Survival Extrapolation In The Presence Of Cause Specific Hazards.

Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.

Measuring the accumulated hazards of smoking: global and regional estimates for 2000

Objective: Current prevalence of smoking, even where data are available, is a poor proxy for cumulative hazards of smoking, which depend on several factors including the age at which smoking began, duration of smoking, number of cigarettes smoked per day, degree of inhalation, and cigarette characteristics such as tar and nicotine content or filter type. Methods: We extended the Peto-Lopez smoking impact ratio method to estimate accumulated hazards of smoking for different regions of the world. Lung cancer mortality data were obtained from the Global Burden of Disease mortality database. The American Cancer Society Cancer Prevention Study, phase 11 (CPS-II) with follow up for the years 1982 to 1988 was the reference population. For the global application of the method, never-smoker lung cancer mortality rates were chosen based on the estimated use of coal for household energy in each region. Results: Men in industrialised countries of Europe, North America, and the Western Pacific had the largest accumulated hazards of smoking. Young and middle age males in many regions of the developing world also had large smoking risks. The accumulated hazards of smoking for women were highest in North America followed by Europe. Conclusions: In the absence of detailed data on smoking prevalence and history, lung cancer mortality provides a robust indicator of the accumulated hazards of smoking. These hazards in developing countries are currently more concentrated among young and middle aged males.

An approach to health and safety in E.U. forestry operations – Hazards and preventive measures

Forestry in general and logging in particular continue to be among the three most hazardous sectors in European countries. The aim of this article is to characterize health and safety problems and solutions in E.U. forestry operations, and particularly in Portuguese operations. Forest types, production, employment and ownership are used to characterize the forest sector. Forestry accidents and health problems data are mentioned. Typical hazards associated to the nature of logging operations are systematized. Preventive measures, focused on a wide spectrum of measures, making safety considerations an integral feature of all operational activities from planning to organization to execution and supervision of work are emphasized in this article.

Casualties distribution in human and natural hazards

Catastrophic events, such as wars and terrorist attacks, big tornadoes and hurricanes, huge earthquakes, tsunamis, floods, and landslides, are always accompanied by a large number of casualties. The size distribution of these casualties have separately been shown to follow approximate power law (PL) distributions. In this paper, we analyze the number of victims of catastrophic phenomena, in particular, terrorism, and find double PL behavior. This means that the data set is better approximated by two PLs instead of one. We have plotted the two PL parameters corresponding to all terrorist events occurred in every year, from 1980 to 2010. We observe an interesting pattern in the chart, where the lines, that connect each pair of points defining the double PLs, are roughly aligned to each other.

BACTERIOLOGICAL HAZARDS AND RISKS ASSOCIATED WITH SEAFOOD CONSUMPTION IN BRAZIL

SUMMARY The present study is a review of data available in Brazil on bacterial diseases transmitted through the consumption of seafood and related products. Data are presented regarding outbreaks and cases of disease and laboratory findings associated with pathogens in seafood and related products, and methods for prevention and control are described.

Hepatitis B virus infection in a population exposed to occupational hazards: firefighters of a metropolitan region in central Brazil

INTRODUCTION: By the nature of their activities, firefighters are exposed to a high risk of contracting hepatitis B virus (HBV) as most of the Fire Brigade occurrences in Campo Grande, State of Mato Grosso do Sul (MS), Brazil, are related to the rescue of victims of traffic accidents and the transportation of clinical and psychiatric emergencies. The aim of this study was to investigate the seroepidemiological profile of HBV infection in firefighters from the City of Campo Grande, central Brazil. METHODS: The research involved 308 firefighters. After giving written consent, they were interviewed and blood was collected for the detection of HBsAg, anti-HBs and total anti-HBc of enzyme-linked immunosorbent assays (ELISA). RESULTS: The participants had an average of 36.4 years of age (SD ± 6.5), being 89.9% male. Blood tests revealed 6.5% of seropositivity for hepatitis B (HB) infection (n=20), and 1% for HbsAg. Isolated anti-HBs markers, indicative of vaccine immunity, were found in 66.9% of the participants and 28.2% were susceptible to infection. With regard to risk factors for HB infection, multivariate regression analysis showed a statistically significant association with length of service; and prevalence was higher in individuals with over 20 years of service. CONCLUSIONS: The prevalence of HB found among the firefighters was low and length of time in the profession was found to be a risk factor. Non-occupational risk factors did not influence the occurrence of HB infection in the population studied.

Testing for Proportional Hazards with Unrestricted Univariate Unobserved Heterogeneity

We develop tests of the proportional hazards assumption, with respect to a continuous covariate, in the presence of unobserved heterogeneity with unknown distribution at the individual observation level. The proposed tests are specially powerful against ordered alternatives useful for modeling non-proportional hazards situations. By contrast to the case when the heterogeneity distribution is known up to …nite dimensional parameters, the null hypothesis for the current problem is similar to a test for absence of covariate dependence. However, the two testing problems di¤er in the nature of relevant alternative hypotheses. We develop tests for both the problems against ordered alternatives. Small sample performance and an application to real data highlight the usefulness of the framework and methodology.

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale: some case studies

Every year, debris flows cause huge damage in mountainous areas. Due to population pressure in hazardous zones, the socio-economic impact is much higher than in the past. Therefore, the development of indicative susceptibility hazard maps is of primary importance, particularly in developing countries. However, the complexity of the phenomenon and the variability of local controlling factors limit the use of processbased models for a first assessment. A debris flow model has been developed for regional susceptibility assessments using digital elevation model (DEM) with a GIS-based approach.. The automatic identification of source areas and the estimation of debris flow spreading, based on GIS tools, provide a substantial basis for a preliminary susceptibility assessment at a regional scale. One of the main advantages of this model is its workability. In fact, everything is open to the user, from the data choice to the selection of the algorithms and their parameters. The Flow-R model was tested in three different contexts: two in Switzerland and one in Pakistan, for indicative susceptibility hazard mapping. It was shown that the quality of the DEM is the most important parameter to obtain reliable results for propagation, but also to identify the potential debris flows sources.

Invisible work, unseen hazards: the health of women immigrant household service workers in Spain

Backgroud: Household service work has been largely absent from occupational health studies. We examine the occupational hazards and health effects identified by immigrant women household service workers. Methods: Exploratory, descriptive study of 46 documented and undocumented immigrant women in household services in Spain, using a phenomenological approach. Data were collected between September 2006 and May 2007 through focus groups and semi-structured individual interviews. Data were separated for analysis by documentation status and sorted using a mixed-generation process. In a second phase of analysis, data on psychosocial hazards were organized using the Copenhagen Psychosocial Questionnaire as a guide. Results: Informants reported a number of environmental, ergonomic and psychosocial hazards and corresponding health effects. Psychosocial hazards were especially strongly present in data. Data on reported hazards were similar by documentation status and varied by several emerging categories: whether participants were primarily cleaners or carers and whether they lived in or outside of the homes of their employers. Documentation status was relevant in terms of empowerment and bargaining, but did not appear to influence work tasks or exposure to hazards directly. Conclusions:Female immigrant household service workers are exposed to a variety of health hazards that could be acted upon by improved legislation, enforcement, and preventive workplace measures, which are discussed.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

Monitoring natural hazards

Few subjects have caught the attention of the entire world as much as those dealing with natural hazards. The first decade of this new millennium provides a litany of tragic examples of various hazards that turned into disasters affecting millions of individuals around the globe. The human losses (some 225,000 people) associated with the 2004 Indian Ocean earthquake and tsunami, the economic costs (approximately 200 billion USD) of the 2011 Tohoku Japan earthquake, tsunami and reactor event, and the collective social impacts of human tragedies experienced during Hurricane Katrina in 2005 all provide repetitive reminders that we humans are temporary guests occupying a very active and angry planet. Any examples may have been cited here to stress the point that natural events on Earth may, and often do, lead to disasters and catastrophes when humans place themselves into situations of high risk. Few subjects share the true interdisciplinary dependency that characterizes the field of natural hazards. From geology and geophysics to engineering and emergency response to social psychology and economics, the study of natural hazards draws input from an impressive suite of unique and previously independent specializations. Natural hazards provide a common platform to reduce disciplinary boundaries and facilitate a beneficial synergy in the provision of timely and useful information and action on this critical subject matter. As social norms change regarding the concept of acceptable risk and human migration leads to an explosion in the number of megacities, coastal over-crowding and unmanaged habitation in precarious environments such as mountainous slopes, the vulnerability of people and their susceptibility to natural hazards increases dramatically. Coupled with the concerns of changing climates, escalating recovery costs, a growing divergence between more developed and less developed countries, the subject of natural hazards remains on the forefront of issues that affect all people, nations, and environments all the time.This treatise provides a compendium of critical, timely and very detailed information and essential facts regarding the basic attributes of natural hazards and concomitant disasters. The Encyclopedia of Natural Hazards effectively captures and integrates contributions from an international portfolio of almost 300 specialists whose range of expertise addresses over 330 topics pertinent to the field of natural hazards. Disciplinary barriers are overcome in this comprehensive treatment of the subject matter. Clear illustrations and numerous color images enhance the primary aim to communicate and educate. The inclusion of a series of unique ?classic case study? events interspersed throughout the volume provides tangible examples linking concepts, issues, outcomes and solutions. These case studies illustrate different but notable recent, historic and prehistoric events that have shaped the world as we now know it. They provide excellent focal points linking the remaining terms in the volume to the primary field of study. This Encyclopedia of Natural Hazards will remain a standard reference of choice for many years.

Fact Sheet: Hazards Materials Accidents, 2009

A hazardous materials accident can occur anywhere. Communities located near chemical manufacturing plants are particularly at risk. However, hazardous materials are transported on our roadways, railways and waterways daily, so any area is considered vulnerable to an accident.