Scientific data and theories for salmonellosis dose–response assessment

An “expansive” risk assessment approach is illustrated, characterizing dose–response relationships for salmonellosis in light of the full body of evidence for human and murine superorganisms. Risk assessments often require analysis of costs and benefits for supporting public health decisions. Decision-makers and the public need to understand uncertainty in such analyses for two reasons. Uncertainty analyses provide a range of possibilities within a framework of present scientific knowledge, thus helping to avoid undesirable consequences associated with the selected policies. And, it encourages the risk assessors to scrutinize all available data and models, thus helping avoid subjective or systematic errors. Without the full analysis of uncertainty, decisions could be biased by judgments based solely on default assumptions, beliefs, and statistical analyses of selected correlative data. Alternative data and theories that incorporate variability and heterogeneity for the human and murine superorganisms, particularly colonization resistance, are emerging as major influences for microbial risk assessment. Salmonellosis risk assessments are often based on conservative default models derived from selected sets of outbreak data that overestimate illness. Consequently, the full extent of uncertainty of estimates of annual number of illnesses is not incorporated in risk assessments and the presently used models may be incorrect.     

A quantitative analysis on the effects of critical factors limiting the effectiveness of species conservation in future time

The effectiveness of conservation plans depends on environmental, ecological, and socioeconomic factors. Global change makes conservation decisions even more challenging. Among others, the components of most concern in modern‐day conservation assessments are as follows: the magnitude of climate and land‐use changes; species dispersal abilities; competition with harmful socioeconomic activities for land use; the number of threatened species to consider; and, relatedly, the available budget to act. Here, we provide a unified framework that quantifies the relative effects of those factors on conservation. We conducted an area‐scheduling work plan in order to identify sets of areas along time in which the persistence expectancies of species are optimized. The approach was illustrated using data of potential distribution of ten nonvolant mammal species in Iberia Peninsula from current time up to 2080. Analyses were conducted considering possible setups among the factors that are likely to critically impact conservation success: three climate/land‐use scenarios; four species’ dispersal kernel curves; six land‐use layer types; and two planning designs, in which assessments were made independently for each species, or joining all species in a single plan. We identified areas for an array of investments levels capable to circumvent the spatial conflicts with socioeconomic activities. The effect of each factor on the estimated species persistence scores was assessed using linear mixed models. Our results evidence that conservation success is highly reliant on the resources available to abate land‐use conflicts. Nonetheless, under the same investment levels, planning design and climate change were the factors that most shaped species persistence scores. The persistence of five species was especially affected by the sole effect of planning design and consequently, larger conservation investments may retard climatic debts. For three species, the negative effects of a changing climate and of multiple‐species planning designs added up, making these species especially at risk. Integrated assessments of the factors most likely to limit species persistence are pivotal to achieve effectiveness.     

Job scheduling and management of wearing tools with stochastic tool lifetimes

The problem of scheduling jobs using wearing tools is studied. Tool wearing is assumed to be stochastic and the jobs are processed in one machining centre provided with a limited capacity tool magazine. The aim is to minimize the expected average completion time of the jobs by choosing their processing order and tool management decisions wisely. All jobs are available at the beginning of the planning period. This kind of situation is met in production planning of CNC-machines. Previous studies concerning this problem have either assumed deterministic wearing for the tools or omitted the wearing completely. In our formulation of the problem, tool wearing is stochastic and the problem becomes very hard to solve analytically. A heuristic based on genetic algorithms is therefore given for the joint problem of job scheduling and tool management. The algorithm searches the most beneficial job sequence when the tool management decisions are made by a removal rule taking into account the future planned usage of the tools. The cost of each job sequence is evaluated by simulating the job processing. Empirical tests with heuristics indicate that by taking the stochastic information into account, one can reduce the average job processing time considerably.     

The Concept of Data Utility in Health Risk Assessment: A Multi-Disciplinary Perspective

Human and ecological health risk assessments and the decisions that stem from them require the acquisition and analysis of data. In agencies that are responsible for health risk decision-making, data (and/or opinions/judgments) are obtained from sources such as scientific literature, analytical and process measurements, expert elicitation, inspection findings, and public and private research institutions. Although the particulars of conducting health risk assessments of given disciplines may be dramatically different, a common concern is the subjective nature of judging data utility. Often risk assessors are limited to available data that may not be completely appropriate to address the question being asked. Data utility refers to the ability of available data to support a risk-based decision for a particular risk assessment. This article familiarizes the audience with the concept of data utility and is intended to raise the awareness of data collectors (e.g., researchers), risk assessors, and risk managers to data utility issues in health risk assessments so data collection and use will be improved. In order to emphasize the cross-cutting nature of data utility, the discussion has not been organized into a classical partitioning of risk assessment concerns as being either human health- or ecological health-oriented, as per the U.S. Environmental Protection Agency's Superfund Program.     

Risk Assessment: Replacing Default Options with Specific Science

The history of approaches to evaluating the hazards and risks of chemicals is briefly reviewed. The role of default options (generic approaches based on general knowledge in the absence of specific knowledge to the contrary) is discussed as a part of the risk assessment paradigm advanced by the National Academy of Science/National Research Council in 1983 and 1994. Examples are given of the impact of acquiring specific science to replace default options. An argument is made for developing specific science that would reduce uncertainty in risk assessments. Research on specific science would be guided by identified sources of uncertainty in the risk assessment process. The importance of using a research strategy that builds on human data is emphasized for validating new molecular and cellular biological assessment methods. The paper closes with a discussion of the tension between a hazard-based approach versus quantitative risk assessment in guiding risk management decisions. The former requires limited data, is qualitative, and easy to communicate, while the latter requires substantial data and is difficult to communicate. However, quantitative risk assessment provides a more rational basis for decisions on the allocation of both public and private resources for actions that will effectively minimize overall health risks to the public.     

Low Penetrance Germline Genetic Testing: Role for Risk Stratification in Prostate Cancer Screening and Examples From Clinical Practice

Broad-based prostate-specific antigen (PSA) screening has saved lives but at a substantial human and financial cost. One way of mitigating this harm, while maintaining and possibly improving the benefit, is by focusing screening efforts on men at higher risk. With age, race, and family history as the only risk factors, many men lack any reliable data to inform their prostate cancer (PCa) screening decisions. Complexities including history of previous negative biopsies, interpretation of negative and/or equivocal mpMRI findings, and patient comorbidities further compound the already complicated decisions surrounding PCa screening and early detection. The authors present cases that provide real-world examples of how a single nucleotide polymorphism-based test can provide patients and providers with personalized PCa risk assessments and allow for development of improved risk-stratified screening regimens.     

Augmenting intraoperative ultrasound with preoperative magnetic resonance planning models for percutaneous renal access

ABSTRACT: BACKGROUND: Ultrasound (US) is a commonly-used intraoperative imaging modality for guiding percutaneous renal access (PRA). However, the anatomy identification and target localization abilities of the US imaging are limited. This paper evaluates the feasibility and efficiency of a proposed image-guided PRA by augmenting the intraoperative US with preoperative magnetic resonance (MR) planning models. METHODS: First, a preoperative surgical planning approach is presented to define an optimal needle trajectory using MR volume data. Then, a MR to US registration is proposed to transfer the preoperative planning into the intraoperative context. The proposed registration makes use of orthogonal US slices to avoid local minima while reduce processing time. During the registration, a respiratory gating method is used to minimize the impact of kidney deformation. By augmenting the intraoperative US with preoperative MR models and a virtual needle, a visual guidance is provided to guarantee the correct execution of the surgical planning. The accuracy, robustness and processing time of the proposed registration were evaluated by four urologists on human data from four volunteers. Furthermore, the PRA experiments were performed by the same four urologists on a kidney phantom. The puncture accuracy in terms of the needle-target distance was measured, while the perceptual quality in using the proposed image guidance was evaluated according to custom scoring method. RESULTS: The mean registration accuracy in terms of the root mean square (RMS) target registration error (TRE) is 3.53mm. The RMA distance from the registered feature points to their average is 0.81mm. The mean operating time of the registration is 6'4". In the phantom evaluation, the mean needle-target distance is 2.08mm for the left lesion and 1.85mm for the right one. The mean duration for all phantom PRA tests was 4'26". According to the custom scoring method, the mean scores of the Intervention Improvement, Workflow Impact, and Clinical Relevance were 4.0, 3.3 and 3.9 respectively. CONCLUSIONS: The presented image guidance is feasible and promising for PRA procedure. With careful setup it can be efficient for overcoming the limitation of current US-guided PRA.     

Tailoring information provision and consent processes to research contexts: the value of rapid assessments

Guidance requires that consent processes for research be appropriately tailored to their cultural context. This paper discusses the use of rapid assessments to identify cultural and ethical issues arising when explaining research in studies in The Gambia and Ethiopia. The assessments provided insights into appropriate ways of providing information to minimize the risk of stigmatizing vulnerable research populations; research participants' views about the most important information to provide about research and their understandings of research; and perceived constraints upon reaching voluntary decisions about participation. These insights demonstrate that rapid assessments are a relatively quick and inexpensive intervention that can provide valuable information to assist in the tailoring of information provision and consent processes to research context while maintaining and enhancing participants' fundamental protections.     

The assessment of mangrove biomass and carbon in West Africa: a spatially explicit analytical framework

Mangrove forests are highly productive and have large carbon sinks while also providing numerous goods and ecosystem services. However, effective management and conservation of the mangrove forests are often dependent on spatially explicit assessments of the resource. Given the remote and highly dispersed nature of mangroves, estimation of biomass and carbon in mangroves through routine field-based inventories represents a challenging task which is impractical for large-scale planning and assessment. Alternative approaches based on geospatial technologies are needed to support this estimation in large areas. However, spatial data processing and analysis approaches used in this estimation of mangrove biomass and carbon have not been adequately investigated. In this study, we present a spatially explicit analytical framework that integrate remotely sensed data and spatial analyses approaches to support the estimation of mangrove biomass and carbon stock and their spatial patterns in West Africa. Forest canopy height derived from SRTM and ICESat/GLAS data was used to estimate mangrove biomass and carbon in nine West African countries. We developed a geospatial software toolkit that implemented the proposed framework. The spatial analysis framework and software toolkit provide solid support for the estimation and relative comparisons of mangrove-related metrics. While the mean canopy height of mangroves in our study area is 10.2 m, the total biomass and carbon were estimated as 272.56 and 136.28 Tg. Nigeria has the highest total mangrove biomass and carbon in the nine countries, but Cameroon is the country with the largest mean biomass and carbon density. The resulting spatially explicit distributions of mangrove biomass and carbon hold great potential in guiding the strategic planning of large-scale field-based assessment of mangrove forests. This study demonstrates the utility of online geospatial data and spatial analysis as a feasible solution for estimating the distribution of mangrove biomass and carbon at larger or smaller scales.     

An international database for pesticide risk assessments and management

Despite a changing world in terms of data sharing, availability, and transparency, there are still major resource issues associated with collating datasets that will satisfy the requirements of comprehensive pesticide risk assessments, especially those undertaken at a regional or national scale. In 1996, a long-term project was initiated to begin collating and formatting pesticide data to eventually create a free-to-all repository of data that would provide a comprehensive transparent, harmonized, and managed extensive dataset for all types of pesticide risk assessments. Over the last 20 years, this database has been keeping pace with improving risk assessments, their associated data requirements, and the needs and expectations of database end users. In 2007, the Pesticide Properties DataBase (PPDB) was launched as a free-to-access website. Currently, the PPDB holds data for almost 2300 pesticide active substances and over 700 metabolites. For each substance around 300 parameters are stored, covering human health, environmental quality, and biodiversity risk assessments. With the approach of the twentieth anniversary of the database, this article seeks to elucidate the current data model, data sources, its validation, and quality control processes and describes a number of existing risk assessment applications that depend upon it.     

Weather Regulates Location,Timing, and Intensity of Dengue Virus Transmission between Humans and Mosquitoes

BackgroundDengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather.Conclusions/SignificanceLocal duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning.     

Distributions Selected for Use in Probabilistic Human Health Risk Assessments in Oregon

In 1995, Oregon enacted amendments to its state Cleanup Law that emphasize risk-based remedial action decisions and allow a responsible party to conduct probabilistic human health risk assessments. This change required selection and/or development of probability density functions for exposure factors frequently used in human health risk assessments. Methods used to obtain distributions for body weight, soil, water, vegetable/fruit, fish, and animal product ingestion, soil adherence, daily inhalation rate, various event and exposure frequencies, and exposure duration are described. Primary data sources were U.S. Environmental Protection Agency guidance and peer-reviewed scientific literature. These distributions of exposure factors may be used, in conjunction with a probabilistic age- and gender-based model, to calculate prospective exposures and risks. A brief overview of this model, which handles temporal parameters (age, exposure frequency, exposure duration) in a manner substantially different from that typically used in deterministic assessments, is also provided. Oregon's development of an age/ gender-based exposure model, and its selection of exposure factor value distributions for that model, represents one of the first attempts to develop practical approaches to using probabilistic techniques in a hazardous waste regulatory program.     

Predation Risk Perception,Food Density and Conspecific Cues Shape Foraging Decisions in a Tropical Lizard

When foraging, animals can maximize their fitness if they are able to tailor their foraging decisions to current environmental conditions. When making foraging decisions, individuals need to assess the benefits of foraging while accounting for the potential risks of being captured by a predator. However, whether and how different factors interact to shape these decisions is not yet well understood, especially in individual foragers. Here we present a standardized set of manipulative field experiments in the form of foraging assays in the tropical lizard Anolis cristatellus in Puerto Rico. We presented male lizards with foraging opportunities to test how the presence of conspecifics, predation-risk perception, the abundance of food, and interactions among these factors determines the outcome of foraging decisions. In Experiment 1, anoles foraged faster when food was scarce and other conspecifics were present near the feeding tray, while they took longer to feed when food was abundant and when no conspecifics were present. These results suggest that foraging decisions in anoles are the result of a complex process in which individuals assess predation risk by using information from conspecific individuals while taking into account food abundance. In Experiment 2, a simulated increase in predation risk (i.e., distance to the feeding tray) confirmed the relevance of risk perception by showing that the use of available perches is strongly correlated with the latency to feed. We found Puerto Rican crested anoles integrate instantaneous ecological information about food abundance, conspecific activity and predation risk, and adjust their foraging behavior accordingly.     

Climate change vulnerability for species—Assessing the assessments

Climate change vulnerability assessments are commonly used to identify species at risk from global climate change, but the wide range of methodologies available makes it difficult for end users, such as conservation practitioners or policymakers, to decide which method to use as a basis for decision‐making. In this study, we evaluate whether different assessments consistently assign species to the same risk categories and whether any of the existing methodologies perform well at identifying climate‐threatened species. We compare the outputs of 12 climate change vulnerability assessment methodologies, using both real and simulated species, and validate the methods using historic data for British birds and butterflies (i.e. using historical data to assign risks and more recent data for validation). Our results show that the different vulnerability assessment methods are not consistent with one another; different risk categories are assigned for both the real and simulated sets of species. Validation of the different vulnerability assessments suggests that methods incorporating historic trend data into the assessment perform best at predicting distribution trends in subsequent time periods. This study demonstrates that climate change vulnerability assessments should not be used interchangeably due to the poor overall agreement between methods when considering the same species. The results of our validation provide more support for the use of trend‐based rather than purely trait‐based approaches, although further validation will be required as data become available.     

A Cascading Auction Protocol as a Framework for Integrating Process Planning and Heterarchical Shop Floor Control

A new contract net-style auction protocol is proposed as a framework for integrating process planning and shop floor control in heterarchical manufacturing systems. Process planning is partitioned into on-line and off-line activities; off-line process planning decisions are represented in a graph format and used as input for on-line process planning activities performed by machine controllers. Triggered by the opening round of an auction, the final on-line stages of process planning are dovetailed with the resource allocation process in the shop floor control system. The auction process allows final process planning decisions to be based on timely information, relying on the distribution of static process planning information rather than the distribution of a model of dynamic shop floor status and allowing a controller to identify all the primary and secondary resources and operations that must be provided for the incremental processing of a part.     

The influence of planning unit characteristics on the efficiency and spatial pattern of systematic conservation planning assessments

Systematic conservation planning is a widely used approach for designing protected area systems and ecological networks. This generally involves dividing the planning region into a series of planning units and using computer software to select portfolios of these units that meet specified conservation targets whilst minimising conservation costs. Previous research has shown that changing the size and shape of these planning units can alter the apparent spatial characteristics of the underlying data and thus influence conservation assessment results. However, this may be less problematic when using newer software that can account for additional constraints based on portfolio costs and fragmentation levels. Here we investigate these issues using a dataset from southern Africa and measure the extent to which changing planning unit shape, size and baseline affects the results of conservation planning assessments. We show that using hexagonal planning units instead of squares produces more efficient and less fragmented portfolios and that using larger planning units produces portfolios that are less efficient but more likely to identify the same priority areas. We also show that using real-world constraints in the analysis, based on reducing socio-economic costs and minimising fragmentation levels, reduces the influence of planning unit characteristics on the results and so argue that future studies should adopt a similar approach when investigating factors that influence conservation assessments.     

Predicting the likely response of data‐poor ecosystems to climate change using space‐for‐time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data‐poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data‐poor ecosystems based on a space‐for‐time substitution, using distant, well‐studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate‐ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains – to investigate ecological response to climate change – allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long‐term predictions will be of significant value to natural resource practitioners attempting to manage data‐poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.     

A complex method of equipment replacement planning. An advanced plan for the replacement of medical equipment

This complex method of equipment replacement planning is a methodology; it is a means to an end, a process that focuses on equipment most in need of replacement, rather than the end itself. It uses data available from the maintenance management database, and attempts to quantify those subjective items important [figure: see text] in making equipment replacement decisions. Like the simple method of the last issue, it is a starting point--albeit an advanced starting point--which the user can modify to fit their particular organization, but the complex method leaves room for expansion. It is based on sound logic, documented facts, and is fully defensible during the decision-making process and will serve your organization well as provide a structure for your equipment replacement planning decisions.     

Laboratory studies on surface sampling of Bacillus anthracis contamination: summary,gaps and recommendations

This article summarizes previous laboratory studies to characterize the performance of methods for collecting, storing/transporting, processing and analysing samples from surfaces contaminated by Bacillus anthracis or related surrogates. The focus is on plate culture and count estimates of surface contamination for swab, wipe and vacuum samples of porous and nonporous surfaces. Summaries of the previous studies and their results were assessed to identify gaps in information needed as inputs to calculate key parameters critical to risk management in biothreat incidents. One key parameter is the number of samples needed to make characterization or clearance decisions with specified statistical confidence. Other key parameters include the ability to calculate, following contamination incidents, the (i) estimates of B. anthracis contamination, as well as the bias and uncertainties in the estimates and (ii) confidence in characterization and clearance decisions for contaminated or decontaminated buildings. Gaps in knowledge and understanding identified during the summary of the studies are discussed. Additional work is needed to quantify (i) the false‐negative rates of surface‐sampling methods with lower concentrations on various surfaces and (ii) the effects on performance characteristics of: aerosol vs liquid deposition of spores, using surrogates instead of B. anthracis, real‐world vs laboratory conditions and storage and transportation conditions. Recommendations are given for future evaluations of data from existing studies and possible new studies.