centres and are symptomatic of a city growth based on pedestrian movement patterns, an urbanism supportative of human interaction and exchange, a form which has nurtured the existence of a public realm. Through the understanding of the principles of traditional urbanism we may learn that the modernist paradigm of a contemporary suburbia has resulted in disconnected and separate land uses with isolated districts where a reliance on the car is essential rather than optional.

Parental beliefs about supervising children when crossing roads and cycling

Pedestrian and cyclist injuries are significant public health issues together accounting for 11-30% of road deaths in highly motorised countries. Children are particularly at risk. In Australia in 2009 children 0-16 years comprised 11.4% of pedestrian deaths and 6.4% of cyclist deaths. Parental attitudes and level of supervision are important to children’s road safety. Results from a telephone survey with parents of children 5-9 years (N=147) are reported. Questions addressed beliefs about preventability of injury, appropriate ages for children to cross the road or cycle independently, and the frequency of holding 5-9 year old children’s hands while crossing the road. Results suggest that parents believe most injuries are preventable and that they personally can act to improve their own safety in the home, on the road, at work, as well as in or on the water. Most parents (68%) indicated children should be 10 years or older before crossing the road or cycling independently. Parents were more likely to report holding younger children’s hands (5-6 years) when crossing the road and less likely to do so for 7-9 year olds. There was a small effect of child gender, with parents more likely to hold boy’s hand than a girl’s.

Modelling of inflatable rescue boats (IRBs) in surf conditions to reduce injuries

The Inflatable Rescue Boat (IRB) is arguably the most effective rescue tool used by the Australian surf lifesavers. The exceptional features of high mobility and rapid response have enabled it to become an icon on Australia's popular beaches. However, the IRB's extensive use within an environment that is as rugged as it is spectacular, has led it to become a danger to those who risk their lives to save others. Epidemiological research revealed lower limb injuries to be predominant, particularly the right leg. The common types of injuries were fractures and dislocations, as well as muscle or ligament strains and tears. The concern expressed by Surf Life Saving Queensland (SLSQ) and Surf Life Saving Australia (SLSA) led to a biomechanical investigation into this unique and relatively unresearched field. The aim of the research was to identify the causes of injury and propose processes that may reduce the instances and severity of injury to surf lifesavers during IRB operation. Following a review of related research, a design analysis of the craft was undertaken as an introduction to the craft, its design and uses. The mechanical characteristics of the vessel were then evaluated and the accelerations applied to the crew in the IRB were established through field tests. The data were then combined and modelled in the 3-D mathematical modelling and simulation package, MADYMO. A tool was created to compare various scenarios of boat design and methods of operation to determine possible mechanisms to reduce injuries. The results of this study showed that under simulated wave loading the boats flex around a pivot point determined by the position of the hinge in the floorboard. It was also found that the accelerations experienced by the crew exhibited similar characteristics to road vehicle accidents. Staged simulations indicated the attributes of an optimum foam in terms of thickness and density. Likewise, modelling of the boat and crew produced simulations that predicted realistic crew response to tested variables. Unfortunately, the observed lack of adherence to the SLSA footstrap Standard has impeded successful epidemiological and modelling outcomes. If uniformity of boat setup can be assured then epidemiological studies will be able to highlight the influence of implementing changes to the boat design. In conclusion, the research provided a tool to successfully link the epidemiology and injury diagnosis to the mechanical engineering design through the use of biomechanics. This was a novel application of the mathematical modelling software MADYMO. Other craft can also be investigated in this manner to provide solutions to the problem identified and therefore reduce risk of injury for the operators.

Safety impacts of alcohol and other drugs in construction : a mid term report

Estimated 640,700 persons suffered a work-related injury or illness in 2009-2010 and 444 lost their lives as a result in 2008-2009, in Australia Very little is known about what proportion of accidents are directly attributable to the effects of AOD Anecdotal evidence highlights issues of AOD and its association with safety risk on construction sites

Systems-based accident analysis in the led outdoor activity domain : application and evaluation of a risk management framework

Safety-compromising accidents occur regularly in the led outdoor activity domain. Formal accident analysis is an accepted means of understanding such events and improving safety. Despite this, there remains no universally accepted framework for collecting and analysing accident data in the led outdoor activity domain. This article presents an application of Rasmussen's risk management framework to the analysis of the Lyme Bay sea canoeing incident. This involved the development of an Accimap, the outputs of which were used to evaluate seven predictions made by the framework. The Accimap output was also compared to an analysis using an existing model from the led outdoor activity domain. In conclusion, the Accimap output was found to be more comprehensive and supported all seven of the risk management framework's predictions, suggesting that it shows promise as a theoretically underpinned approach for analysing, and learning from, accidents in the led outdoor activity domain.

Development of accident modification factors on intersection crash maneuvers

In order to estimate the safety impact of roadway interventions engineers need to collect, analyze, and interpret the results of carefully implemented data collection efforts. The intent of these studies is to develop Accident Modification Factors (AMF's), which are used to predict the safety impact of various road safety features at other locations or in upon future enhancements. Models are typically estimated to estimate AMF's for total crashes, but can and should be estimated for crash outcomes as well. This paper first describes data collected with the intent estimate AMF's for rural intersections in the state of Georgia within the United Sates. Modeling results of crash prediction models for the crash outcomes: angle, head-on, rear-end, sideswipe (same direction and opposite direction) and pedestrian-involved crashes are then presented and discussed. The analysis reveals that factors such as the Annual Average Daily Traffic (AADT), the presence of turning lanes, and the number of driveways have a positive association with each type of crash, while the median width and the presence of lighting are negatively associated with crashes. The model covariates are related to crash outcome in different ways, suggesting that crash outcomes are associated with different pre-crash conditions.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

Le infrastrutture viarie dismesse o declassate ed il progetto di paesaggio

Paesaggio ed infrastrutture viarie sono un binomio molto forte: il primo ha insito il concetto di accessibilità, in quanto non può esistere senza la presenza di un osservatore; la strada, invece, trova i fattori che la connotano nel suo rapporto con la morfologia su cui insiste. Le infrastrutture viarie sono elemento strutturale e strutturante non solo di un territorio, ma anche di un paesaggio. Le attuali esigenze di mobilità portano oggi a ripensare ed adeguare molte infrastrutture viarie: laddove è possibile si potenziano le strutture esistenti, in diversi casi si ricorre a nuovi tracciati o a varianti di percorso. Porsi il problema di conservare itinerari testimoni della cultura materiale ed economica di una società implica considerazioni articolate, che travalicano i limiti del sedime: una via è un organismo più complesso della semplice linea di trasporto in quanto implica tutta una serie di manufatti a supporto della mobilità e soprattutto il corridoio infrastrutturale che genera e caratterizza, ovvero una porzione variabile di territorio definita sia dal tracciato che dalla morfologia del contesto. L’evoluzione dei modelli produttivi ed economici, che oggi porta quote sempre maggiori di popolazione a passare un tempo sempre minore all’interno del proprio alloggio, rende la riflessione sulle infrastrutture viarie dismesse o declassate occasione per la progettazione di spazi per l’abitare collettivo inseriti in contesti paesaggistici, tanto urbani che rurali, tramite reti di percorsi pensate per assorbire tagli di mobilità specifici e peculiari. Partendo da queste riflessioni la Tesi si articola in: Individuazioni del contesto teorico e pratico: Lo studio mette in evidenza come la questione delle infrastrutture viarie e del loro rapporto con il paesaggio implichi riflessioni incrociate a diversi livelli e tramite diverse discipline. La definizione dello spazio fisico della strada passa infatti per la costruzione di un itinerario, un viaggio che si appoggia tanto ad elementi fisici quanto simbolici. La via è un organismo complesso che travalica il proprio sedime per coinvolgere una porzione ampia di territorio, un corridoio variabile ed articolato in funzione del paesaggio attraversato. Lo studio propone diverse chiavi di lettura, mettendo in luce le possibili declinazioni del tema, in funzione del taglio modale, del rapporto con il contesto, del regime giuridico, delle implicazioni urbanistiche e sociali. La mobilità dolce viene individuata quale possibile modalità di riuso, tutela e recupero, del patrimonio diffuso costituito dalle diversi reti di viabilità. Antologia di casi studio: Il corpo principale dello studio si basa sulla raccolta, analisi e studio dello stato dell’arte nel settore; gli esempi raccolti sono presentati in due sezioni: la prima dedicata alle esperienze più significative ed articolate, che affrontano il recupero delle infrastrutture viarie a più livelli ed in modo avanzato non concentrandosi solo sulla conversione del sedime, ma proponendo un progetto che coinvolga tutto il corridoio attraversato dall’infrastruttura; la seconda parte illustra la pratica corrente nelle diverse realtà nazionali, ponendo in evidenza similitudini e differenze tra i vari approcci.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Incorporating weather into regionwide safety planning prediction models

Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros

Accident prediction model for railway-highway interfaces

Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes. Considerable past research has explored relationships between vehicle accidents and geometric design and operation of road sections, but relatively little research has examined factors that contribute to accidents at railway-highway crossings. Between 1998 and 2002 in Korea, about 95% of railway accidents occurred at highway-rail grade crossings, resulting in 402 accidents, of which about 20% resulted in fatalities. These statistics suggest that efforts to reduce crashes at these locations may significantly reduce crash costs. The objective of this paper is to examine factors associated with railroad crossing crashes. Various statistical models are used to examine the relationships between crossing accidents and features of crossings. The paper also compares accident models developed in the United States and the safety effects of crossing elements obtained using Korea data. Crashes were observed to increase with total traffic volume and average daily train volumes. The proximity of crossings to commercial areas and the distance of the train detector from crossings are associated with larger numbers of accidents, as is the time duration between the activation of warning signals and gates. The unique contributions of the paper are the application of the gamma probability model to deal with underdispersion and the insights obtained regarding railroad crossing related vehicle crashes.