Application of a QMRA Framework to Inform Selection of Drinking Water Interventions in the Developing Context

The aim of this study was to develop a modified quantitative microbial risk assessment (QMRA) framework that could be applied as a decision support tool to choose between alternative drinking water interventions in the developing context. The impact of different household water treatment (HWT) interventions on the overall incidence of diarrheal disease and disability adjusted life years (DALYs) was estimated, without relying on source water pathogen concentration as the starting point for the analysis. A framework was developed and a software tool constructed and then implemented for an illustrative case study for Nepal based on published scientific data. Coagulation combined with free chlorine disinfection provided the greatest estimated health gains in the short term; however, when long‐term compliance was incorporated into the calculations, the preferred intervention was porous ceramic filtration. The model demonstrates how the QMRA framework can be used to integrate evidence from different studies to inform management decisions, and in particular to prioritize the next best intervention with respect to estimated reduction in diarrheal incidence. This study only considered HWT interventions; it is recognized that a systematic consideration of sanitation, recreation, and drinking water pathways is important for effective management of waterborne transmission of pathogens, and the approach could be expanded to consider the broader water‐related context.     

Trauma and health risk behaviors in people with severe mental illness

The current study tests the association between a composite measure of unsafe sex and sharing syringes for drug use with six of the more common lifetime traumatic/stressful events in 421 community mental health clients with severe mental illness (SMI) while controlling for psychiatric symptoms and related problems. A small but significant proportion of respondents said they had injected drugs with a shared needle in their lifetime (30, 7.2%), and a much larger proportion of respondents had engaged in unprotected sex (165, 39.2%). Unprotected sex and needle sharing were significantly correlated (Spearman’s rho = .20, p < .01). Frequency of lifetime traumatic events that occurred at least once was reported by one third to three quarters of clients depending on type of trauma. Regression analysis revealed that substance abuse and lifetime homelessness were significantly correlated with health risk behaviors. Practitioners need to be continuously vigilant to comorbid substance use and the housing needs of people with SMI. Limitations of the study include its cross-sectional design.     

Why Frequency is Not Well Defined for Engineering Systems with Nonexponential Failure Times

Dr. Yellman proposes to define frequency as “a time‐rate of events of a specified type over a particular time interval.” We review why no definition of frequency, including this one, can satisfy both of two conditions: (1) the definition should agree with the ordinary meaning of frequency, such as that less frequent events are less likely to occur than more frequent events, over any particular time interval for which the frequencies of both are defined; and (2) the definition should be applicable not only to exponentially distributed times between (or until) events, but also to some nonexponential (e.g., uniformly distributed) times. We make the simple point that no definition can satisfy (1) and (2) by showing that any definition that determines which of any two uniformly distributed times has the higher “frequency” (or that determines that they have the same “frequency,” if neither is higher) must assign a higher frequency number to the distribution with the lower probability of occurrence over some time intervals. Dr. Yellman's proposed phrase, “time‐rate of events … over a particular time interval” is profoundly ambiguous in such cases, as the instantaneous failure rates vary over an infinitely wide range (e.g., from one to infinity), making it unclear which value is denoted by the phrase “time‐rate of events.”     

Quantifying the Establishment Likelihood of Invasive Alien Species Introductions Through Ports with Application to Honeybees in Australia

The cost of an uncontrolled incursion of invasive alien species (IAS) arising from undetected entry through ports can be substantial, and knowledge of port‐specific risks is needed to help allocate limited surveillance resources. Quantifying the establishment likelihood of such an incursion requires quantifying the ability of a species to enter, establish, and spread. Estimation of the approach rate of IAS into ports provides a measure of likelihood of entry. Data on the approach rate of IAS are typically sparse, and the combinations of risk factors relating to country of origin and port of arrival diverse. This presents challenges to making formal statistical inference on establishment likelihood. Here we demonstrate how these challenges can be overcome with judicious use of mixed‐effects models when estimating the incursion likelihood into Australia of the European (Apis mellifera) and Asian (A. cerana) honeybees, along with the invasive parasites of biosecurity concern they host (e.g., Varroa destructor). Our results demonstrate how skewed the establishment likelihood is, with one‐tenth of the ports accounting for 80% or more of the likelihood for both species. These results have been utilized by biosecurity agencies in the allocation of resources to the surveillance of maritime ports.     

Identifying Changing Aviation Threat Environments Within an Adaptive Homeland Security Advisory System

A critical component of aviation security consists of screening passengers and baggage to protect airports and aircraft from terrorist threats. Advancements in screening device technology have increased the ability to detect these threats; however, specifying the operational configurations of these devices in response to changes in the threat environment can become difficult. This article proposes to use Fisher information as a statistical measure for detecting changes in the threat environment. The perceived risk of passengers, according to prescreening information and behavior analysis, is analyzed as the passengers sequentially enter the security checkpoint. The alarm responses from the devices used to detect threats are also analyzed to monitor significant changes in the frequency of threat items uncovered. The key results are that this information‐based measure can be used within the Homeland Security Advisory System to indicate changes in threat conditions in real time, and provide the flexibility of security screening detection devices to responsively and automatically adapt operational configurations to these changing threat conditions.     

The duty to care and the need to split

This paper arises out of psychoanalytically oriented consultancy to teams of staff in the helping professions where there is a statutory 'duty to care'. It takes as its premise the seemingly paradoxical hypothesis that workers may need to split off part of their emotional experience in order to preserve their own mental health and provide reliable services to their clients. I argue that while a professional 'duty to care' requires us to be emotionally 'in touch', the demands of our clients together with the demands of the institutional response to the 'duty to care' cause us to split off parts of our awareness. I also argue that provided the splitting does not become extreme we are doing no more or less than the rest of society. In other words, there is a degree of 'normal splitting' which numbs our awareness of danger and destructiveness and seeks to protect us from too much anxiety and pain. Yet if professional workers are charged with the responsibility of assessing risk and acting accordingly for the protection of all concerned they need ways of being 'in touch' (re-integrating the splits) for some or enough of the time. Finally, I will describe ways of being 'in touch', illustrating the difficulty and the pain of re-integrating the splits and some of the insights that can arise out of this work with examples from my consultancy work.     

Bayesian analysis of multivariate stochastic volatility with skew return distribution

Multivariate stochastic volatility models with skew distributions are proposed. Exploiting Cholesky stochastic volatility modeling, univariate stochastic volatility processes with leverage effect and generalized hyperbolic skew t-distributions are embedded to multivariate analysis with time-varying correlations. Bayesian modeling allows this approach to provide parsimonious skew structure and to easily scale up for high-dimensional problem. Analyses of daily stock returns are illustrated. Empirical results show that the time-varying correlations and the sparse skew structure contribute to improved prediction performance and Value-at-Risk forecasts.     

An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory

Land subsidence risk assessment (LSRA) is a multi‐attribute decision analysis (MADA) problem and is often characterized by both quantitative and qualitative attributes with various types of uncertainty. Therefore, the problem needs to be modeled and analyzed using methods that can handle uncertainty. In this article, we propose an integrated assessment model based on the evidential reasoning (ER) algorithm and fuzzy set theory. The assessment model is structured as a hierarchical framework that regards land subsidence risk as a composite of two key factors: hazard and vulnerability. These factors can be described by a set of basic indicators defined by assessment grades with attributes for transforming both numerical data and subjective judgments into a belief structure. The factor‐level attributes of hazard and vulnerability are combined using the ER algorithm, which is based on the information from a belief structure calculated by the Dempster‐Shafer (D‐S) theory, and a distributed fuzzy belief structure calculated by fuzzy set theory. The results from the combined algorithms yield distributed assessment grade matrices. The application of the model to the Xixi‐Chengnan area, China, illustrates its usefulness and validity for LSRA. The model utilizes a combination of all types of evidence, including all assessment information—quantitative or qualitative, complete or incomplete, and precise or imprecise—to provide assessment grades that define risk assessment on the basis of hazard and vulnerability. The results will enable risk managers to apply different risk prevention measures and mitigation planning based on the calculated risk states.     

中国石油股份实施ERP的思考——基于中国石油华北天然气销售公司的实践

自2007年底开始,中石油在地区公司推行ERP,华北天然气销售公司从2008年5月开始组织ERP项目建设,2008年11月开始实施。华北天然气销售公司在实施ERP过程中对传统会计务实理念产生了冲击,对公司的会计基础工作也产生了影响。从长期看,实施ERP与FMIS融合系统能整合中石油的技术平台,提高企业的整体竞争力。因此,中石油在ERP的实施中,应改变传统会计观念,加强基础数据的维护,保证基础数据的准确性和实效性,完善ERP系统的配套管理机制和运行机制,建立配套的内部控制机制,做好风险管理工作。     

Too Scared or Too Capable? Why Do College Students Stay Away from the H1N1 Vaccine?

Although college students were among the populations that had the highest frequency of infection for H1N1 influenza, only 8% of them received H1N1 vaccine this past flu season nationwide. During the peak of this pandemic, information about H1N1 vaccine was widely available. However, knowledge test and behavioral data indicated that most college students were not equipped with basic facts about H1N1 and the H1N1 vaccine. To investigate socio‐psychological factors that might have deterred this high‐risk population from learning about and getting the H1N1 vaccine, this study tested the utility of a risk information seeking model in addressing this health communication problem. Data collected from an online survey of 371 college students showed that respondents seemed to overestimate how much they knew about the vaccine. Risk information seeking, however, positively influenced their intentions to get the vaccine. Results suggested that to communicate effectively to this population, it is important to emphasize the difference between perceived knowledge and actual knowledge, monitor emotional responses to potential risks, and promote getting flu vaccination as a socially desirable behavior.