TU-EF-204-09: A Preliminary Method of Risk-Informed Optimization of Tube Current Modulation for Dose Reduction in CT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Y; Liu, B; Kalra, M

Purpose: X-rays from CT scans can increase cancer risk to patients. Lifetime Attributable Risk of Cancer Incidence for adult patients has been investigated and shown to decrease as patient age. However, a new risk model shows an increasing risk trend for several radiosensitive organs for middle age patients. This study investigates the feasibility of a general method for optimizing tube current modulation (TCM) functions to minimize risk by reducing radiation dose to radiosensitive organs of patients. Methods: Organ-based TCM has been investigated in literature for eye lens dose and breast dose. Adopting the concept in organ-based TCM, this study seeksmore » to find an optimized tube current for minimal total risk to breasts and lungs by reducing dose to these organs. The contributions of each CT view to organ dose are determined through simulations of CT scan view-by-view using a GPU-based fast Monte Carlo code, ARCHER. A Linear Programming problem is established for tube current optimization, with Monte Carlo results as weighting factors at each view. A pre-determined dose is used as upper dose boundary, and tube current of each view is optimized to minimize the total risk. Results: An optimized tube current is found to minimize the total risk of lungs and breasts: compared to fixed current, the risk is reduced by 13%, with breast dose reduced by 38% and lung dose reduced by 7%. The average tube current is maintained during optimization to maintain image quality. In addition, dose to other organs in chest region is slightly affected, with relative change in dose smaller than 10%. Conclusion: Optimized tube current plans can be generated to minimize cancer risk to lungs and breasts while maintaining image quality. In the future, various risk models and greater number of projections per rotation will be simulated on phantoms of different gender and age. National Institutes of Health R01EB015478.« less

Making Better Re/Insurance Underwriting and Capital Management Decisions with Public-Private-Academic Partnerships

NASA Astrophysics Data System (ADS)

Michel, G.; Gunasekera, R.; Werner, A.; Galy, H.

2012-04-01

Similar to 2001, 2004, and 2005, 2011 was another year of unexpected international catastrophe events, in which insured losses were more than twice the expected long-term annual average catastrophe losses of USD 30 to 40bn. Key catastrophe events that significantly contributed these losses included the Mw 9.0 Great Tohoku earthquake and tsunami, the Jan. 2011 floods in Queensland, the October 2011 floods in Thailand, the Mw 6.1 Christchurch earthquake and Convective system (Tornado) in United States. However, despite considerable progress in catastrophe modelling, the advent of global catastrophe models, increasing risk model coverage and skill in the detailed modelling, the above mentioned events were not satisfactorily modelled by the current mainstream Re/Insurance catastrophe models. This presentation therefore address problems in models and incomplete understanding identified from recent catastrophic events by considering: i) the current modelling environment, and ii) how the current processes could be improved via: a) the understanding of risk within science networks such as the Willis Research Network, and b) the integration of risk model results from available insurance catastrophe models and tools. This presentation aims to highlight the needed improvements in decision making and market practices, thereby advancing the current management of risk in the Re/Insurance industry. This also increases the need for better integration of Public-Private-Academic partnerships and tools to provide better estimates of not only financial loss but also humanitarian and infrastructural losses as well.

Risk transfer modeling among hierarchically associated stakeholders in development of space systems

NASA Astrophysics Data System (ADS)

Henkle, Thomas Grove, III

Research develops an empirically derived cardinal model that prescribes handling and transfer of risks between organizations with hierarchical relationships. Descriptions of mission risk events, risk attitudes, and conditions for risk transfer are determined for client and underwriting entities associated with acquisition, production, and deployment of space systems. The hypothesis anticipates that large client organizations should be able to assume larger dollar-value risks of a program in comparison to smaller organizations even though many current risk transfer arrangements via space insurance violate this hypothesis. A literature survey covers conventional and current risk assessment methods, current techniques used in the satellite industry for complex system development, cardinal risk modeling, and relevant aspects of utility theory. Data gathered from open literature on demonstrated launch vehicle and satellite in-orbit reliability, annual space insurance premiums and losses, and ground fatalities and range damage associated with satellite launch activities are presented. Empirically derived models are developed for risk attitudes of space system clients and third-party underwriters associated with satellite system development and deployment. Two application topics for risk transfer are examined: the client-underwriter relationship on assumption or transfer of risks associated with first-year mission success, and statutory risk transfer agreements between space insurance underwriters and the US government to promote growth in both commercial client and underwriting industries. Results indicate that client entities with wealth of at least an order of magnitude above satellite project costs should retain risks to first-year mission success despite present trends. Furthermore, large client entities such as the US government should never pursue risk transfer via insurance under previously demonstrated probabilities of mission success; potential savings may reasonably exceed multiple tens of $millions per space project. Additional results indicate that current US government statutory arrangements on risk sharing with underwriting entities appears reasonable with respect to stated objectives. This research combines aspects of multiple disciplines to include risk management, decision theory, utility theory, and systems architecting. It also demonstrates development of a more general theory on prescribing risk transfer criteria between distinct, but hierarchically associated entities involved in complex system development with applicability to a variety of technical domains.

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

Modeling approaches for characterizing and evaluating environmental exposure to engineered nanomaterials in support of risk-based decision making.

PubMed

Hendren, Christine Ogilvie; Lowry, Michael; Grieger, Khara D; Money, Eric S; Johnston, John M; Wiesner, Mark R; Beaulieu, Stephen M

2013-02-05

As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.

Risk Importance Measures in the Designand Operation of Nuclear Power Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vrbanic I.; Samanta P.; Basic, I

This monograph presents and discusses risk importance measures as quantified by the probabilistic risk assessment (PRA) models of nuclear power plants (NPPs) developed according to the current standards and practices. Usually, PRA tools calculate risk importance measures related to a single ?basic event? representing particular failure mode. This is, then, reflected in many current PRA applications. The monograph focuses on the concept of ?component-level? importance measures that take into account different failure modes of the component including common-cause failures (CCFs). In opening sections the roleof risk assessment in safety analysis of an NPP is introduced and discussion given of ?traditional?,more » mainly deterministic, design principles which have been established to assign a level of importance to a particular system, structure or component. This is followed by an overview of main risk importance measures for risk increase and risk decrease from current PRAs. Basic relations which exist among the measures are shown. Some of the current practical applications of risk importancemeasures from the field of NPP design, operation and regulation are discussed. The core of the monograph provides a discussion on theoreticalbackground and practical aspects of main risk importance measures at the level of ?component? as modeled in a PRA, starting from the simplest case, single basic event, and going toward more complexcases with multiple basic events and involvements in CCF groups. The intent is to express the component-level importance measures via theimportance measures and probabilities of the underlying single basic events, which are the inputs readily available from a PRA model andits results. Formulas are derived and discussed for some typical cases. The formulas and their results are demonstrated through some practicalexamples, done by means of a simplified PRA model developed in and run by RiskSpectrum? tool, which are presented in the appendices. The monograph concludes with discussion of limitations of the use of risk importance measures and a summary of component-level importance cases evaluated.« less

The evolution of global disaster risk assessments: from hazard to global change

NASA Astrophysics Data System (ADS)

Peduzzi, Pascal

2013-04-01

The perception of disaster risk as a dynamic process interlinked with global change is a fairly recent concept. It gradually emerged as an evolution from new scientific theories, currents of thinking and lessons learned from large disasters since the 1970s. The interest was further heighten, in the mid-1980s, by the Chernobyl nuclear accident and the discovery of the ozone layer hole, both bringing awareness that dangerous hazards can generate global impacts. The creation of the UN International Decade for Natural Disaster Reduction (IDNDR) and the publication of the first IPCC report in 1990 reinforced the interest for global risk assessment. First global risk models including hazard, exposure and vulnerability components were available since mid-2000s. Since then increased computation power and more refined datasets resolution, led to more numerous and sophisticated global risk models. This article presents a recent history of global disaster risk models, the current status of researches for the Global Assessment Report on Disaster Risk Reduction (GAR 2013) and future challenges and limitations for the development of next generation global disaster risk models.

Geographic exposure risk of variant Creutzfeldt-Jakob disease in US blood donors: a risk-ranking model to evaluate alternative donor-deferral policies.

PubMed

Yang, Hong; Huang, Yin; Gregori, Luisa; Asher, David M; Bui, Travis; Forshee, Richard A; Anderson, Steven A

2017-04-01

Variant Creutzfeldt-Jakob disease (vCJD) has been transmitted by blood transfusion (TTvCJD). The US Food and Drug Administration (FDA) recommends deferring blood donors who resided in or traveled to 30 European countries where they may have been exposed to bovine spongiform encephalopathy (BSE) through beef consumption. Those recommendations warrant re-evaluation, because new cases of BSE and vCJD have markedly abated. The FDA developed a risk-ranking model to calculate the geographic vCJD risk using country-specific case rates and person-years of exposure of US blood donors. We used the reported country vCJD case rates, when available, or imputed vCJD case rates from reported BSE and UK beef exports during the risk period. We estimated the risk reduction and donor loss should the deferral be restricted to a few high-risk countries. We also estimated additional risk reduction by leukocyte reduction (LR) of red blood cells (RBCs). The United Kingdom, Ireland, and France had the greatest vCJD risk, contributing approximately 95% of the total risk. The model estimated that deferring US donors who spent extended periods of time in these three countries, combined with currently voluntary LR (95% of RBC units), would reduce the vCJD risk by 89.3%, a reduction similar to that achieved under the current policy (89.8%). Limiting deferrals to exposure in these three countries would potentially allow donations from an additional 100,000 donors who are currently deferred. Our analysis suggests that a deferral option focusing on the three highest risk countries would achieve a level of blood safety similar to that achieved by the current policy. © 2016 AABB.

Development of a relative risk model for drinking water regulation and design recommendations for a peri urban region of Argentina.

PubMed

Rodriguez-Alvarez, María Soledad; Weir, Mark H; Pope, Joanna M; Seghezzo, Lucas; Rajal, Verónica B; Salusso, María Mónica; Moraña, Liliana B

2015-10-01

Argentina is a developing Latin American nation that has an aim of achieving the United Nations Millennium Development Goals for potable water supplies. Their current regulations however, limit the continued development of improved potable water quality and infrastructure from a microbiological viewpoint. This is since the current regulations are focused solely to pathogenic Eschericia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa) and fecal indicators. Regions of lower socioeconomic status such as peri-urban areas are particularly at risk due to lessened financial and political ability to influence their environmental quality and infrastructure needs. Therefore, a combined microbiological sampling, analysis and quantitative microbial risk assessment (QMRA) modeling effort were engaged for a peri-urban area of Salta Argentina. Drinking water samples from home taps were analyzed and a QMRA model was developed, results of which were compared against a general 1:10,000 risk level for lack of a current Argentinian standard. This QMRA model was able to demonstrate that the current regulations were being achieved for E. coli but were less than acceptable for P. aeruginosa in some instances. Appropriate health protections are far from acceptable for Giardia for almost all water sources. Untreated water sources were sampled and analyzed then QMRA modeled as well, since a significant number of the community (∼9%) still use them for potable water supplies. For untreated water E. coli risks were near 1:10,000, however, P. aeruginosa and Giardia risks failed to be acceptable in almost all instances. The QMRA model and microbiological analyses demonstrate the need for improved regulatory efforts for the peri-urban area along with improved investment in their water infrastructure. Copyright © 2015 Elsevier GmbH. All rights reserved.

The NASA Space Radiobiology Risk Assessment Project

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; Huff, Janice; Ponomarev, Artem; Patel, Zarana; Kim, Myung-Hee

The current first phase (2006-2011) has the three major goals of: 1) optimizing the conventional cancer risk models currently used based on the double-detriment life-table and radiation quality functions; 2) the integration of biophysical models of acute radiation syndromes; and 3) the development of new systems radiation biology models of cancer processes. The first-phase also includes continued uncertainty assessment of space radiation environmental models and transport codes, and relative biological effectiveness factors (RBE) based on flight data and NSRL results, respectively. The second phase of the (2012-2016) will: 1) develop biophysical models of central nervous system risks (CNS); 2) achieve comphrensive systems biology models of cancer processes using data from proton and heavy ion studies performed at NSRL; and 3) begin to identify computational models of biological countermeasures. Goals for the third phase (2017-2021) include: 1) the development of a systems biology model of cancer risks for operational use at NASA; 2) development of models of degenerative risks, 2) quantitative models of counter-measure impacts on cancer risks; and 3) indiviudal based risk assessments. Finally, we will support a decision point to continue NSRL research in support of NASA's exploration goals beyond 2021, and create an archival of NSRL research results for continued analysis. Details on near term goals, plans for a WEB based data resource of NSRL results, and a space radiation Wikepedia are described.

Decision analysis and risk models for land development affecting infrastructure systems.

PubMed

Thekdi, Shital A; Lambert, James H

2012-07-01

Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

Risk attitudes in a changing environment: An evolutionary model of the fourfold pattern of risk preferences.

PubMed

Mallpress, Dave E W; Fawcett, Tim W; Houston, Alasdair I; McNamara, John M

2015-04-01

A striking feature of human decision making is the fourfold pattern of risk attitudes, involving risk-averse behavior in situations of unlikely losses and likely gains, but risk-seeking behavior in response to likely losses and unlikely gains. Current theories to explain this pattern assume particular psychological processes to reproduce empirical observations, but do not address whether it is adaptive for the decision maker to respond to risk in this way. Here, drawing on insights from behavioral ecology, we build an evolutionary model of risk-sensitive behavior, to investigate whether particular types of environmental conditions could favor a fourfold pattern of risk attitudes. We consider an individual foraging in a changing environment, where energy is needed to prevent starvation and build up reserves for reproduction. The outcome, in terms of reproductive value (a rigorous measure of evolutionary success), of a one-off choice between a risky and a safe gain, or between a risky and a safe loss, determines the risk-sensitive behavior we should expect to see in this environment. Our results show that the fourfold pattern of risk attitudes may be adaptive in an environment in which conditions vary stochastically but are autocorrelated in time. In such an environment the current options provide information about the likely environmental conditions in the future, which affect the optimal pattern of risk sensitivity. Our model predicts that risk preferences should be both path dependent and affected by the decision maker's current state. (c) 2015 APA, all rights reserved).

Suicide risk factors for young adults: testing a model across ethnicities.

PubMed

Gutierrez, P M; Rodriguez, P J; Garcia, P

2001-06-01

A general path model based on existing suicide risk research was developed to test factors contributing to current suicidal ideation in young adults. A sample of 673 undergraduate students completed a packet of questionnaires containing the Beck Depression Inventory, Adult Suicidal Ideation Questionnaire, and Multi-Attitude Suicide Tendency Scale. They also provided information on history of suicidality and exposure to attempted and completed suicide in others. Structural equation modeling was used to test the fit of the data to the hypothesized model. Goodness-of-fit indices were adequate and supported the interactive effects of exposure, repulsion by life, depression, and history of self-harm on current ideation. Model fit for three subgroups based on race/ethnicity (i.e., White, Black, and Hispanic) determined that repulsion by life and depression function differently across groups. Implications of these findings for current methods of suicide risk assessment and future research are discussed in the context of the importance of culture.

A framework for global river flood risk assessments

NASA Astrophysics Data System (ADS)

Winsemius, H. C.; Van Beek, L. P. H.; Jongman, B.; Ward, P. J.; Bouwman, A.

2012-08-01

There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate. The framework estimates hazard at high resolution (~1 km2) using global forcing datasets of the current (or in scenario mode, future) climate, a global hydrological model, a global flood routing model, and importantly, a flood extent downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population) to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population). The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE). We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case-study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard and damage estimates has been performed using the Dartmouth Flood Observatory database and damage estimates from the EM-DAT database and World Bank sources. We discuss and show sensitivities of the estimated risks with regard to the use of different climate input sets, decisions made in the downscaling algorithm, and different approaches to establish impact models.

Modelling fatigue and the use of fatigue models in work settings.

PubMed

Dawson, Drew; Ian Noy, Y; Härmä, Mikko; Akerstedt, Torbjorn; Belenky, Gregory

2011-03-01

In recent years, theoretical models of the sleep and circadian system developed in laboratory settings have been adapted to predict fatigue and, by inference, performance. This is typically done using the timing of prior sleep and waking or working hours as the primary input and the time course of the predicted variables as the primary output. The aim of these models is to provide employers, unions and regulators with quantitative information on the likely average level of fatigue, or risk, associated with a given pattern of work and sleep with the goal of better managing the risk of fatigue-related errors and accidents/incidents. The first part of this review summarises the variables known to influence workplace fatigue and draws attention to the considerable variability attributable to individual and task variables not included in current models. The second part reviews the current fatigue models described in the scientific and technical literature and classifies them according to whether they predict fatigue directly by using the timing of prior sleep and wake (one-step models) or indirectly by using work schedules to infer an average sleep-wake pattern that is then used to predict fatigue (two-step models). The third part of the review looks at the current use of fatigue models in field settings by organizations and regulators. Given their limitations it is suggested that the current generation of models may be appropriate for use as one element in a fatigue risk management system. The final section of the review looks at the future of these models and recommends a standardised approach for their use as an element of the 'defenses-in-depth' approach to fatigue risk management. Copyright © 2010 Elsevier Ltd. All rights reserved.

Practical examples of modeling choices and their consequences for risk assessment

EPA Science Inventory

Although benchmark dose (BMD) modeling has become the preferred approach to identifying a point of departure (POD) over the No Observed Adverse Effect Level, there remain challenges to its application in human health risk assessment. BMD modeling, as currently implemented by the...

Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724

77 FR 17536 - Self-Regulatory Organizations; ICE Clear Credit LLC; Notice of Filing of Proposed Rule Change to...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-26

... Organizations; ICE Clear Credit LLC; Notice of Filing of Proposed Rule Change to Its Risk Model To Reduce the Current Level of Risk Mutualization Among Its Clearing Participants and To Modify the Initial Margin Risk Model so That It Is Easier for Market Participants To Measure Their Risk March 20, 2012. Pursuant to...

Comorbid sleep disorders and suicide risk among children and adolescents with bipolar disorder.

PubMed

Stanley, Ian H; Hom, Melanie A; Luby, Joan L; Joshi, Paramjit T; Wagner, Karen D; Emslie, Graham J; Walkup, John T; Axelson, David A; Joiner, Thomas E

2017-12-01

Children and adolescents with bipolar disorder are at increased risk for suicide. Sleep disturbances are common among youth with bipolar disorder and are also independently implicated in suicide risk; thus, comorbid sleep disorders may amplify suicide risk in this clinical population. This study examined the effects of comorbid sleep disorders on suicide risk among youth with bipolar disorder. We conducted secondary analyses of baseline data from the Treatment of Early Age Mania (TEAM) study, a randomized controlled trial of individuals aged 6-15 years (mean ± SD = 10.2 ± 2.7 years) with DSM-IV bipolar I disorder (N = 379). Sleep disorders (i.e., nightmare, sleep terror, and sleepwalking disorders) and suicide risk were assessed via the WASH-U-KSADS and the CDRS-R, respectively. We constructed uncontrolled logistic regression models as well as models controlling for trauma history, a generalized anxiety disorder (GAD) diagnosis, and depression symptoms. Participants with a current comorbid nightmare disorder versus those without were nearly twice as likely to screen positive for suicide risk in an uncontrolled model and models controlling for trauma history, a GAD diagnosis, and depression symptoms. Neither a current comorbid sleep terror disorder nor a sleepwalking disorder was significantly associated with suicide risk. This pattern of findings remained consistent for both current and lifetime sleep disorder diagnoses. Youth with bipolar I disorder and a comorbid nightmare disorder appear to be at heightened suicide risk. Implications for assessment and treatment are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Model for Assessing the Liability of Seemingly Correct Software

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Voas, Larry K.; Miller, Keith W.

1991-01-01

Current research on software reliability does not lend itself to quantitatively assessing the risk posed by a piece of life-critical software. Black-box software reliability models are too general and make too many assumptions to be applied confidently to assessing the risk of life-critical software. We present a model for assessing the risk caused by a piece of software; this model combines software testing results and Hamlet's probable correctness model. We show how this model can assess software risk for those who insure against a loss that can occur if life-critical software fails.

Integrated Environmental Modeling: Quantitative Microbial Risk Assessment

EPA Science Inventory

The presentation discusses the need for microbial assessments and presents a road map associated with quantitative microbial risk assessments, through an integrated environmental modeling approach. A brief introduction and the strengths of the current knowledge are illustrated. W...

Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data

EPA Science Inventory

The benchmark dose (BMD) approach has gained acceptance as a valuable risk assessment tool, but risk assessors still face significant challenges associated with selecting an appropriate BMD/BMDL estimate from the results of a set of acceptable dose-response models. Current approa...

Development and validation of a risk model for identification of non-neutropenic, critically ill adult patients at high risk of invasive Candida infection: the Fungal Infection Risk Evaluation (FIRE) Study.

PubMed

Harrison, D; Muskett, H; Harvey, S; Grieve, R; Shahin, J; Patel, K; Sadique, Z; Allen, E; Dybowski, R; Jit, M; Edgeworth, J; Kibbler, C; Barnes, R; Soni, N; Rowan, K

2013-02-01

There is increasing evidence that invasive fungal disease (IFD) is more likely to occur in non-neutropenic patients in critical care units. A number of randomised controlled trials (RCTs) have evaluated antifungal prophylaxis in non-neutropenic, critically ill patients, demonstrating a reduction in the risk of proven IFD and suggesting a reduction in mortality. It is necessary to establish a method to identify and target antifungal prophylaxis at those patients at highest risk of IFD, who stand to benefit most from any antifungal prophylaxis strategy. To develop and validate risk models to identify non-neutropenic, critically ill adult patients at high risk of invasive Candida infection, who would benefit from antifungal prophylaxis, and to assess the cost-effectiveness of targeting antifungal prophylaxis to high-risk patients based on these models. Systematic review, prospective data collection, statistical modelling, economic decision modelling and value of information analysis. Ninety-six UK adult general critical care units. Consecutive admissions to participating critical care units. None. Invasive fungal disease, defined as a blood culture or sample from a normally sterile site showing yeast/mould cells in a microbiological or histopathological report. For statistical and economic modelling, the primary outcome was invasive Candida infection, defined as IFD-positive for Candida species. Systematic review: Thirteen articles exploring risk factors, risk models or clinical decision rules for IFD in critically ill adult patients were identified. Risk factors reported to be significantly associated with IFD were included in the final data set for the prospective data collection. Data were collected on 60,778 admissions between July 2009 and March 2011. Overall, 383 patients (0.6%) were admitted with or developed IFD. The majority of IFD patients (94%) were positive for Candida species. The most common site of infection was blood (55%). The incidence of IFD identified in unit was 4.7 cases per 1000 admissions, and for unit-acquired IFD was 3.2 cases per 1000 admissions. Statistical modelling: Risk models were developed at admission to the critical care unit, 24 hours and the end of calendar day 3. The risk model at admission had fair discrimination (c-index 0.705). Discrimination improved at 24 hours (c-index 0.823) and this was maintained at the end of calendar day 3 (c-index 0.835). There was a drop in model performance in the validation sample. Economic decision model: Irrespective of risk threshold, incremental quality-adjusted life-years of prophylaxis strategies compared with current practice were positive but small compared with the incremental costs. Incremental net benefits of each prophylaxis strategy compared with current practice were all negative. Cost-effectiveness acceptability curves showed that current practice was the strategy most likely to be cost-effective. Across all parameters in the decision model, results indicated that the value of further research for the whole population of interest might be high relative to the research costs. The results of the Fungal Infection Risk Evaluation (FIRE) Study, derived from a highly representative sample of adult general critical care units across the UK, indicated a low incidence of IFD among non-neutropenic, critically ill adult patients. IFD was associated with substantially higher mortality, more intensive organ support and longer length of stay. Risk modelling produced simple risk models that provided acceptable discrimination for identifying patients at 'high risk' of invasive Candida infection. Results of the economic model suggested that the current most cost-effective treatment strategy for prophylactic use of systemic antifungal agents among non-neutropenic, critically ill adult patients admitted to NHS adult general critical care units is a strategy of no risk assessment and no antifungal prophylaxis. Funding for this study was provided by the Health Technology Assessment programme of the National Institute for Health Research.

The cardiovascular event reduction tool (CERT)--a simplified cardiac risk prediction model developed from the West of Scotland Coronary Prevention Study (WOSCOPS).

PubMed

L'Italien, G; Ford, I; Norrie, J; LaPuerta, P; Ehreth, J; Jackson, J; Shepherd, J

2000-03-15

The clinical decision to treat hypercholesterolemia is premised on an awareness of patient risk, and cardiac risk prediction models offer a practical means of determining such risk. However, these models are based on observational cohorts where estimates of the treatment benefit are largely inferred. The West of Scotland Coronary Prevention Study (WOSCOPS) provides an opportunity to develop a risk-benefit prediction model from the actual observed primary event reduction seen in the trial. Five-year Cox model risk estimates were derived from all WOSCOPS subjects (n = 6,595 men, aged 45 to 64 years old at baseline) using factors previously shown to be predictive of definite fatal coronary heart disease or nonfatal myocardial infarction. Model risk factors included age, diastolic blood pressure, total cholesterol/ high-density lipoprotein ratio (TC/HDL), current smoking, diabetes, family history of fatal coronary heart disease, nitrate use or angina, and treatment (placebo/ 40-mg pravastatin). All risk factors were expressed as categorical variables to facilitate risk assessment. Risk estimates were incorporated into a simple, hand-held slide rule or risk tool. Risk estimates were identified for 5-year age bands (45 to 65 years), 4 categories of TC/HDL ratio (<5.5, 5.5 to <6.5, 6.5 to <7.5, > or = 7.5), 2 levels of diastolic blood pressure (<90, > or = 90 mm Hg), from 0 to 3 additional risk factors (current smoking, diabetes, family history of premature fatal coronary heart disease, nitrate use or angina), and pravastatin treatment. Five-year risk estimates ranged from 2% in very low-risk subjects to 61% in the very high-risk subjects. Risk reduction due to pravastatin treatment averaged 31%. Thus, the Cardiovascular Event Reduction Tool (CERT) is a risk prediction model derived from the WOSCOPS trial. Its use will help physicians identify patients who will benefit from cholesterol reduction.

A Review on Automatic Mammographic Density and Parenchymal Segmentation

PubMed Central

He, Wenda; Juette, Arne; Denton, Erika R. E.; Oliver, Arnau

2015-01-01

Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models. PMID:26171249

Algorithms for the prediction of retinopathy of prematurity based on postnatal weight gain.

PubMed

Binenbaum, Gil

2013-06-01

Current ROP screening guidelines represent a simple risk model with two dichotomized factors, birth weight and gestational age at birth. Pioneering work has shown that tracking postnatal weight gain, a surrogate for low insulin-like growth factor 1, may capture the influence of many other ROP risk factors and improve risk prediction. Models including weight gain, such as WINROP, ROPScore, and CHOP ROP, have demonstrated accurate ROP risk assessment and a potentially large reduction in ROP examinations, compared to current guidelines. However, there is a need for larger studies, and generalizability is limited in countries with developing neonatal care systems. Copyright © 2013 Elsevier Inc. All rights reserved.

Toward refined environmental scenarios for ecological risk assessment of down-the-drain chemicals in freshwater environments.

PubMed

Franco, Antonio; Price, Oliver R; Marshall, Stuart; Jolliet, Olivier; Van den Brink, Paul J; Rico, Andreu; Focks, Andreas; De Laender, Frederik; Ashauer, Roman

2017-03-01

Current regulatory practice for chemical risk assessment suffers from the lack of realism in conventional frameworks. Despite significant advances in exposure and ecological effect modeling, the implementation of novel approaches as high-tier options for prospective regulatory risk assessment remains limited, particularly among general chemicals such as down-the-drain ingredients. While reviewing the current state of the art in environmental exposure and ecological effect modeling, we propose a scenario-based framework that enables a better integration of exposure and effect assessments in a tiered approach. Global- to catchment-scale spatially explicit exposure models can be used to identify areas of higher exposure and to generate ecologically relevant exposure information for input into effect models. Numerous examples of mechanistic ecological effect models demonstrate that it is technically feasible to extrapolate from individual-level effects to effects at higher levels of biological organization and from laboratory to environmental conditions. However, the data required to parameterize effect models that can embrace the complexity of ecosystems are large and require a targeted approach. Experimental efforts should, therefore, focus on vulnerable species and/or traits and ecological conditions of relevance. We outline key research needs to address the challenges that currently hinder the practical application of advanced model-based approaches to risk assessment of down-the-drain chemicals. Integr Environ Assess Manag 2017;13:233-248. © 2016 SETAC. © 2016 SETAC.

Breast cancer risk from different mammography screening practices.

PubMed

Bijwaard, Harmen; Brenner, Alina; Dekkers, Fieke; van Dillen, Teun; Land, Charles E; Boice, John D

2010-09-01

Mammography screening is an accepted procedure for early detection of breast tumors among asymptomatic women. Since this procedure involves the use of X rays, it is itself potentially carcinogenic. Although there is general consensus about the benefit of screening for older women, screening practices differ between countries. In this paper radiation risks for these different practices are estimated using a new approach. We model breast cancer induction by ionizing radiation in a cohort of patients exposed to frequent X-ray examinations. The biologically based, mechanistic model provides a better foundation for the extrapolation of risks to different mammography screening practices than empirical models do. The model predicts that the excess relative risk (ERR) doubles when screening starts at age 40 instead of 50 and that a continuation of screening at ages 75 and higher carries little extra risk. The number of induced fatal breast cancers is estimated to be considerably lower than derived from epidemiological studies and from internationally accepted radiation protection risks. The present findings, if used in a risk-benefit analysis for mammography screening, would be more favorable to screening than estimates currently recommended for radiation protection. This has implications for the screening ages that are currently being reconsidered in several countries.

Risk stratification following acute myocardial infarction.

PubMed

Singh, Mandeep

2007-07-01

This article reviews the current risk assessment models available for patients presenting with myocardial infarction (MI). These practical tools enhance the health care provider's ability to rapidly and accurately assess patient risk from the event or revascularization therapy, and are of paramount importance in managing patients presenting with MI. This article highlights the models used for ST-elevation MI (STEMI) and non-ST elevation MI (NSTEMI) and provides an additional description of models used to assess risks after primary angioplasty (ie, angioplasty performed for STEMI).

Systems engineering approach to environmental risk management: A case study of depleted uranium at test area C-64, Eglin Air Force Base, Florida. Master`s thesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carter, C.M.; Fortmann, K.M.; Hill, S.W.

1994-12-01

Environmental restoration is an area of concern in an environmentally conscious world. Much effort is required to clean up the environment and promote environmentally sound methods for managing current land use. In light of the public consciousness with the latter topic, the United States Air Force must also take an active role in addressing these environmental issues with respect to current and future USAF base land use. This thesis uses the systems engineering technique to assess human health risks and to evaluate risk management options with respect to depleted uranium contamination in the sampled region of Test Area (TA) C-64more » at Eglin Air Force Base (AFB). The research combines the disciplines of environmental data collection, DU soil concentration distribution modeling, ground water modeling, particle resuspension modeling, exposure assessment, health hazard assessment, and uncertainty analysis to characterize the test area. These disciplines are required to quantify current and future health risks, as well as to recommend cost effective ways to increase confidence in health risk assessment and remediation options.« less

Development of a Multi-Hazard Landscape for Exposure and Risk Interpretation

EPA Science Inventory

A complete accounting of potential hazard exposures is critical in the development of any model meant to depict the resilience of a system. This allows for a clear ledger to both assess current risk status along with potential ways to improve resilience. The US EPA is currently...

77 FR 27255 - Self-Regulatory Organizations; ICE Clear Credit LLC; Order Approving Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-09

... Organizations; ICE Clear Credit LLC; Order Approving Proposed Rule Change To Reduce the Current Level of Risk Mutualization Among Clearing Participants and To Modify the Initial Margin Risk Model So That It Is Easier for... modifications to its risk model for clearing credit default swaps (``CDS'') contracts. For the first...

Validation of visualized transgenic zebrafish as a high throughput model to assay bradycardia related cardio toxicity risk candidates.

PubMed

Wen, Dingsheng; Liu, Aiming; Chen, Feng; Yang, Julin; Dai, Renke

2012-10-01

Drug-induced QT prolongation usually leads to torsade de pointes (TdP), thus for drugs in the early phase of development this risk should be evaluated. In the present study, we demonstrated a visualized transgenic zebrafish as an in vivo high-throughput model to assay the risk of drug-induced QT prolongation. Zebrafish larvae 48 h post-fertilization expressing green fluorescent protein in myocardium were incubated with compounds reported to induce QT prolongation or block the human ether-a-go-go-related gene (hERG) K⁺ current. The compounds sotalol, indapaminde, erythromycin, ofoxacin, levofloxacin, sparfloxacin and roxithromycin were additionally administrated by microinjection into the larvae yolk sac. The ventricle heart rate was recorded using the automatic monitoring system after incubation or microinjection. As a result, 14 out of 16 compounds inducing dog QT prolongation caused bradycardia in zebrafish. A similar result was observed with 21 out of 26 compounds which block hERG current. Among the 30 compounds which induced human QT prolongation, 25 caused bradycardia in this model. Thus, the risk of compounds causing bradycardia in this transgenic zebrafish correlated with that causing QT prolongation and hERG K⁺ current blockage in established models. The tendency that high logP values lead to high risk of QT prolongation in this model was indicated, and non-sensitivity of this model to antibacterial agents was revealed. These data suggest application of this transgenic zebrafish as a high-throughput model to screen QT prolongation-related cardio toxicity of the drug candidates. Copyright © 2012 John Wiley & Sons, Ltd.

Modeled Health Economic Impact of a Hypothetical Certolizumab Pegol Risk-Sharing Scheme for Patients with Moderate-to-Severe Rheumatoid Arthritis in Finland.

PubMed

Soini, Erkki; Asseburg, Christian; Taiha, Maarit; Puolakka, Kari; Purcaru, Oana; Luosujärvi, Riitta

2017-10-01

To model the American College of Rheumatology (ACR) outcomes, cost-effectiveness, and budget impact of certolizumab pegol (CZP) (with and without a hypothetical risk-sharing scheme at treatment initiation for biologic-naïve patients) versus the current mix of reimbursed biologics for treatment of moderate-to-severe rheumatoid arthritis (RA) in Finland. A probabilistic model with 12-week cycles and a societal approach was developed for the years 2015-2019, accounting for differences in ACR responses (meta-analysis), mortality, and persistence. The risk-sharing scheme included a treatment switch and refund of the costs associated with CZP acquisition if patients failed to achieve ACR20 response at week 12. For the current treatment mix, ACR20 at week 24 determined treatment continuation. Quality-adjusted life years were derived on the basis of the Health Utilities Index. In the Finnish target population, CZP treatment with a risk-sharing scheme led to a estimated annual net expenditure decrease ranging from 1.7% in 2015 to 5.6% in 2019 compared with the current treatment mix. Per patient over the 5 years, CZP risk sharing was estimated to decrease the time without ACR response by 5%-units, decrease work absenteeism by 24 days, and increase the time with ACR20, ACR50, and ACR70 responses by 5%-, 6%-, and 1%-units, respectively, with a gain of 0.03 quality-adjusted life years. The modeled risk-sharing scheme showed reduced costs of €7866 per patient, with a more than 95% probability of cost-effectiveness when compared with the current treatment mix. The present analysis estimated that CZP, with or without the risk-sharing scheme, is a cost-effective alternative treatment for RA patients in Finland. The surplus provided by the CZP risk-sharing scheme could fund treatment for 6% more Finnish RA patients. UCB Pharma.

Development of a risk assessment tool for projecting individualized probabilities of developing breast cancer for Chinese women.

PubMed

Wang, Yuan; Gao, Ying; Battsend, Munkhzul; Chen, Kexin; Lu, Wenli; Wang, Yaogang

2014-11-01

The optimal approach regarding breast cancer screening for Chinese women is unclear due to the relative low incidence rate. A risk assessment tool may be useful for selection of high-risk subsets of population for mammography screening in low-incidence and resource-limited developing country. The odd ratios for six main risk factors of breast cancer were pooled by review manager after a systematic research of literature. Health risk appraisal (HRA) model was developed to predict an individual's risk of developing breast cancer in the next 5 years from current age. The performance of this HRA model was assessed based on a first-round screening database. Estimated risk of breast cancer increased with age. Increases in the 5-year risk of developing breast cancer were found with the existence of any of included risk factors. When individuals who had risk above median risk (3.3‰) were selected from the validation database, the sensitivity is 60.0% and the specificity is 47.8%. The unweighted area under the curve (AUC) was 0.64 (95% CI = 0.50-0.78). The risk-prediction model reported in this article is based on a combination of risk factors and shows good overall predictive power, but it is still weak at predicting which particular women will develop the disease. It would be very helpful for the improvement of a current model if more population-based prospective follow-up studies were used for the validation.

Characterizing uncertainty when evaluating risk management metrics: risk assessment modeling of Listeria monocytogenes contamination in ready-to-eat deli meats.

PubMed

Gallagher, Daniel; Ebel, Eric D; Gallagher, Owen; Labarre, David; Williams, Michael S; Golden, Neal J; Pouillot, Régis; Dearfield, Kerry L; Kause, Janell

2013-04-01

This report illustrates how the uncertainty about food safety metrics may influence the selection of a performance objective (PO). To accomplish this goal, we developed a model concerning Listeria monocytogenes in ready-to-eat (RTE) deli meats. This application used a second order Monte Carlo model that simulates L. monocytogenes concentrations through a series of steps: the food-processing establishment, transport, retail, the consumer's home and consumption. The model accounted for growth inhibitor use, retail cross contamination, and applied an FAO/WHO dose response model for evaluating the probability of illness. An appropriate level of protection (ALOP) risk metric was selected as the average risk of illness per serving across all consumed servings-per-annum and the model was used to solve for the corresponding performance objective (PO) risk metric as the maximum allowable L. monocytogenes concentration (cfu/g) at the processing establishment where regulatory monitoring would occur. Given uncertainty about model inputs, an uncertainty distribution of the PO was estimated. Additionally, we considered how RTE deli meats contaminated at levels above the PO would be handled by the industry using three alternative approaches. Points on the PO distribution represent the probability that - if the industry complies with a particular PO - the resulting risk-per-serving is less than or equal to the target ALOP. For example, assuming (1) a target ALOP of -6.41 log10 risk of illness per serving, (2) industry concentrations above the PO that are re-distributed throughout the remaining concentration distribution and (3) no dose response uncertainty, establishment PO's of -4.98 and -4.39 log10 cfu/g would be required for 90% and 75% confidence that the target ALOP is met, respectively. The PO concentrations from this example scenario are more stringent than the current typical monitoring level of an absence in 25 g (i.e., -1.40 log10 cfu/g) or a stricter criteria of absence in 125 g (i.e., -2.1 log10 cfu/g). This example, and others, demonstrates that a PO for L. monocytogenes would be far below any current monitoring capabilities. Furthermore, this work highlights the demands placed on risk managers and risk assessors when applying uncertain risk models to the current risk metric framework. Copyright © 2013 Elsevier B.V. All rights reserved.

Appendix 2: Risk-based framework and risk case studies. Risk Assessment for two bird species in northern Wisconsin.

Treesearch

Megan M. Friggens; Stephen N. Matthews

2012-01-01

Species distribution models for 147 bird species have been derived using climate, elevation, and distribution of current tree species as potential predictors (Matthews et al. 2011). In this case study, a risk matrix was developed for two bird species (fig. A2-5), with projected change in bird habitat (the x axis) based on models of changing suitable habitat resulting...

Cardiovascular disease risk scores in the current practice: which to use in rheumatoid arthritis?

PubMed

Purcarea, A; Sovaila, S; Gheorghe, A; Udrea, G; Stoica, V

2014-01-01

Cardiovascular disease (CVD) is the highest prevalence disease in the general population (GP) and it accounts for 20 million deaths worldwide each year. Its prevalence is even higher in rheumatoid arthritis. Early detection of subclinical disease is critical and the use of cardiovascular risk prediction models and calculators is widely spread. The impact of such techniques in the GP was previously studied. Despite their common background and similarities, some disagreement exists between most scores and their importance in special high-risk populations like rheumatoid arthritis (RA), having a low level of evidence. The current article aims to single out those predictive models (models) that could be most useful in the care of rheumatoid arthritis patients.

Cardiovascular disease risk scores in the current practice: which to use in rheumatoid arthritis?

PubMed Central

Purcarea, A; Sovaila, S; Gheorghe, A; Udrea, G; Stoica, V

2014-01-01

Cardiovascular disease (CVD) is the highest prevalence disease in the general population (GP) and it accounts for 20 million deaths worldwide each year. Its prevalence is even higher in rheumatoid arthritis. Early detection of subclinical disease is critical and the use of cardiovascular risk prediction models and calculators is widely spread. The impact of such techniques in the GP was previously studied. Despite their common background and similarities, some disagreement exists between most scores and their importance in special high-risk populations like rheumatoid arthritis (RA), having a low level of evidence. The current article aims to single out those predictive models (models) that could be most useful in the care of rheumatoid arthritis patients. PMID:25713603

Proposals for enhanced health risk assessment and stratification in an integrated care scenario

PubMed Central

Dueñas-Espín, Ivan; Vela, Emili; Pauws, Steffen; Bescos, Cristina; Cano, Isaac; Cleries, Montserrat; Contel, Joan Carles; de Manuel Keenoy, Esteban; Garcia-Aymerich, Judith; Gomez-Cabrero, David; Kaye, Rachelle; Lahr, Maarten M H; Lluch-Ariet, Magí; Moharra, Montserrat; Monterde, David; Mora, Joana; Nalin, Marco; Pavlickova, Andrea; Piera, Jordi; Ponce, Sara; Santaeugenia, Sebastià; Schonenberg, Helen; Störk, Stefan; Tegner, Jesper; Velickovski, Filip; Westerteicher, Christoph; Roca, Josep

2016-01-01

Objectives Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario. Settings The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL). Participants Responsible teams for regional data management in the five ACT regions. Primary and secondary outcome measures We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction. Results There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment. Conclusions The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation. PMID:27084274

Simulating the Risk of Liver Fluke Infection using a Mechanistic Hydro-epidemiological Model

NASA Astrophysics Data System (ADS)

Beltrame, Ludovica; Dunne, Toby; Rose, Hannah; Walker, Josephine; Morgan, Eric; Vickerman, Peter; Wagener, Thorsten

2016-04-01

Liver Fluke (Fasciola hepatica) is a common parasite found in livestock and responsible for considerable economic losses throughout the world. Risk of infection is strongly influenced by climatic and hydrological conditions, which characterise the host environment for parasite development and transmission. Despite on-going control efforts, increases in fluke outbreaks have been reported in recent years in the UK, and have been often attributed to climate change. Currently used fluke risk models are based on empirical relationships derived between historical climate and incidence data. However, hydro-climate conditions are becoming increasingly non-stationary due to climate change and direct anthropogenic impacts such as land use change, making empirical models unsuitable for simulating future risk. In this study we introduce a mechanistic hydro-epidemiological model for Liver Fluke, which explicitly simulates habitat suitability for disease development in space and time, representing the parasite life cycle in connection with key environmental conditions. The model is used to assess patterns of Liver Fluke risk for two catchments in the UK under current and potential future climate conditions. Comparisons are made with a widely used empirical model employing different datasets, including data from regional veterinary laboratories. Results suggest that mechanistic models can achieve adequate predictive ability and support adaptive fluke control strategies under climate change scenarios.

MODIS imagery improves pest risk assessment: A case study of wheat stem sawfly (Cephus cinctus, Hymenoptera: Cephidae) in Colorado, USA

USGS Publications Warehouse

Lestina, Jordan; Cook, Maxwell; Kumar, Sunil; Morisette, Jeffrey T.; Ode, Paul J.; Peirs, Frank

2016-01-01

Wheat stem sawfly (Cephus cinctus Norton, Hymenoptera: Cephidae) has long been a significant insect pest of spring, and more recently, winter wheat in the northern Great Plains. Wheat stem sawfly was first observed infesting winter wheat in Colorado in 2010 and, subsequently, has spread rapidly throughout wheat production regions of the state. Here, we used maximum entropy modeling (MaxEnt) to generate habitat suitability maps in order to predict the risk of crop damage as this species spreads throughout the winter wheat-growing regions of Colorado. We identified environmental variables that influence the current distribution of wheat stem sawfly in the state and evaluated whether remotely sensed variables improved model performance. We used presence localities of C. cinctus and climatic, topographic, soils, and normalized difference vegetation index and enhanced vegetation index data derived from Moderate Resolution Imaging Spectroradiometer (MODIS) imagery as environmental variables. All models had high performance in that they were successful in predicting suitable habitat for C. cinctus in its current distribution in eastern Colorado. The enhanced vegetation index for the month of April improved model performance and was identified as a top contributor to MaxEnt model. Soil clay percent at 0–5 cm, temperature seasonality, and precipitation seasonality were also associated with C. cinctus distribution in Colorado. The improved model performance resulting from integrating vegetation indices in our study demonstrates the ability of remote sensing technologies to enhance species distribution modeling. These risk maps generated can assist managers in planning control measures for current infestations and assess the future risk of C. cinctus establishment in currently uninfested regions.

A framework for global river flood risk assessments

NASA Astrophysics Data System (ADS)

Winsemius, H. C.; Van Beek, L. P. H.; Jongman, B.; Ward, P. J.; Bouwman, A.

2013-05-01

There is an increasing need for strategic global assessments of flood risks in current and future conditions. In this paper, we propose a framework for global flood risk assessment for river floods, which can be applied in current conditions, as well as in future conditions due to climate and socio-economic changes. The framework's goal is to establish flood hazard and impact estimates at a high enough resolution to allow for their combination into a risk estimate, which can be used for strategic global flood risk assessments. The framework estimates hazard at a resolution of ~ 1 km2 using global forcing datasets of the current (or in scenario mode, future) climate, a global hydrological model, a global flood-routing model, and more importantly, an inundation downscaling routine. The second component of the framework combines hazard with flood impact models at the same resolution (e.g. damage, affected GDP, and affected population) to establish indicators for flood risk (e.g. annual expected damage, affected GDP, and affected population). The framework has been applied using the global hydrological model PCR-GLOBWB, which includes an optional global flood routing model DynRout, combined with scenarios from the Integrated Model to Assess the Global Environment (IMAGE). We performed downscaling of the hazard probability distributions to 1 km2 resolution with a new downscaling algorithm, applied on Bangladesh as a first case study application area. We demonstrate the risk assessment approach in Bangladesh based on GDP per capita data, population, and land use maps for 2010 and 2050. Validation of the hazard estimates has been performed using the Dartmouth Flood Observatory database. This was done by comparing a high return period flood with the maximum observed extent, as well as by comparing a time series of a single event with Dartmouth imagery of the event. Validation of modelled damage estimates was performed using observed damage estimates from the EM-DAT database and World Bank sources. We discuss and show sensitivities of the estimated risks with regard to the use of different climate input sets, decisions made in the downscaling algorithm, and different approaches to establish impact models.

Overview of the CERT Resilience Management Model (CERT-RMM)

DTIC Science & Technology

2014-01-23

Management Model (CERT®-RMM) Jim Cebula Technical Manager - Cyber Risk Management , CERT® Division Jim Cebula is the Technical Manager of the...Cyber Risk Management team in the Cyber Security Solutions Directorate of the CERT Division at the Software Engineering Institute (SEI), a unit of...Carnegie Mellon University. Cebula’s current activities include risk management methods along with assessment and management of operational

(De)Constructing the Risk Categories in the Aim Assessment Model for Children with Sexually Harmful Behaviour

ERIC Educational Resources Information Center

Myers, Steve

2007-01-01

This article critically analyses the AIM Assessment Model for children who have sexually harmful behaviour, exploring the underpinning knowledge and the processes involved. The model reflects current trends in the assessment of children, in child welfare and criminal justice services, producing categories of risk that lead to levels of…

Software risk estimation and management techniques at JPL

NASA Technical Reports Server (NTRS)

Hihn, J.; Lum, K.

2002-01-01

In this talk we will discuss how uncertainty has been incorporated into the JPL software model, probabilistic-based estimates, and how risk is addressed, how cost risk is currently being explored via a variety of approaches, from traditional risk lists, to detailed WBS-based risk estimates to the Defect Detection and Prevention (DDP) tool.

PBPK and population modelling to interpret urine cadmium concentrations of the French population

DOE Office of Scientific and Technical Information (OSTI.GOV)

Béchaux, Camille, E-mail: Camille.bechaux@anses.fr; Bodin, Laurent; Clémençon, Stéphan

As cadmium accumulates mainly in kidney, urinary concentrations are considered as relevant data to assess the risk related to cadmium. The French Nutrition and Health Survey (ENNS) recorded the concentration of cadmium in the urine of the French population. However, as with all biomonitoring data, it needs to be linked to external exposure for it to be interpreted in term of sources of exposure and for risk management purposes. The objective of this work is thus to interpret the cadmium biomonitoring data of the French population in terms of dietary and cigarette smoke exposures. Dietary and smoking habits recorded inmore » the ENNS study were combined with contamination levels in food and cigarettes to assess individual exposures. A PBPK model was used in a Bayesian population model to link this external exposure with the measured urinary concentrations. In this model, the level of the past exposure was corrected thanks to a scaling function which account for a trend in the French dietary exposure. It resulted in a modelling which was able to explain the current urinary concentrations measured in the French population through current and past exposure levels. Risk related to cadmium exposure in the general French population was then assessed from external and internal critical values corresponding to kidney effects. The model was also applied to predict the possible urinary concentrations of the French population in 2030 assuming there will be no more changes in the exposures levels. This scenario leads to significantly lower concentrations and consequently lower related risk. - Highlights: • Interpretation of urine cadmium concentrations in France • PBPK and Bayesian population modelling of cadmium exposure • Assessment of the historic time-trend of the cadmium exposure in France • Risk assessment from current and future external and internal exposure.« less

Paradigm of pretest risk stratification before coronary computed tomography.

PubMed

Jensen, Jesper Møller; Ovrehus, Kristian A; Nielsen, Lene H; Jensen, Jesper K; Larsen, Henrik M; Nørgaard, Bjarne L

2009-01-01

The optimal method of determining the pretest risk of coronary artery disease as a patient selection tool before coronary multidetector computed tomography (MDCT) is unknown. We investigated the ability of 3 different clinical risk scores to predict the outcome of coronary MDCT. This was a retrospective study of 551 patients consecutively referred for coronary MDCT on a suspicion of coronary artery disease. Diamond-Forrester, Duke, and Morise risk models were used to predict coronary artery stenosis (>50%) as assessed by coronary MDCT. The models were compared by receiver operating characteristic analysis. The distribution of low-, intermediate-, and high-risk persons, respectively, was established and compared for each of the 3 risk models. Overall, all risk prediction models performed equally well. However, the Duke risk model classified the low-risk patients more correctly than did the other models (P < 0.01). In patients without coronary artery calcification (CAC), the predictive value of the Duke risk model was superior to the other risk models (P < 0.05). Currently available risk prediction models seem to perform better in patients without CAC. Between the risk prediction models, there was a significant discrepancy in the distribution of patients at low, intermediate, or high risk (P < 0.01). The 3 risk prediction models perform equally well, although the Duke risk score may have advantages in subsets of patients. The choice of risk prediction model affects the referral pattern to MDCT. Copyright (c) 2009 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

How does temporal variability in model parameters affect the risk conclusions from MCnest?

EPA Science Inventory

USEPA recently began using the MCnest model for avian risk for adverse reproductive effects due to pesticide exposure. A more advanced version is currently under development and beta testing for use with threatened and endangered birds. For both versions, a species database has...

Fatal and nonfatal risk associated with recycle of D&D-generated concrete

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boren, J.K.; Ayers, K.W.; Parker, F.L.

1997-02-01

As decontamination and decommissioning activities proceed within the U.S. Department of Energy Complex, vast volumes of uncontaminated and contaminated concrete will be generated. The current practice of decontaminating and landfilling the concrete is an expensive and potentially wasteful practice. Research is being conducted at Vanderbilt University to assess the economic, social, legal, and political ramifications of alternate methods of dealing with waste concrete. An important aspect of this research work is the assessment of risk associated with the various alternatives. A deterministic risk assessment model has been developed which quantifies radiological as well as non-radiological risks associated with concrete disposalmore » and recycle activities. The risk model accounts for fatal as well as non-fatal risks to both workers and the public. Preliminary results indicate that recycling of concrete presents potentially lower risks than the current practice. Radiological considerations are shown to be of minor importance in comparison to other sources of risk, with conventional transportation fatalities and injuries dominating. Onsite activities can also be a major contributor to non-fatal risk.« less

Assessing pesticide risks to threatened and endangered species using population models: Findings and recommendations from a CropLife America Science Forum.

PubMed

Forbes, V E; Brain, R; Edwards, D; Galic, N; Hall, T; Honegger, J; Meyer, C; Moore, D R J; Nacci, D; Pastorok, R; Preuss, T G; Railsback, S F; Salice, C; Sibly, R M; Tenhumberg, B; Thorbek, P; Wang, M

2015-07-01

This brief communication reports on the main findings and recommendations from the 2014 Science Forum organized by CropLife America. The aim of the Forum was to gain a better understanding of the current status of population models and how they could be used in ecological risk assessments for threatened and endangered species potentially exposed to pesticides in the United States. The Forum panelists' recommendations are intended to assist the relevant government agencies with implementation of population modeling in future endangered species risk assessments for pesticides. The Forum included keynote presentations that provided an overview of current practices, highlighted the findings of a recent National Academy of Sciences report and its implications, reviewed the main categories of existing population models and the types of risk expressions that can be produced as model outputs, and provided examples of how population models are currently being used in different legislative contexts. The panel concluded that models developed for listed species assessments should provide quantitative risk estimates, incorporate realistic variability in environmental and demographic factors, integrate complex patterns of exposure and effects, and use baseline conditions that include present factors that have caused the species to be listed (e.g., habitat loss, invasive species) or have resulted in positive management action. Furthermore, the panel advocates for the formation of a multipartite advisory committee to provide best available knowledge and guidance related to model implementation and use, to address such needs as more systematic collection, digitization, and dissemination of data for listed species; consideration of the newest developments in good modeling practice; comprehensive review of existing population models and their applicability for listed species assessments; and development of case studies using a few well-tested models for particular species to demonstrate proof of concept. To advance our common goals, the panel recommends the following as important areas for further research and development: quantitative analysis of the causes of species listings to guide model development; systematic assessment of the relative role of toxicity versus other factors in driving pesticide risk; additional study of how interactions between density dependence and pesticides influence risk; and development of pragmatic approaches to assessing indirect effects of pesticides on listed species. © 2015 SETAC.

Predictive risk models for proximal aortic surgery

PubMed Central

Díaz, Rocío; Pascual, Isaac; Álvarez, Rubén; Alperi, Alberto; Rozado, Jose; Morales, Carlos; Silva, Jacobo; Morís, César

2017-01-01

Predictive risk models help improve decision making, information to our patients and quality control comparing results between surgeons and between institutions. The use of these models promotes competitiveness and led to increasingly better results. All these virtues are of utmost importance when the surgical operation entails high-risk. Although proximal aortic surgery is less frequent than other cardiac surgery operations, this procedure itself is more challenging and technically demanding than other common cardiac surgery techniques. The aim of this study is to review the current status of predictive risk models for patients who undergo proximal aortic surgery, which means aortic root replacement, supracoronary ascending aortic replacement or aortic arch surgery. PMID:28616348

A simple simulation model as a tool to assess alternative health care provider payment reform options in Vietnam.

PubMed

Cashin, Cheryl; Phuong, Nguyen Khanh; Shain, Ryan; Oanh, Tran Thi Mai; Thuy, Nguyen Thi

2015-01-01

Vietnam is currently considering a revision of its 2008 Health Insurance Law, including the regulation of provider payment methods. This study uses a simple spreadsheet-based, micro-simulation model to analyse the potential impacts of different provider payment reform scenarios on resource allocation across health care providers in three provinces in Vietnam, as well as on the total expenditure of the provincial branches of the public health insurance agency (Provincial Social Security [PSS]). The results show that currently more than 50% of PSS spending is concentrated at the provincial level with less than half at the district level. There is also a high degree of financial risk on district hospitals with the current fund-holding arrangement. Results of the simulation model show that several alternative scenarios for provider payment reform could improve the current payment system by reducing the high financial risk currently borne by district hospitals without dramatically shifting the current level and distribution of PSS expenditure. The results of the simulation analysis provided an empirical basis for health policy-makers in Vietnam to assess different provider payment reform options and make decisions about new models to support health system objectives.

Development of a Hospital Outcome Measure Intended for Use With Electronic Health Records: 30-Day Risk-standardized Mortality After Acute Myocardial Infarction.

PubMed

McNamara, Robert L; Wang, Yongfei; Partovian, Chohreh; Montague, Julia; Mody, Purav; Eddy, Elizabeth; Krumholz, Harlan M; Bernheim, Susannah M

2015-09-01

Electronic health records (EHRs) offer the opportunity to transform quality improvement by using clinical data for comparing hospital performance without the burden of chart abstraction. However, current performance measures using EHRs are lacking. With support from the Centers for Medicare & Medicaid Services (CMS), we developed an outcome measure of hospital risk-standardized 30-day mortality rates for patients with acute myocardial infarction for use with EHR data. As no appropriate source of EHR data are currently available, we merged clinical registry data from the Action Registry-Get With The Guidelines with claims data from CMS to develop the risk model (2009 data for development, 2010 data for validation). We selected candidate variables that could be feasibly extracted from current EHRs and do not require changes to standard clinical practice or data collection. We used logistic regression with stepwise selection and bootstrapping simulation for model development. The final risk model included 5 variables available on presentation: age, heart rate, systolic blood pressure, troponin ratio, and creatinine level. The area under the receiver operating characteristic curve was 0.78. Hospital risk-standardized mortality rates ranged from 9.6% to 13.1%, with a median of 10.7%. The odds of mortality for a high-mortality hospital (+1 SD) were 1.37 times those for a low-mortality hospital (-1 SD). This measure represents the first outcome measure endorsed by the National Quality Forum for public reporting of hospital quality based on clinical data in the EHR. By being compatible with current clinical practice and existing EHR systems, this measure is a model for future quality improvement measures.

Surrogate modeling of joint flood risk across coastal watersheds

NASA Astrophysics Data System (ADS)

Bass, Benjamin; Bedient, Philip

2018-03-01

This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.

Current modeling practice may lead to falsely high benchmark dose estimates.

PubMed

Ringblom, Joakim; Johanson, Gunnar; Öberg, Mattias

2014-07-01

Benchmark dose (BMD) modeling is increasingly used as the preferred approach to define the point-of-departure for health risk assessment of chemicals. As data are inherently variable, there is always a risk to select a model that defines a lower confidence bound of the BMD (BMDL) that, contrary to expected, exceeds the true BMD. The aim of this study was to investigate how often and under what circumstances such anomalies occur under current modeling practice. Continuous data were generated from a realistic dose-effect curve by Monte Carlo simulations using four dose groups and a set of five different dose placement scenarios, group sizes between 5 and 50 animals and coefficients of variations of 5-15%. The BMD calculations were conducted using nested exponential models, as most BMD software use nested approaches. "Non-protective" BMDLs (higher than true BMD) were frequently observed, in some scenarios reaching 80%. The phenomenon was mainly related to the selection of the non-sigmoidal exponential model (Effect=a·e(b)(·dose)). In conclusion, non-sigmoid models should be used with caution as it may underestimate the risk, illustrating that awareness of the model selection process and sound identification of the point-of-departure is vital for health risk assessment. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

A spatially explicit model for estimating risks of pesticide exposure on bird populations

EPA Science Inventory

Product Description (FY17 Key Product): Current ecological risk assessment for pesticides under FIFRA relies on risk quotients (RQs), which suffer from significant methodological shortcomings. For example, RQs do not integrate adverse effects arising from multiple demographic pr...

Retrospective and current risks of mercury to panthers in the Florida Everglades.

PubMed

Barron, Mace G; Duvall, Stephanie E; Barron, Kyle J

2004-04-01

Florida panthers are an endangered species inhabiting south Florida. Hg has been suggested as a causative factor for low populations and some reported panther deaths, but a quantitative assessment of risks has never been performed. This study quantitatively evaluated retrospective (pre-1992) and current (2002) risks of chronic dietary Hg exposures to panthers in the Florida Everglades. A probabilistic assessment of Hg risks was performed using a dietary exposure model and Latin Hypercube sampling that incorporated the variability and uncertainty in ingestion rate, diet, body weight, and mercury exposure of panthers. Hazard quotients (HQs) for retrospective risks ranged from less than 0.1-20, with a 46% probability of exceeding chronic dietary thresholds for methylmercury. Retrospective risks of developing clinical symptoms, including ataxia and convulsions, had an HQ range of <0.1-5.4 with a 17% probability of exceeding an HQ of 1. Current risks were substantially lower (4% probability of exceedences; HQ range <0.1-3.5) because of an estimated 70-90% decline in Hg exposure to panthers over the last decade. Under worst case conditions of panthers consuming only raccoons from the most contaminated area of the Everglades, current risks of developing clinical symptoms that may lead to death was 4.6%. Current risks of mercury poisoning of panthers with a diversified diet was 0.1% (HQ range of <0.1-1.4). The results of this assessment indicate that past Hg exposures likely adversely affected panthers in the Everglades, but current risks of Hg are low.

Reconstruction of the 1945 Wieringermeer Flood

NASA Astrophysics Data System (ADS)

Hoes, O. A. C.; Hut, R. W.; van de Giesen, N. C.; Boomgaard, M.

2013-03-01

The present state-of-the-art in flood risk assessment focuses on breach models, flood propagation models, and economic modelling of flood damage. However, models need to be validated with real data to avoid erroneous conclusions. Such reference data can either be historic data, or can be obtained from controlled experiments. The inundation of the Wieringermeer polder in the Netherlands in April 1945 is one of the few examples for which sufficient historical information is available. The objective of this article is to compare the flood simulation with flood data from 1945. The context, the breach growth process and the flood propagation are explained. Key findings for current flood risk management addresses the importance of the drainage canal network during the inundation of a polder, and the uncertainty that follows from not knowing the breach growth parameters. This case study shows that historical floods provide valuable data for the validation of models and reveal lessons that are applicable in current day flood risk management.

Bayesian algorithm implementation in a real time exposure assessment model on benzene with calculation of associated cancer risks.

PubMed

Sarigiannis, Dimosthenis A; Karakitsios, Spyros P; Gotti, Alberto; Papaloukas, Costas L; Kassomenos, Pavlos A; Pilidis, Georgios A

2009-01-01

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations.

Bayesian Algorithm Implementation in a Real Time Exposure Assessment Model on Benzene with Calculation of Associated Cancer Risks

PubMed Central

Sarigiannis, Dimosthenis A.; Karakitsios, Spyros P.; Gotti, Alberto; Papaloukas, Costas L.; Kassomenos, Pavlos A.; Pilidis, Georgios A.

2009-01-01

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model. Bayesian algorithm was involved in crucial points of both model sub compartments. The application was evaluated in two filling stations (one urban and one rural). Among several algorithms available for the development of the ANN exposure model, Bayesian regularization provided the best results and seemed to be a promising technique for prediction of the exposure pattern of that occupational population group. On assessing the estimated leukemia risk under the scope of providing a distribution curve based on the exposure levels and the different susceptibility of the population, the Bayesian algorithm was a prerequisite of the Monte Carlo approach, which is integrated in the PBPK-based risk model. In conclusion, the modeling system described herein is capable of exploiting the information collected by the environmental sensors in order to estimate in real time the personal exposure and the resulting health risk for employees of gasoline filling stations. PMID:22399936

Risk Assessment in Child Sexual Abuse Cases

ERIC Educational Resources Information Center

Levenson, Jill S.; Morin, John W.

2006-01-01

Despite continuing improvements in risk assessment for child protective services (CPS) and movement toward actuarial prediction of child maltreatment, current models have not adequately addressed child sexual abuse. Sexual abuse cases present unique and ambiguous indicators to the investigating professional, and risk factors differ from those…

Personalized assessment and management of women at risk for breast cancer in North America.

PubMed

Pruthi, Sandhya; Heisey, Ruth; Bevers, Therese

2015-03-01

Many women at increased risk for breast cancer would benefit from referral for genetic testing, enhanced screening, preventive therapy or risk-reducing surgery. We present a visual model and a step-wise approach to assist with a personalized risk stratification and management of these women. We present current recommendations with respect to lifestyle behaviors and mammographic screening, and we review the current evidence regarding enhanced screening and risk-reducing therapies. We discuss the usefulness of three risk-assessment tools in determining whether a woman qualifies for genetic testing, enhanced screening or preventive therapy and present four cases to demonstrate the usefulness of this approach in the clinical setting.

Incorporating Nonchemical Stressors Into Cumulative Risk Assessments

PubMed Central

Rider, Cynthia V.; Dourson, Michael L.; Hertzberg, Richard C.; Mumtaz, Moiz M.; Price, Paul S.; Simmons, Jane Ellen

2012-01-01

The role of nonchemical stressors in modulating the human health risk associated with chemical exposures is an area of increasing attention. On 9 March 2011, a workshop titled “Approaches for Incorporating Nonchemical Stressors into Cumulative Risk Assessment” took place during the 50th Anniversary Annual Society of Toxicology Meeting in Washington D.C. Objectives of the workshop included describing the current state of the science from various perspectives (i.e., regulatory, exposure, modeling, and risk assessment) and presenting expert opinions on currently available methods for incorporating nonchemical stressors into cumulative risk assessments. Herein, distinct frameworks for characterizing exposure to, joint effects of, and risk associated with chemical and nonchemical stressors are discussed. PMID:22345310

Proposals for enhanced health risk assessment and stratification in an integrated care scenario.

PubMed

Dueñas-Espín, Ivan; Vela, Emili; Pauws, Steffen; Bescos, Cristina; Cano, Isaac; Cleries, Montserrat; Contel, Joan Carles; de Manuel Keenoy, Esteban; Garcia-Aymerich, Judith; Gomez-Cabrero, David; Kaye, Rachelle; Lahr, Maarten M H; Lluch-Ariet, Magí; Moharra, Montserrat; Monterde, David; Mora, Joana; Nalin, Marco; Pavlickova, Andrea; Piera, Jordi; Ponce, Sara; Santaeugenia, Sebastià; Schonenberg, Helen; Störk, Stefan; Tegner, Jesper; Velickovski, Filip; Westerteicher, Christoph; Roca, Josep

2016-04-15

Population-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario. The five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL). Responsible teams for regional data management in the five ACT regions. We characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction. There was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment. The results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The Risk Need Responsivity Model of Offender Rehabilitation: Is There Really a Need for a Paradigm Shift?

ERIC Educational Resources Information Center

Looman, Jan; Abracen, Jeffrey

2013-01-01

The current paper critically reviews the Risk-Need-Responsivity (RNR) and Good Lives Model (GLM) approaches to correctional treatment. Research, or the lack thereof, is discussed in terms of whether there is a need for a new model of offender rehabilitation. We argue that although there is a wealth of research in support of RNR approaches, there…

Flightdeck Automation Problems (FLAP) Model for Safety Technology Portfolio Assessment

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2014-01-01

NASA's Aviation Safety Program (AvSP) develops and advances methodologies and technologies to improve air transportation safety. The Safety Analysis and Integration Team (SAIT) conducts a safety technology portfolio assessment (PA) to analyze the program content, to examine the benefits and risks of products with respect to program goals, and to support programmatic decision making. The PA process includes systematic identification of current and future safety risks as well as tracking several quantitative and qualitative metrics to ensure the program goals are addressing prominent safety risks accurately and effectively. One of the metrics within the PA process involves using quantitative aviation safety models to gauge the impact of the safety products. This paper demonstrates the role of aviation safety modeling by providing model outputs and evaluating a sample of portfolio elements using the Flightdeck Automation Problems (FLAP) model. The model enables not only ranking of the quantitative relative risk reduction impact of all portfolio elements, but also highlighting the areas with high potential impact via sensitivity and gap analyses in support of the program office. Although the model outputs are preliminary and products are notional, the process shown in this paper is essential to a comprehensive PA of NASA's safety products in the current program and future programs/projects.

Multi crop model climate risk country-level management design: case study on the Tanzanian maize production system

NASA Astrophysics Data System (ADS)

Chavez, E.

2015-12-01

Future climate projections indicate that a very serious consequence of post-industrial anthropogenic global warming is the likelihood of the greater frequency and intensity of extreme hydrometeorological events such as heat waves, droughts, storms, and floods. The design of national and international policies targeted at building more resilient and environmentally sustainable food systems needs to rely on access to robust and reliable data which is largely absent. In this context, the improvement of the modelling of current and future agricultural production losses using the unifying language of risk is paramount. In this study, we use a methodology that allows the integration of the current understanding of the various interacting systems of climate, agro-environment, crops, and the economy to determine short to long-term risk estimates of crop production loss, in different environmental, climate, and adaptation scenarios. This methodology is applied to Tanzania to assess optimum risk reduction and maize production increase paths in different climate scenarios. The simulations carried out use inputs from three different crop models (DSSAT, APSIM, WRSI) run in different technological scenarios and thus allowing to estimate crop model-driven risk exposure estimation bias. The results obtained also allow distinguishing different region-specific optimum climate risk reduction policies subject to historical as well as RCP2.5 and RCP8.5 climate scenarios. The region-specific risk profiles obtained provide a simple framework to determine cost-effective risk management policies for Tanzania and allow to optimally combine investments in risk reduction and risk transfer.

Risk factors for accident death in the U.S. Army, 2004-2009.

PubMed

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B; Ursano, Robert J; Heeringa, Steven G

2014-12-01

Accidents are one of the leading causes of death among U.S. active-duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty from line-of-duty accident deaths. Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004-2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers and increased for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate not-line-of-duty from line-of-duty accident deaths. Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. Copyright © 2014 American Journal of Preventive Medicine. All rights reserved.

Risk Factors for Accident Death in the U.S. Army, 2004–2009

PubMed Central

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A.; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C.; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B.; Ursano, Robert J.; Heeringa, Steven G.

2014-01-01

Background Accidents are one of the leading causes of death among U.S. active duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. Purpose To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty (NLOD) from line-of-duty (LOD) accident deaths. Methods Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004–2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Results Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers while increasing for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate NLOD from LOD accident deaths. Conclusions Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. PMID:25441238

Applying Risk and Resilience Metrics to Energy Investments

DTIC Science & Technology

2015-12-01

the model as a positive aspect, though the user can easily devalue risk and resiliency while increasing the value of the cost and policy categories to... policy or position of the Department of Defense or the U.S. Government. IRB Protocol number ____N/A____. 12a. DISTRIBUTION / AVAILABILITY STATEMENT...decision making model. The model developed for this project includes cost metrics and policy mandates that the current model considers and adds the

Defending Against Advanced Persistent Threats Using Game-Theory.

PubMed

Rass, Stefan; König, Sandra; Schauer, Stefan

2017-01-01

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical system security, since information on attacks, the current system status or the attacker's incentives is often vague, uncertain and in many cases even unavailable. Game theory is a natural approach to model the conflict between the attacker and the defender, and this work investigates a generalized class of matrix games as a risk mitigation tool for an advanced persistent threat (APT) defense. Unlike standard game and decision theory, our model is tailored to capture and handle the full uncertainty that is immanent to APTs, such as disagreement among qualitative expert risk assessments, unknown adversarial incentives and uncertainty about the current system state (in terms of how deeply the attacker may have penetrated into the system's protective shells already). Practically, game-theoretic APT models can be derived straightforwardly from topological vulnerability analysis, together with risk assessments as they are done in common risk management standards like the ISO 31000 family. Theoretically, these models come with different properties than classical game theoretic models, whose technical solution presented in this work may be of independent interest.

Risk assessment of vector-borne diseases for public health governance.

PubMed

Sedda, L; Morley, D W; Braks, M A H; De Simone, L; Benz, D; Rogers, D J

2014-12-01

In the context of public health, risk governance (or risk analysis) is a framework for the assessment and subsequent management and/or control of the danger posed by an identified disease threat. Generic frameworks in which to carry out risk assessment have been developed by various agencies. These include monitoring, data collection, statistical analysis and dissemination. Due to the inherent complexity of disease systems, however, the generic approach must be modified for individual, disease-specific risk assessment frameworks. The analysis was based on the review of the current risk assessments of vector-borne diseases adopted by the main Public Health organisations (OIE, WHO, ECDC, FAO, CDC etc…). Literature, legislation and statistical assessment of the risk analysis frameworks. This review outlines the need for the development of a general public health risk assessment method for vector-borne diseases, in order to guarantee that sufficient information is gathered to apply robust models of risk assessment. Stochastic (especially spatial) methods, often in Bayesian frameworks are now gaining prominence in standard risk assessment procedures because of their ability to assess accurately model uncertainties. Risk assessment needs to be addressed quantitatively wherever possible, and submitted with its quality assessment in order to enable successful public health measures to be adopted. In terms of current practice, often a series of different models and analyses are applied to the same problem, with results and outcomes that are difficult to compare because of the unknown model and data uncertainties. Therefore, the risk assessment areas in need of further research are identified in this article. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Multi-hazard risk analysis related to hurricanes

NASA Astrophysics Data System (ADS)

Lin, Ning

Hurricanes present major hazards to the United States. Associated with extreme winds, heavy rainfall, and storm surge, landfalling hurricanes often cause enormous structural damage to coastal regions. Hurricane damage risk assessment provides the basis for loss mitigation and related policy-making. Current hurricane risk models, however, often oversimplify the complex processes of hurricane damage. This dissertation aims to improve existing hurricane risk assessment methodology by coherently modeling the spatial-temporal processes of storm landfall, hazards, and damage. Numerical modeling technologies are used to investigate the multiplicity of hazards associated with landfalling hurricanes. The application and effectiveness of current weather forecasting technologies to predict hurricane hazards is investigated. In particular, the Weather Research and Forecasting model (WRF), with Geophysical Fluid Dynamics Laboratory (GFDL)'s hurricane initialization scheme, is applied to the simulation of the wind and rainfall environment during hurricane landfall. The WRF model is further coupled with the Advanced Circulation (AD-CIRC) model to simulate storm surge in coastal regions. A case study examines the multiple hazards associated with Hurricane Isabel (2003). Also, a risk assessment methodology is developed to estimate the probability distribution of hurricane storm surge heights along the coast, particularly for data-scarce regions, such as New York City. This methodology makes use of relatively simple models, specifically a statistical/deterministic hurricane model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, to simulate large numbers of synthetic surge events, and conducts statistical analysis. The estimation of hurricane landfall probability and hazards are combined with structural vulnerability models to estimate hurricane damage risk. Wind-induced damage mechanisms are extensively studied. An innovative windborne debris risk model is developed based on the theory of Poisson random measure, substantiated by a large amount of empirical data. An advanced vulnerability assessment methodology is then developed, by integrating this debris risk model and a component-based pressure damage model, to predict storm-specific or annual damage to coastal residential neighborhoods. The uniqueness of this vulnerability model lies in its detailed description of the interaction between wind pressure and windborne debris effects over periods of strong winds, which is a major mechanism leading to structural failures during hurricanes.

The pediatric sepsis biomarker risk model: potential implications for sepsis therapy and biology.

PubMed

Alder, Matthew N; Lindsell, Christopher J; Wong, Hector R

2014-07-01

Sepsis remains a major cause of morbidity and mortality in adult and pediatric intensive care units. Heterogeneity of demographics, comorbidities, biological mechanisms, and severity of illness leads to difficulty in determining which patients are at highest risk of mortality. Determining mortality risk is important for weighing the potential benefits of more aggressive interventions and for deciding whom to enroll in clinical trials. Biomarkers can be used to parse patients into different risk categories and can outperform current methods of patient risk stratification based on physiologic parameters. Here we review the Pediatric Sepsis Biomarker Risk Model that has also been modified and applied to estimate mortality risk in adult patients. We compare the two models and speculate on the biological implications of the biomarkers in patients with sepsis.

Risk prediction model: Statistical and artificial neural network approach

NASA Astrophysics Data System (ADS)

Paiman, Nuur Azreen; Hariri, Azian; Masood, Ibrahim

2017-04-01

Prediction models are increasingly gaining popularity and had been used in numerous areas of studies to complement and fulfilled clinical reasoning and decision making nowadays. The adoption of such models assist physician's decision making, individual's behavior, and consequently improve individual outcomes and the cost-effectiveness of care. The objective of this paper is to reviewed articles related to risk prediction model in order to understand the suitable approach, development and the validation process of risk prediction model. A qualitative review of the aims, methods and significant main outcomes of the nineteen published articles that developed risk prediction models from numerous fields were done. This paper also reviewed on how researchers develop and validate the risk prediction models based on statistical and artificial neural network approach. From the review done, some methodological recommendation in developing and validating the prediction model were highlighted. According to studies that had been done, artificial neural network approached in developing the prediction model were more accurate compared to statistical approach. However currently, only limited published literature discussed on which approach is more accurate for risk prediction model development.

Modeling current climate conditions for forest pest risk assessment

Treesearch

Frank H. Koch; John W. Coulston

2010-01-01

Current information on broad-scale climatic conditions is essential for assessing potential distribution of forest pests. At present, sophisticated spatial interpolation approaches such as the Parameter-elevation Regressions on Independent Slopes Model (PRISM) are used to create high-resolution climatic data sets. Unfortunately, these data sets are based on 30-year...

Risk Profiling May Improve Lung Cancer Screening

Cancer.gov

A new modeling study suggests that individualized, risk-based selection of ever-smokers for lung cancer screening may prevent more lung cancer deaths and improve the effectiveness and efficiency of screening compared with current screening recommendations

Risk: The Ethics of a Creative Curriculum

ERIC Educational Resources Information Center

Hargreaves, Janet

2008-01-01

Higher education in the UK espouses to develop intelligence and critical skills in undergraduates. To do this requires exposing students to challenge and thus risk. However, current models of quality assurance are risk-averse and thus potentially limit the scope of creative learning and teaching strategies. Using two case studies, this paper…

Development of prognostic model for predicting survival after retrograde placement of ureteral stent in advanced gastrointestinal cancer patients and its evaluation by decision curve analysis.

PubMed

Kawano, Shingo; Komai, Yoshinobu; Ishioka, Junichiro; Sakai, Yasuyuki; Fuse, Nozomu; Ito, Masaaki; Kihara, Kazunori; Saito, Norio

2016-10-01

The aim of this study was to determine risk factors for survival after retrograde placement of ureteral stents and develop a prognostic model for advanced gastrointestinal tract (GIT: esophagus, stomach, colon and rectum) cancer patients. We examined the clinical records of 122 patients who underwent retrograde placement of a ureteral stent against malignant extrinsic ureteral obstruction. A prediction model for survival after stenting was developed. We compared its clinical usefulness with our previous model based on the results from nephrostomy cases by decision curve analysis. Median follow-up period was 201 days (8-1490) and 97 deaths occurred. The 1-year survival rate in this cohort was 29%. Based on multivariate analysis, primary site of colon origin, absence of retroperitoneal lymph node metastasis and serum albumin >3g/dL were significantly associated with a prolonged survival time. To develop a prognostic model, we divided the patients into 3 risk groups of favorable: 0-1 factors (N.=53), intermediate: 2 risk factors (N.=54), and poor: 3 risk factors (N.=15). There were significant differences in the survival profiles of these 3 risk groups (P<0.0001). Decision curve analyses revealed that the current model has a superior net benefit than our previous model for most of the examined probabilities. We have developed a novel prognostic model for GIT cancer patients who were treated with retrograde placement of a ureteral stent. The current model should help urologists and medical oncologists to predict survival in cases of malignant extrinsic ureteral obstruction.

What to say and how to say it: effective communication for cardiovascular disease prevention.

PubMed

Navar, Ann Marie; Stone, Neil J; Martin, Seth S

2016-09-01

Current guidelines for cholesterol treatment emphasize the importance of engaging patients in a risk-benefit discussion prior to initiating statin therapy. Although current risk prediction algorithms are well defined, there is less data on how to communicate with patients about cardiovascular disease risk, benefits of treatment, and possible adverse effects. We propose a four-part model for effective shared decision-making: 1) Assessing patient priorities, perceived risk, and prior experience with cardiovascular risk reduction; 2) Arriving at a recommendation for therapy based on the patient's risk of disease, guideline recommendations, new clinical trial data, and patient preferences; 3) Communicating this recommendation along with risks, benefits, and alternatives to therapy following best practices for discussing numeric risk; and 4) Arriving at a shared decision with the patient with ongoing reassessment as risk factors and patient priorities change.

Integrating emerging earth science technologies into disaster risk management: an enterprise architecture approach

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster risk management has grown to rely on earth observations, multi-source data analysis, numerical modeling, and interagency information sharing. The practice and outcomes of disaster risk management will likely undergo further change as several emerging earth science technologies come of age: mobile devices; location-based services; ubiquitous sensors; drones; small satellites; satellite direct readout; Big Data analytics; cloud computing; Web services for predictive modeling, semantic reconciliation, and collaboration; and many others. Integrating these new technologies well requires developing and adapting them to meet current needs; but also rethinking current practice to draw on new capabilities to reach additional objectives. This requires a holistic view of the disaster risk management enterprise and of the analytical or operational capabilities afforded by these technologies. One helpful tool for this assessment, the GEOSS Architecture for the Use of Remote Sensing Products in Disaster Management and Risk Assessment (Evans & Moe, 2013), considers all phases of the disaster risk management lifecycle for a comprehensive set of natural hazard types, and outlines common clusters of activities and their use of information and computation resources. We are using these architectural views, together with insights from current practice, to highlight effective, interrelated roles for emerging earth science technologies in disaster risk management. These roles may be helpful in creating roadmaps for research and development investment at national and international levels.

Using landscape epidemiological models to understand the distribution of chronic wasting disease in the Midwestern USA

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Rolley, Robert E.; Shelton, Paul

2013-01-01

Animal movement across the landscape plays a critical role in the ecology of infectious wildlife diseases. Dispersing animals can spread pathogens between infected areas and naïve populations. While tracking free-ranging animals over the geographic scales relevant to landscape-level disease management is challenging, landscape features that influence gene flow among wildlife populations may also influence the contact rates and disease spread between populations. We used spatial diffusion and barriers to white-tailed deer gene flow, identified through landscape genetics, to model the distribution of chronic wasting disease (CWD) in the infected region of southern Wisconsin and northern Illinois, USA. Our generalized linear model showed that risk of CWD infection declined exponentially with distance from current outbreaks, and inclusion of gene flow barriers dramatically improved fit and predictive power of the model. Our results indicate that CWD is spreading across the Midwestern landscape from these two endemic foci, but spread is strongly influenced by highways and rivers that also reduce deer gene flow. We used our model to plot a risk map, providing important information for CWD management by identifying likely routes of disease spread and providing a tool for prioritizing disease monitoring and containment efforts. The current analysis may serve as a framework for modeling future disease risk drawing on genetic information to investigate barriers to spread and extending management and monitoring beyond currently affected regions.

Arrhythmic hazard map for a 3D whole-ventricles model under multiple ion channel block.

PubMed

Okada, Jun-Ichi; Yoshinaga, Takashi; Kurokawa, Junko; Washio, Takumi; Furukawa, Tetsushi; Sawada, Kohei; Sugiura, Seiryo; Hisada, Toshiaki

2018-05-10

To date, proposed in silico models for preclinical cardiac safety testing are limited in their predictability and usability. We previously reported a multi-scale heart simulation that accurately predicts arrhythmogenic risk for benchmark drugs. We extend this approach and report the first comprehensive hazard map of drug-induced arrhythmia based on the exhaustive in silico electrocardiogram (ECG) database of drug effects, developed using a petaflop computer. A total of 9075 electrocardiograms constitute the five-dimensional hazard map, with coordinates representing the extent of the block of each of the five ionic currents (rapid delayed rectifier potassium current (IKr), fast (INa) and late (INa,L) components of the sodium current, L-type calcium current (ICa,L) and slow delayed rectifier current (IKs)), involved in arrhythmogenesis. Results of the evaluation of arrhythmogenic risk based on this hazard map agreed well with the risk assessments reported in three references. ECG database also suggested that the interval between the J-point and the T-wave peak is a superior index of arrhythmogenicity compared to other ECG biomarkers including the QT interval. Because concentration-dependent effects on electrocardiograms of any drug can be traced on this map based on in vitro current assay data, its arrhythmogenic risk can be evaluated without performing costly and potentially risky human electrophysiological assays. Hence, the map serves as a novel tool for use in pharmaceutical research and development. This article is protected by copyright. All rights reserved.

Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

PubMed Central

Ellis, Randall P.; Pope, Gregory C.; Iezzoni, Lisa I.; Ayanian, John Z.; Bates, David W.; Burstin, Helen; Ash, Arlene S.

1996-01-01

Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. PMID:10172666

Pneumococcal vaccine targeting strategy for older adults: customized risk profiling.

PubMed

Balicer, Ran D; Cohen, Chandra J; Leibowitz, Morton; Feldman, Becca S; Brufman, Ilan; Roberts, Craig; Hoshen, Moshe

2014-02-12

Current pneumococcal vaccine campaigns take a broad, primarily age-based approach to immunization targeting, overlooking many clinical and administrative considerations necessary in disease prevention and resource planning for specific patient populations. We aim to demonstrate the utility of a population-specific predictive model for hospital-treated pneumonia to direct effective vaccine targeting. Data was extracted for 1,053,435 members of an Israeli HMO, age 50 and older, during the study period 2008-2010. We developed and validated a logistic regression model to predict hospital-treated pneumonia using training and test samples, including a set of standard and population-specific risk factors. The model's predictive value was tested for prospectively identifying cases of pneumonia and invasive pneumococcal disease (IPD), and was compared to the existing international paradigm for patient immunization targeting. In a multivariate regression, age, co-morbidity burden and previous pneumonia events were most strongly positively associated with hospital-treated pneumonia. The model predicting hospital-treated pneumonia yielded a c-statistic of 0.80. Utilizing the predictive model, the top 17% highest-risk within the study validation population were targeted to detect 54% of those members who were subsequently treated for hospitalized pneumonia in the follow up period. The high-risk population identified through this model included 46% of the follow-up year's IPD cases, and 27% of community-treated pneumonia cases. These outcomes were compared with international guidelines for risk for pneumococcal diseases that accurately identified only 35% of hospitalized pneumonia, 41% of IPD cases and 21% of community-treated pneumonia. We demonstrate that a customized model for vaccine targeting performs better than international guidelines, and therefore, risk modeling may allow for more precise vaccine targeting and resource allocation than current national and international guidelines. Health care managers and policy-makers may consider the strategic potential of utilizing clinical and administrative databases for creating population-specific risk prediction models to inform vaccination campaigns. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessing cancer risk in China from γ-hexachlorocyclohexane emitted from Chinese and Indian sources.

PubMed

Xu, Yue; Tian, Chongguo; Ma, Jianmin; Wang, Xiaoping; Li, Jun; Tang, Jianhui; Chen, Yingjun; Qin, Wei; Zhang, Gan

2013-07-02

Three models, including an atmospheric transport model, a multimedia exposure model, and a risk assessment model, were used to assess cancer risk in China caused by γ-HCH (gamma-hexachlorocyclohexane) emitted from Chinese and Indian sources. Extensive model investigations revealed the contribution of different sources to the cancer risk in China. Cancer risk in Eastern China was primarily attributable to γ-HCH contamination from Chinese sources, whereas cancer risk in Western China was caused mostly by Indian emissions. The contribution of fresh use of lindane in India to the cancer risk in China was almost 1 order of magnitude higher than that of the reemission of γ-HCH from Indian soils. Of total population, 58% (about 0.79 billion) residents in China were found to live in the environment with high levels of cancer risk exceeding the acceptable cancer risk of 10(-6), recommended by the United States Environmental Protection Agency (U.S. EPA). The cancer risk in China was mostly induced by the local contamination of γ-HCH emitted from Chinese sources, whereas fresh use of lindane in India will become a significant source of the cancer risk in China if Indian emissions maintain their current levels.

Risk Assessment of Hurricane Storm Surge for Tampa Bay

NASA Astrophysics Data System (ADS)

Lin, N.; Emanuel, K.

2011-12-01

Hurricane storm surge presents a major hazard for the United States and many other coastal areas around the world. Risk assessment of current and future hurricane storm surge provides the basis for risk mitigation and related decision making. This study investigates the hurricane surge risk for Tampa Bay, located on the central west coast of Florida. Although fewer storms have made landfall in the central west Florida than in regions farther west in the Gulf of Mexico and the east coast of U.S., Tampa Bay is highly vulnerable to storm surge due to its geophysical features. It is surrounded by low-lying lands, much of which may be inundated by a storm tide of 6 m. Also, edge waves trapped on the west Florida shelf can propagate along the coastline and affect the sea level outside the area of a forced storm surge; Tampa Bay may be affected by storms traversing some distance outside the Bay. Moreover, when the propagation speed of the edge wave is close to that of a storm moving parallel to the coast, resonance may occur and the water elevation in the Bay may be greatly enhanced. Therefore, Tampa Bay is vulnerable to storms with a broad spectrum of characteristics. We apply a model-based risk assessment method to carry out the investigation. To estimate the current surge risk, we apply a statistical/deterministic hurricane model to generate a set of 1500 storms for the Tampa area, under the observed current climate (represented by 1981-2000 statistics) estimated from the NCAR/NCEP reanalysis. To study the effect of climate change, we use four climate models, CNRM-CM3, ECHAM, GFDL-CM2.0, and MIROC3.2, respectively, to drive the hurricane model to generate four sets of 1500 Tampa storms under current climate conditions (represented by 1981-2000 statistics) and another four under future climate conditions of the IPCC-AR4 A1B emission scenario (represented by 2081-2100 statistics). Then, we apply two hydrodynamic models, the Advanced Circulation (ADCIRC) model and the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model with grids of various resolutions to simulate the surges induced by the synthetic storms. The surge risk under each of the climate scenarios is depicted by a surge return level curve (exceedance probability curve). For the city of Tampa, the heights of the 100-year, 500-year, and 1000-year surges under the current climate are estimated to be 3.85, 5.66, and 6.31 m, respectively. Two of the four climate models predict that surge return periods will be significantly shortened in the future climates due to the change of storm climatology; the current 100-year surge may happen every 50 years or less, the 500-year surge every 200 years or less, and the 1000-year surge every 300 years or less. The other two climate models predict that the surge return periods will become moderately shorter or remain almost unchanged in the future climates. Extreme surges up to 12 m at Tampa appear in our simulations. Although occurring with very small probabilities, these extreme surges would have a devastating impact on the Tampa Bay area. By examining the generated synthetic surge database, we study the characteristics of the extreme storms at Tampa Bay, especially for the storms that may interact with edge waves along the Florida west coast.

Qualitative risk assessment in a data-scarce environment: a model to assess the impact of control measures on spread of African Swine Fever.

PubMed

Wieland, Barbara; Dhollander, Sofie; Salman, Mo; Koenen, Frank

2011-04-01

In the absence of data, qualitative risk assessment frameworks have proved useful to assess risks associated with animal health diseases. As part of a scientific opinion for the European Commission (EC) on African Swine Fever (ASF), a working group of the European Food Safety Authority (EFSA) assessed the risk of ASF remaining endemic in Trans Caucasus Countries (TCC) and the Russian Federation (RF) and the risk of ASF becoming endemic in the EU if disease were introduced. The aim was to develop a tool to evaluate how current control or preventive measures mitigate the risk of spread and giving decision makers the means to review how strengthening of surveillance and control measures would mitigate the risk of disease spread. Based on a generic model outlining disease introduction, spread and endemicity in a region, the impact of risk mitigation measures on spread of disease was assessed for specific risk questions. The resulting hierarchical models consisted of key steps containing several sub-steps. For each step of the risk pathways risk estimates were determined by the expert group based on existing data or through expert opinion elicitation. Risk estimates were combined using two different combination matrices, one to combine estimates of independent steps and one to combine conditional probabilities. The qualitative risk assessment indicated a moderate risk that ASF will remain endemic in current affected areas in the TCC and RF and a high risk of spread to currently unaffected areas. If introduced into the EU, ASF is likely to be controlled effectively in the production sector with high or limited biosecurity. In the free range production sector, however, there is a moderate risk of ASF becoming endemic due to wild boar contact, non-compliance with animal movement bans, and difficult access to all individual pigs upon implementation of control measures. This study demonstrated the advantages of a systematic framework to assist an expert panel to carry out a risk assessment as it helped experts to disassociate steps in the risk pathway and to overcome preconceived notions of final risk estimates. The approach presented here shows how a qualitative risk assessment framework can address animal diseases with complexity in their spread and control measures and how transparency of the resulting estimates was achieved. Copyright © 2011 Elsevier B.V. All rights reserved.

Prototype Biology-Based Radiation Risk Module Project

NASA Technical Reports Server (NTRS)

Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

2015-01-01

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Human In Silico Drug Trials Demonstrate Higher Accuracy than Animal Models in Predicting Clinical Pro-Arrhythmic Cardiotoxicity.

PubMed

Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca

2017-01-01

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na + and Ca 2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca 2+ -transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

Underground Test Area Subproject Phase I Data Analysis Task. Volume VIII - Risk Assessment Documentation Package

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

Volume VIII of the documentation for the Phase I Data Analysis Task performed in support of the current Regional Flow Model, Transport Model, and Risk Assessment for the Nevada Test Site Underground Test Area Subproject contains the risk assessment documentation. Because of the size and complexity of the model area, a considerable quantity of data was collected and analyzed in support of the modeling efforts. The data analysis task was consequently broken into eight subtasks, and descriptions of each subtask's activities are contained in one of the eight volumes that comprise the Phase I Data Analysis Documentation.

PACE and the Medicare+Choice risk-adjusted payment model.

PubMed

Temkin-Greener, H; Meiners, M R; Gruenberg, L

2001-01-01

This paper investigates the impact of the Medicare principal inpatient diagnostic cost group (PIP-DCG) payment model on the Program of All-Inclusive Care for the Elderly (PACE). Currently, more than 6,000 Medicare beneficiaries who are nursing home certifiable receive care from PACE, a program poised for expansion under the Balanced Budget Act of 1997. Overall, our analysis suggests that the application of the PIP-DCG model to the PACE program would reduce Medicare payments to PACE, on average, by 38%. The PIP-DCG payment model bases its risk adjustment on inpatient diagnoses and does not capture adequately the risk of caring for a population with functional impairments.

Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis.

PubMed

Gray, Ewan; Donten, Anna; Karssemeijer, Nico; van Gils, Carla; Evans, D Gareth; Astley, Sue; Payne, Katherine

2017-09-01

To identify the incremental costs and consequences of stratified national breast screening programs (stratified NBSPs) and drivers of relative cost-effectiveness. A decision-analytic model (discrete event simulation) was conceptualized to represent four stratified NBSPs (risk 1, risk 2, masking [supplemental screening for women with higher breast density], and masking and risk 1) compared with the current UK NBSP and no screening. The model assumed a lifetime horizon, the health service perspective to identify costs (£, 2015), and measured consequences in quality-adjusted life-years (QALYs). Multiple data sources were used: systematic reviews of effectiveness and utility, published studies reporting costs, and cohort studies embedded in existing NBSPs. Model parameter uncertainty was assessed using probabilistic sensitivity analysis and one-way sensitivity analysis. The base-case analysis, supported by probabilistic sensitivity analysis, suggested that the risk stratified NBSPs (risk 1 and risk-2) were relatively cost-effective when compared with the current UK NBSP, with incremental cost-effectiveness ratios of £16,689 per QALY and £23,924 per QALY, respectively. Stratified NBSP including masking approaches (supplemental screening for women with higher breast density) was not a cost-effective alternative, with incremental cost-effectiveness ratios of £212,947 per QALY (masking) and £75,254 per QALY (risk 1 and masking). When compared with no screening, all stratified NBSPs could be considered cost-effective. Key drivers of cost-effectiveness were discount rate, natural history model parameters, mammographic sensitivity, and biopsy rates for recalled cases. A key assumption was that the risk model used in the stratification process was perfectly calibrated to the population. This early model-based cost-effectiveness analysis provides indicative evidence for decision makers to understand the key drivers of costs and QALYs for exemplar stratified NBSP. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Risk assessment for two bird species in northern Wisconsin

Treesearch

Megan M. Friggens; Stephen N. Matthews

2012-01-01

Species distribution models for 147 bird species have been derived using climate, elevation, and distribution of current tree species as potential predictors (Matthews et al. 2011). In this case study, a risk matrix was developed for two bird species (fig. A2-5), with projected change in bird habitat (the x axis) based on models of changing suitable habitat resulting...

Cumulative Risk Disparities in Children's Neurocognitive Functioning: A Developmental Cascade Model

ERIC Educational Resources Information Center

Wade, Mark; Browne, Dillon T.; Plamondon, Andre; Daniel, Ella; Jenkins, Jennifer M.

2016-01-01

The current longitudinal study examined the role of cumulative social risk on children's theory of mind (ToM) and executive functioning (EF) across early development. Further, we also tested a cascade model of development in which children's social cognition at 18 months was hypothesized to predict ToM and EF at age 4.5 through intermediary…

[The genetics of thrombosis in cancer].

PubMed

Soria, José Manuel; López, Sonia

2015-01-01

Venous thromboembolism (VTE) is a multifactorial and complex disease in which the interaction of genetic factors (estimated at 60%) and environmental factors (e.g., the use of oral contraceptives, pregnancy, immobility and cancer) determine the risk of thrombosis for each individual. In particular, the association between thrombosis and cancer is well established. Approximately 20% of patients with cancer develop a thromboembolic event over the course of the natural history of the tumor process, with thrombosis being the second leading cause of death for these patients. One of the greatest challenges currently facing the field of oncology is the identification of patients at high risk of VTE who can benefit from thromboprophylaxis. Currently, there is a VTE risk prediction model for patients with cancer (the Khorana risk score); however, its ability to identify patients at high risk is very low. It is important to note that this score, which is based on five clinical parameters, ignores the genetic variability associated with VTE risk. In this article, we present the preliminary results of the Oncothromb study, whose objective is to develop an individual VTE risk prediction model for patients with cancer who are treated with outpatient chemotherapy. Our model includes the clinical and genetic data on each patient (Thrombo inCode(®) genetic profile). Only by integrating multiple layers of biological information (clinical, plasmatic and genetic) we could obtain models that provide accurate information as to which patients are at high risk of developing a thromboembolic event associated with cancer so as to take appropriate prophylactic measures. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Risk of Incident Diabetes Mellitus Associated With the Dosage and Duration of Oral Glucocorticoid Therapy in Patients With Rheumatoid Arthritis

PubMed Central

Movahedi, Mohammad; Beauchamp, Marie‐Eve; Abrahamowicz, Michal; Ray, David W.; Michaud, Kaleb; Pedro, Sofia

2016-01-01

Objective To quantify the risk of incident diabetes mellitus (DM) associated with the dosage, duration, and timing of glucocorticoid (GC) use in patients with rheumatoid arthritis (RA). Methods We undertook a cohort study using 2 databases: a UK primary care database (the Clinical Practice Research Datalink [CPRD]) including 21,962 RA patients (1992–2009) and the US National Data Bank for Rheumatic Diseases (NDB) including 12,657 RA patients (1998–2013). Information on the dosage and timing of GC use was extracted. DM in the CPRD was defined using Read codes, at least 2 prescriptions for oral antidiabetic medication, or abnormal blood test results. DM in the NDB was defined through patient self‐reports. Data were analyzed using time‐dependent Cox models and a novel weighted cumulative dose (WCD) model that accounts for dosage, duration, and timing of treatment. Results The hazard ratio (HR) was 1.30 (95% confidence interval [95% CI] 1.17–1.45) and 1.61 (95% CI 1.37–1.89) in current GC users compared to nonusers in the CPRD and the NDB, respectively. A range of conventional statistical models consistently confirmed increases in risk with the GC dosage and duration. The WCD model showed that recent GC use contributed the most to the current risk of DM, while doses taken >6 months previously did not influence current risk. In the CPRD, 5 mg of prednisolone equivalent dose for the last 1, 3, and 6 months was significantly associated with HRs of 1.20, 1.43, and 1.48, respectively, compared to nonusers. Conclusion GC use is a clinically important and quantifiable risk factor for DM. Risk is influenced by the dosage and treatment duration, although only for GC use within the last 6 months. PMID:26663814

Lung Cancer Screening May Benefit Those at Highest Risk

Cancer.gov

People at the highest risk for lung cancer, based on a risk model, may be more likely to benefit from screening with low-dose CT, a new analysis suggests. The study authors believe the findings may better define who should undergo lung cancer screening, as this Cancer Currents blog post explains.

Using Computational Approaches to Improve Risk-Stratified Patient Management: Rationale and Methods

PubMed Central

Stone, Bryan L; Sakaguchi, Farrant; Sheng, Xiaoming; Murtaugh, Maureen A

2015-01-01

Background Chronic diseases affect 52% of Americans and consume 86% of health care costs. A small portion of patients consume most health care resources and costs. More intensive patient management strategies, such as case management, are usually more effective at improving health outcomes, but are also more expensive. To use limited resources efficiently, risk stratification is commonly used in managing patients with chronic diseases, such as asthma, chronic obstructive pulmonary disease, diabetes, and heart disease. Patients are stratified based on predicted risk with patients at higher risk given more intensive care. The current risk-stratified patient management approach has 3 limitations resulting in many patients not receiving the most appropriate care, unnecessarily increased costs, and suboptimal health outcomes. First, using predictive models for health outcomes and costs is currently the best method for forecasting individual patient’s risk. Yet, accuracy of predictive models remains poor causing many patients to be misstratified. If an existing model were used to identify candidate patients for case management, enrollment would miss more than half of those who would benefit most, but include others unlikely to benefit, wasting limited resources. Existing models have been developed under the assumption that patient characteristics primarily influence outcomes and costs, leaving physician characteristics out of the models. In reality, both characteristics have an impact. Second, existing models usually give neither an explanation why a particular patient is predicted to be at high risk nor suggestions on interventions tailored to the patient’s specific case. As a result, many high-risk patients miss some suitable interventions. Third, thresholds for risk strata are suboptimal and determined heuristically with no quality guarantee. Objective The purpose of this study is to improve risk-stratified patient management so that more patients will receive the most appropriate care. Methods This study will (1) combine patient, physician profile, and environmental variable features to improve prediction accuracy of individual patient health outcomes and costs; (2) develop the first algorithm to explain prediction results and suggest tailored interventions; (3) develop the first algorithm to compute optimal thresholds for risk strata; and (4) conduct simulations to estimate outcomes of risk-stratified patient management for various configurations. The proposed techniques will be demonstrated on a test case of asthma patients. Results We are currently in the process of extracting clinical and administrative data from an integrated health care system’s enterprise data warehouse. We plan to complete this study in approximately 5 years. Conclusions Methods developed in this study will help transform risk-stratified patient management for better clinical outcomes, higher patient satisfaction and quality of life, reduced health care use, and lower costs. PMID:26503357

Climate change effects on wildland fire risk in the Northeastern and Great Lakes states predicted by a downscaled multi-model ensemble

NASA Astrophysics Data System (ADS)

Kerr, Gaige Hunter; DeGaetano, Arthur T.; Stoof, Cathelijne R.; Ward, Daniel

2018-01-01

This study is among the first to investigate wildland fire risk in the Northeastern and the Great Lakes states under a changing climate. We use a multi-model ensemble (MME) of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) together with the Canadian Forest Fire Weather Index System (CFFWIS) to understand changes in wildland fire risk through differences between historical simulations and future projections. Our results are relatively homogeneous across the focus region and indicate modest increases in the magnitude of fire weather indices (FWIs) during northern hemisphere summer. The most pronounced changes occur in the date of the initialization of CFFWIS and peak of the wildland fire season, which in the future are trending earlier in the year, and in the significant increases in the length of high-risk episodes, defined by the number of consecutive days with FWIs above the current 95th percentile. Further analyses show that these changes are most closely linked to expected changes in the focus region's temperature and precipitation. These findings relate to the current understanding of particulate matter vis-à-vis wildfires and have implications for human health and local and regional changes in radiative forcings. When considering current fire management strategies which could be challenged by increasing wildland fire risk, fire management agencies could adapt new strategies to improve awareness, prevention, and resilience to mitigate potential impacts to critical infrastructure and population.

A Revised Framingham Stroke Risk Profile to Reflect Temporal Trends

PubMed Central

Dufouil, Carole; Beiser, Alexa; McLure, Leslie A.; Wolf, Philip A.; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J.; Himali, Jayandra J.; Sullivan, Lisa; Aparicio, Hugo J.; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S.; Pikula, Aleksandra; Romero, Jose R.; D’Agostino, Ralph B.; Samieri, Cécilia; Vasan, Ramachandran S.; Chêne, Genevieve; Howard, George; Seshadri, Sudha

2017-01-01

Background Age-adjusted stroke incidence has decreased over the past 50 years, likely due to changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the Framingham Heart Study (FHS) and other cohorts. We compared the accuracy of the standard (Old), and of a revised (New) version of the FSRP in predicting the risk of all-stroke and ischemic stroke, and validated this new FSRP in two external cohorts, the 3 Cities (3C) and REGARDS studies. Methods We computed the old FSRP as originally described, and a new model that used the most recent epoch-specific risk factors' prevalence and hazard-ratios for persons ≥ 55 years and for the subsample ≥ 65 years (to match the age range in REGARDS and 3C studies respectively), and compared the efficacy of these models in predicting 5- and 10-year stroke risks. Results The new FSRP was a better predictor of current stroke risks in all three samples than the old FSRP (Calibration chi-squares of new/old FSRP: in men 64.0/12.1, 59.4/30.6 and 20.7/12.5; in women 42.5/4.1, 115.4/90.3 and 9.8/6.5 in FHS, REGARDS and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared to blacks. Conclusions A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. PMID:28159800

Revised Framingham Stroke Risk Profile to Reflect Temporal Trends.

PubMed

Dufouil, Carole; Beiser, Alexa; McLure, Leslie A; Wolf, Philip A; Tzourio, Christophe; Howard, Virginia J; Westwood, Andrew J; Himali, Jayandra J; Sullivan, Lisa; Aparicio, Hugo J; Kelly-Hayes, Margaret; Ritchie, Karen; Kase, Carlos S; Pikula, Aleksandra; Romero, Jose R; D'Agostino, Ralph B; Samieri, Cécilia; Vasan, Ramachandran S; Chêne, Genevieve; Howard, George; Seshadri, Sudha

2017-03-21

Age-adjusted stroke incidence has decreased over the past 50 years, likely as a result of changes in the prevalence and impact of various stroke risk factors. An updated version of the Framingham Stroke Risk Profile (FSRP) might better predict current risks in the FHS (Framingham Heart Study) and other cohorts. We compared the accuracy of the standard (old) and of a revised (new) version of the FSRP in predicting the risk of all-stroke and ischemic stroke and validated this new FSRP in 2 external cohorts, the 3C (3 Cities) and REGARDS (Reasons for Geographic and Racial Differences in Stroke) studies. We computed the old FSRP as originally described and a new model that used the most recent epoch-specific risk factor prevalence and hazard ratios for individuals ≥55 years of age and for the subsample ≥65 years of age (to match the age range in REGARDS and 3C studies, respectively) and compared the efficacy of these models in predicting 5- and 10-year stroke risks. The new FSRP was a better predictor of current stroke risks in all 3 samples than the old FSRP (calibration χ 2 of new/old FSRP: in men: 64.0/12.1, 59.4/30.6, and 20.7/12.5; in women: 42.5/4.1, 115.4/90.3, and 9.8/6.5 in FHS, REGARDS, and 3C, respectively). In the REGARDS, the new FSRP was a better predictor among whites compared with blacks. A more contemporaneous, new FSRP better predicts current risks in 3 large community samples and could serve as the basis for examining geographic and racial differences in stroke risk and the incremental diagnostic utility of novel stroke risk factors. © 2017 American Heart Association, Inc.

Enhancing Interdisciplinary Human System Risk Research Through Modeling and Network Approaches

NASA Technical Reports Server (NTRS)

Mindock, Jennifer; Lumpkins, Sarah; Shelhamer, Mark

2015-01-01

NASA's Human Research Program (HRP) supports research to reduce human health and performance risks inherent in future human space exploration missions. Understanding risk outcomes and contributing factors in an integrated manner allows HRP research to support development of efficient and effective mitigations from cross-disciplinary perspectives, and to enable resilient human and engineered systems for spaceflight. The purpose of this work is to support scientific collaborations and research portfolio management by utilizing modeling for analysis and visualization of current and potential future interdisciplinary efforts.

Defending Against Advanced Persistent Threats Using Game-Theory

PubMed Central

König, Sandra; Schauer, Stefan

2017-01-01

Advanced persistent threats (APT) combine a variety of different attack forms ranging from social engineering to technical exploits. The diversity and usual stealthiness of APT turns them into a central problem of contemporary practical system security, since information on attacks, the current system status or the attacker’s incentives is often vague, uncertain and in many cases even unavailable. Game theory is a natural approach to model the conflict between the attacker and the defender, and this work investigates a generalized class of matrix games as a risk mitigation tool for an advanced persistent threat (APT) defense. Unlike standard game and decision theory, our model is tailored to capture and handle the full uncertainty that is immanent to APTs, such as disagreement among qualitative expert risk assessments, unknown adversarial incentives and uncertainty about the current system state (in terms of how deeply the attacker may have penetrated into the system’s protective shells already). Practically, game-theoretic APT models can be derived straightforwardly from topological vulnerability analysis, together with risk assessments as they are done in common risk management standards like the ISO 31000 family. Theoretically, these models come with different properties than classical game theoretic models, whose technical solution presented in this work may be of independent interest. PMID:28045922

. Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability

USGS Publications Warehouse

Gentile, J.H.; Harwell, M.A.; Cropper, W.; Harwell, C. C.; DeAngelis, Donald L.; Davis, S.; Ogden, J.C.; Lirman, D.

2001-01-01

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.

Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability.

PubMed

Gentile, J H; Harwell, M A; Cropper, W; Harwell, C C; DeAngelis, D; Davis, S; Ogden, J C; Lirman, D

2001-07-02

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability, and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.

Evaluating the risk of water distribution system failure: A shared frailty model

NASA Astrophysics Data System (ADS)

Clark, Robert M.; Thurnau, Robert C.

2011-12-01

Condition assessment (CA) Modeling is drawing increasing interest as a technique that can assist in managing drinking water infrastructure. This paper develops a model based on the application of a Cox proportional hazard (PH)/shared frailty model and applies it to evaluating the risk of failure in drinking water networks using data from the Laramie Water Utility (located in Laramie, Wyoming, USA). Using the risk model a cost/ benefit analysis incorporating the inspection value method (IVM), is used to assist in making improved repair, replacement and rehabilitation decisions for selected drinking water distribution system pipes. A separate model is developed to predict failures in prestressed concrete cylinder pipe (PCCP). Various currently available inspection technologies are presented and discussed.

Review and comparison between the Wells-Riley and dose-response approaches to risk assessment of infectious respiratory diseases.

PubMed

Sze To, G N; Chao, C Y H

2010-02-01

Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells-Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose-response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells-Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose-response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed. This review article summarizes the strengths and limitations of the Wells-Riley and the dose-response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells-Riley model and dose-response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment.

Climate, Deer, Rodents, and Acorns as Determinants of Variation in Lyme-Disease Risk

PubMed Central

Canham, Charles D; Oggenfuss, Kelly; Winchcombe, Raymond J; Keesing, Felicia

2006-01-01

Risk of human exposure to vector-borne zoonotic pathogens is a function of the abundance and infection prevalence of vectors. We assessed the determinants of Lyme-disease risk (density and Borrelia burgdorferi-infection prevalence of nymphal Ixodes scapularis ticks) over 13 y on several field plots within eastern deciduous forests in the epicenter of US Lyme disease (Dutchess County, New York). We used a model comparison approach to simultaneously test the importance of ambient growing-season temperature, precipitation, two indices of deer (Odocoileus virginianus) abundance, and densities of white-footed mice (Peromyscus leucopus), eastern chipmunks (Tamias striatus), and acorns ( Quercus spp.), in both simple and multiple regression models, in predicting entomological risk. Indices of deer abundance had no predictive power, and precipitation in the current year and temperature in the prior year had only weak effects on entomological risk. The strongest predictors of a current year's risk were the prior year's abundance of mice and chipmunks and abundance of acorns 2 y previously. In no case did inclusion of deer or climate variables improve the predictive power of models based on rodents, acorns, or both. We conclude that interannual variation in entomological risk of exposure to Lyme disease is correlated positively with prior abundance of key hosts for the immature stages of the tick vector and with critical food resources for those hosts. PMID:16669698

Drugs to Treat Systemic Lupus Erythematosus: Relationship between Current Use and Cardiovascular Risk Factors

PubMed Central

Rho, Young Hee; Oeser, Annette; Chung, Cecilia P; Morrow, Jason D; Stein, C Michael

2008-01-01

Objectives Cardiovascular risk is increased in patients with systemic lupus erythematosus (SLE). Drugs used to treat SLE can modify traditional cardiovascular risk factors. We examined the effect of selected drugs used in the treatment of SLE on cardiovascular risk factors. Methods We compared systolic and diastolic blood pressure, serum lipid concentrations, glucose, homocysteine, and urinary F2-isoprostane concentrations in 99 patients with lupus who were either current users or non-users of systemic corticosteroids, antimalarials, non-steroidal anti-inflammatory drugs (NSAIDs), COX-2 selective NSAIDs, azathioprine, and methotrexate. Multivariable adjustment was done with linear regression modeling using sex, age and disease activity (SLEDAI) as controlling variables. Results Serum triglyceride concentrations were higher (135.1 ± 61.4 vs. 95.3 ± 47.5 mg/dL, adjusted P = 0.003) in patients receiving corticosteroids. Homocysteine concentrations were marginally higher in patients receiving methotrexate (adjusted P = 0.08). Current use of either NSAIDs or COX-2 inhibitors was not associated with increased cardiovascular risk factors. Current hydroxychloroquine use was not associated with significant alterations in lipid profiles. Conclusions In a non-random sample of patients with SLE, current corticosteroid use was associated with increased triglyceride concentrations, but other drugs had little effect on traditional cardiovascular risk factors. PMID:20157365

Space Radiation Cancer Risk Projections and Uncertainties - 2010

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Kim, Myung-Hee Y.; Chappell, Lori J.

2011-01-01

Uncertainties in estimating health risks from galactic cosmic rays greatly limit space mission lengths and potential risk mitigation evaluations. NASA limits astronaut exposures to a 3% risk of exposure-induced death and protects against uncertainties using an assessment of 95% confidence intervals in the projection model. Revisions to this model for lifetime cancer risks from space radiation and new estimates of model uncertainties are described here. We review models of space environments and transport code predictions of organ exposures, and characterize uncertainties in these descriptions. We summarize recent analysis of low linear energy transfer radio-epidemiology data, including revision to Japanese A-bomb survivor dosimetry, longer follow-up of exposed cohorts, and reassessments of dose and dose-rate reduction effectiveness factors. We compare these projections and uncertainties with earlier estimates. Current understanding of radiation quality effects and recent data on factors of relative biological effectiveness and particle track structure are reviewed. Recent radiobiology experiment results provide new information on solid cancer and leukemia risks from heavy ions. We also consider deviations from the paradigm of linearity at low doses of heavy ions motivated by non-targeted effects models. New findings and knowledge are used to revise the NASA risk projection model for space radiation cancer risks.

Risk to Water Security on Small Islands

NASA Astrophysics Data System (ADS)

Holding, S. T.; Allen, D. M.

2013-12-01

The majority of fresh water available on small islands is shallow groundwater that forms a freshwater lens. Freshwater lenses are generally limited in extent and as such are vulnerable to many stressors that impact water security. These include stressors related to climate change, such as sea level rise, as well as those related to human impacts, such as contamination. Traditionally, water security assessments have focussed on indicators that provide a snapshot of the current condition. However, recent work suggests that in order to effectively manage the water system, it is also important to consider uncertain future impacts to the system by evaluating how different stressors might impact water security. In this study, a framework for assessing risk to water security was developed and tested on Andros Island in The Bahamas. The assessment comprises two main components that characterise the water system: numerical modelling studies and a hazard survey. A baseline numerical model of the freshwater lens throughout Andros Island was developed to simulate the morphology of the freshwater lens and estimate the freshwater resources currently available. The model was prepared using SEAWAT, a density-dependent flow and solute transport code. Various stressors were simulated in the model to evaluate the response of the freshwater lens to predicted future shifts in climate patterns, sea level rise, and changes in water use. A hazard survey was also conducted on the island to collect information related to the storage of contaminants, sanitation infrastructure, waste disposal practices and groundwater abstraction rates. The results of the survey form a geo-spatial database of the location and associated hazards to the freshwater lens. The resulting risk framework provides a ranking of overall risk to water security based on information from the numerical modelling and hazard survey. The risk framework is implemented in a Geographic Information System (GIS) and provides a map of the risk to water security throughout Andros Island. It evaluates risk to water security for current and future scenarios and will enable water resource managers to effectively adapt to future impacts on water security.

[Spanish adolescents' low perception of risk in alcohol consumption].

PubMed

Suárez-Relinque, Cristian; Arroyo, Gonzalo Del Moral; Ferrer, Belén Martínez; Ochoa, Gonzalo Musitu

2017-08-07

According to recent studies, Spanish adolescents show low perception of risk in alcohol consumption. The current study aims to analyze the factors that favor this low perception based on the opinion of a group of 32 professional experts on adolescence, family, school, mass media, and local policies. A qualitative methodology was used, based on Grounded Theory, using information from 5 focus groups guided by semi-structured interviews. Twelve factors or subcategories were identified, grouped in 4 general categories: short-term risk, immediacy, and perception of invulnerability ("adolescent thinking" category); benevolent view of alcohol, normalization of consumption, and alcohol-entertainment binomial ("social norms" category); parents' habitual consumption, verbal/non-verbal inconsistency in parental model, risk-free consumption depicted in the mass media, consumption with positive results in the media ("social models" category); and excessive health content, long-term risk ("preventive discourse" category). After discussing the results in the context of the current scientific literature, the article offers various proposals for increasing risk perception in adolescents: stronger impact of contents on short-term risks of alcohol; educational strategies targeted to adolescents to include agents of socialization, especially parents; and policies centered on the substance and reduction of supply.

Prediction of Coronary Artery Disease Risk Based on Multiple Longitudinal Biomarkers

PubMed Central

Yang, Lili; Yu, Menggang; Gao, Sujuan

2016-01-01

In the last decade, few topics in the area of cardiovascular disease (CVD) research have received as much attention as risk prediction. One of the well documented risk factors for CVD is high blood pressure (BP). Traditional CVD risk prediction models consider BP levels measured at a single time and such models form the basis for current clinical guidelines for CVD prevention. However, in clinical practice, BP levels are often observed and recorded in a longitudinal fashion. Information on BP trajectories can be powerful predictors for CVD events. We consider joint modeling of time to coronary artery disease and individual longitudinal measures of systolic and diastolic BPs in a primary care cohort with up to 20 years of follow-up. We applied novel prediction metrics to assess the predictive performance of joint models. Predictive performances of proposed joint models and other models were assessed via simulations and illustrated using the primary care cohort. PMID:26439685

Ferrets as Models for Influenza Virus Transmission Studies and Pandemic Risk Assessments

PubMed Central

Barclay, Wendy; Barr, Ian; Fouchier, Ron A.M.; Matsuyama, Ryota; Nishiura, Hiroshi; Peiris, Malik; Russell, Charles J.; Subbarao, Kanta; Zhu, Huachen

2018-01-01

The ferret transmission model is extensively used to assess the pandemic potential of emerging influenza viruses, yet experimental conditions and reported results vary among laboratories. Such variation can be a critical consideration when contextualizing results from independent risk-assessment studies of novel and emerging influenza viruses. To streamline interpretation of data generated in different laboratories, we provide a consensus on experimental parameters that define risk-assessment experiments of influenza virus transmissibility, including disclosure of variables known or suspected to contribute to experimental variability in this model, and advocate adoption of more standardized practices. We also discuss current limitations of the ferret transmission model and highlight continued refinements and advances to this model ongoing in laboratories. Understanding, disclosing, and standardizing the critical parameters of ferret transmission studies will improve the comparability and reproducibility of pandemic influenza risk assessment and increase the statistical power and, perhaps, accuracy of this model. PMID:29774862

Multifactorial disease risk calculator: Risk prediction for multifactorial disease pedigrees.

PubMed

Campbell, Desmond D; Li, Yiming; Sham, Pak C

2018-03-01

Construction of multifactorial disease models from epidemiological findings and their application to disease pedigrees for risk prediction is nontrivial for all but the simplest of cases. Multifactorial Disease Risk Calculator is a web tool facilitating this. It provides a user-friendly interface, extending a reported methodology based on a liability-threshold model. Multifactorial disease models incorporating all the following features in combination are handled: quantitative risk factors (including polygenic scores), categorical risk factors (including major genetic risk loci), stratified age of onset curves, and the partition of the population variance in disease liability into genetic, shared, and unique environment effects. It allows the application of such models to disease pedigrees. Pedigree-related outputs are (i) individual disease risk for pedigree members, (ii) n year risk for unaffected pedigree members, and (iii) the disease pedigree's joint liability distribution. Risk prediction for each pedigree member is based on using the constructed disease model to appropriately weigh evidence on disease risk available from personal attributes and family history. Evidence is used to construct the disease pedigree's joint liability distribution. From this, lifetime and n year risk can be predicted. Example disease models and pedigrees are provided at the website and are used in accompanying tutorials to illustrate the features available. The website is built on an R package which provides the functionality for pedigree validation, disease model construction, and risk prediction. Website: http://grass.cgs.hku.hk:3838/mdrc/current. © 2017 WILEY PERIODICALS, INC.

Upcoming Environmental Modeling in Ground Water Public Meeting

EPA Pesticide Factsheets

This meeting provides a public forum for pesticide registrants, other stakeholders and EPA to discuss current issues related to modeling pesticide fate, transport, and exposure for pesticide risk assessments in a regulatory context.

Understanding cancer development processes after HZE-particle exposure: roles of ROS, DNA damage repair and inflammation.

PubMed

Sridharan, D M; Asaithamby, A; Bailey, S M; Costes, S V; Doetsch, P W; Dynan, W S; Kronenberg, A; Rithidech, K N; Saha, J; Snijders, A M; Werner, E; Wiese, C; Cucinotta, F A; Pluth, J M

2015-01-01

During space travel astronauts are exposed to a variety of radiations, including galactic cosmic rays composed of high-energy protons and high-energy charged (HZE) nuclei, and solar particle events containing low- to medium-energy protons. Risks from these exposures include carcinogenesis, central nervous system damage and degenerative tissue effects. Currently, career radiation limits are based on estimates of fatal cancer risks calculated using a model that incorporates human epidemiological data from exposed populations, estimates of relative biological effectiveness and dose-response data from relevant mammalian experimental models. A major goal of space radiation risk assessment is to link mechanistic data from biological studies at NASA Space Radiation Laboratory and other particle accelerators with risk models. Early phenotypes of HZE exposure, such as the induction of reactive oxygen species, DNA damage signaling and inflammation, are sensitive to HZE damage complexity. This review summarizes our current understanding of critical areas within the DNA damage and oxidative stress arena and provides insight into their mechanistic interdependence and their usefulness in accurately modeling cancer and other risks in astronauts exposed to space radiation. Our ultimate goals are to examine potential links and crosstalk between early response modules activated by charged particle exposure, to identify critical areas that require further research and to use these data to reduced uncertainties in modeling cancer risk for astronauts. A clearer understanding of the links between early mechanistic aspects of high-LET response and later surrogate cancer end points could reveal key nodes that can be therapeutically targeted to mitigate the health effects from charged particle exposures.

Sex-Specific Pathways to Early Puberty, Sexual Debut, and Sexual Risk Taking: Tests of an Integrated Evolutionary-Developmental Model

ERIC Educational Resources Information Center

James, Jenee; Ellis, Bruce J.; Schlomer, Gabriel L.; Garber, Judy

2012-01-01

The current study tested sex-specific pathways to early puberty, sexual debut, and sexual risk taking, as specified by an integrated evolutionary-developmental model of adolescent sexual development and behavior. In a prospective study of 238 adolescents (n = 129 girls and n = 109 boys) followed from approximately 12-18 years of age, we tested for…

Factor Structure and Stability of Smoking-Related Health Beliefs in the National Lung Screening Trial

PubMed Central

Koblitz, Amber R.; Persoskie, Alexander; Ferrer, Rebecca A.; Klein, William M. P.; Dwyer, Laura A.; Park, Elyse R.

2016-01-01

Introduction: Absolute and comparative risk perceptions, worry, perceived severity, perceived benefits, and self-efficacy are important theoretical determinants of tobacco use, but no measures have been validated to ensure the discriminant validity as well as test-retest reliability of these measures in the tobacco context. The purpose of the current study is to examine the reliability and factor structure of a measure assessing smoking-related health cognitions and emotions in a national sample of current and former heavy smokers in the National Lung Screening Trial. Methods: A sub-study of the National Lung Screening Trial assessed current and former smokers’ (age 55–74; N = 4379) self-reported health cognitions and emotions at trial enrollment and at 12-month follow-up. Items were derived from the Health Belief Model and Self-Regulation Model. Results: An exploratory factor analysis of baseline responses revealed a five-factor structure for former smokers (risk perceptions, worry, perceived severity, perceived benefits, and self-efficacy) and a six-factor structure for current smokers, such that absolute risk and comparative risk perceptions emerged as separate factors. A confirmatory factor analysis of 12-month follow-up responses revealed a good fit for the five latent constructs for former smokers and six latent constructs for current smokers. Longitudinal stability of these constructs was also demonstrated. Conclusions: This is the first study to examine tobacco-related health cognition and emotional constructs over time in current and former heavy smokers undergoing lung screening. This study found that the theoretical constructs were stable across time and that the factor structure differed based on smoking status (current vs. former). PMID:25964503

Stratospheric controlled perturbation experiment: a small-scale experiment to improve understanding of the risks of solar geoengineering

PubMed Central

Dykema, John A.; Keith, David W.; Anderson, James G.; Weisenstein, Debra

2014-01-01

Although solar radiation management (SRM) through stratospheric aerosol methods has the potential to mitigate impacts of climate change, our current knowledge of stratospheric processes suggests that these methods may entail significant risks. In addition to the risks associated with current knowledge, the possibility of ‘unknown unknowns’ exists that could significantly alter the risk assessment relative to our current understanding. While laboratory experimentation can improve the current state of knowledge and atmospheric models can assess large-scale climate response, they cannot capture possible unknown chemistry or represent the full range of interactive atmospheric chemical physics. Small-scale, in situ experimentation under well-regulated circumstances can begin to remove some of these uncertainties. This experiment—provisionally titled the stratospheric controlled perturbation experiment—is under development and will only proceed with transparent and predominantly governmental funding and independent risk assessment. We describe the scientific and technical foundation for performing, under external oversight, small-scale experiments to quantify the risks posed by SRM to activation of halogen species and subsequent erosion of stratospheric ozone. The paper's scope includes selection of the measurement platform, relevant aspects of stratospheric meteorology, operational considerations and instrument design and engineering. PMID:25404681

Stratospheric controlled perturbation experiment: a small-scale experiment to improve understanding of the risks of solar geoengineering.

PubMed

Dykema, John A; Keith, David W; Anderson, James G; Weisenstein, Debra

2014-12-28

Although solar radiation management (SRM) through stratospheric aerosol methods has the potential to mitigate impacts of climate change, our current knowledge of stratospheric processes suggests that these methods may entail significant risks. In addition to the risks associated with current knowledge, the possibility of 'unknown unknowns' exists that could significantly alter the risk assessment relative to our current understanding. While laboratory experimentation can improve the current state of knowledge and atmospheric models can assess large-scale climate response, they cannot capture possible unknown chemistry or represent the full range of interactive atmospheric chemical physics. Small-scale, in situ experimentation under well-regulated circumstances can begin to remove some of these uncertainties. This experiment-provisionally titled the stratospheric controlled perturbation experiment-is under development and will only proceed with transparent and predominantly governmental funding and independent risk assessment. We describe the scientific and technical foundation for performing, under external oversight, small-scale experiments to quantify the risks posed by SRM to activation of halogen species and subsequent erosion of stratospheric ozone. The paper's scope includes selection of the measurement platform, relevant aspects of stratospheric meteorology, operational considerations and instrument design and engineering.

Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample

PubMed Central

Higgins, Stephen T.; Kurti, Allison N.; Redner, Ryan; White, Thomas J.; Keith, Diana R.; Gaalema, Diann E.; Sprague, Brian L.; Stanton, Cassandra A.; Roberts, Megan E.; Doogan, Nathan J.; Priest, Jeff S.

2016-01-01

Introduction Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample. Methods Data were obtained from 114,426 adults (≥ 18 years) in the U.S. National Survey on Drug Use and Health (years 2011–13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness). Results Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population. Conclusions These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined. PMID:26902875

Clinical Implications in the Treatment of Mania: Reducing Risk Behavior in Manic Patients

ERIC Educational Resources Information Center

Leahy, Robert L.

2005-01-01

Bipolar individuals engage in risky behavior during manic phases that contributes to their vulnerability to regret during their depressive phases. A cognitive model of risk assessment is proposed in which manic risk assessment is based on exaggeration of current and future resources, high utility for gains, low demands for information to assess…

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Thio, H. K.; Løvholt, F.; Harbitz, C. B.; Polet, J.; Lorito, S.; Basili, R.; Volpe, M.; Romano, F.; Selva, J.; Piatanesi, A.; Davies, G.; Griffin, J.; Baptista, M. A.; Omira, R.; Babeyko, A. Y.; Power, W. L.; Salgado Gálvez, M.; Behrens, J.; Yalciner, A. C.; Kanoglu, U.; Pekcan, O.; Ross, S.; Parsons, T.; LeVeque, R. J.; Gonzalez, F. I.; Paris, R.; Shäfer, A.; Canals, M.; Fraser, S. A.; Wei, Y.; Weiss, R.; Zaniboni, F.; Papadopoulos, G. A.; Didenkulova, I.; Necmioglu, O.; Suppasri, A.; Lynett, P. J.; Mokhtari, M.; Sørensen, M.; von Hillebrandt-Andrade, C.; Aguirre Ayerbe, I.; Aniel-Quiroga, Í.; Guillas, S.; Macias, J.

2016-12-01

The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Lorito, S.; Basili, R.; Harbitz, C. B.; Løvholt, F.; Polet, J.; Thio, H. K.

2017-12-01

The tsunamis occurred worldwide in the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but often disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

The Global Tsunami Model (GTM)

NASA Astrophysics Data System (ADS)

Løvholt, Finn

2017-04-01

The large tsunami disasters of the last two decades have highlighted the need for a thorough understanding of the risk posed by relatively infrequent but disastrous tsunamis and the importance of a comprehensive and consistent methodology for quantifying the hazard. In the last few years, several methods for probabilistic tsunami hazard analysis have been developed and applied to different parts of the world. In an effort to coordinate and streamline these activities and make progress towards implementing the Sendai Framework of Disaster Risk Reduction (SFDRR) we have initiated a Global Tsunami Model (GTM) working group with the aim of i) enhancing our understanding of tsunami hazard and risk on a global scale and developing standards and guidelines for it, ii) providing a portfolio of validated tools for probabilistic tsunami hazard and risk assessment at a range of scales, and iii) developing a global tsunami hazard reference model. This GTM initiative has grown out of the tsunami component of the Global Assessment of Risk (GAR15), which has resulted in an initial global model of probabilistic tsunami hazard and risk. Started as an informal gathering of scientists interested in advancing tsunami hazard analysis, the GTM is currently in the process of being formalized through letters of interest from participating institutions. The initiative has now been endorsed by the United Nations International Strategy for Disaster Reduction (UNISDR) and the World Bank's Global Facility for Disaster Reduction and Recovery (GFDRR). We will provide an update on the state of the project and the overall technical framework, and discuss the technical issues that are currently being addressed, including earthquake source recurrence models, the use of aleatory variability and epistemic uncertainty, and preliminary results for a probabilistic global hazard assessment, which is an update of the model included in UNISDR GAR15.

Assessing predation risk: optimal behaviour and rules of thumb.

PubMed

Welton, Nicky J; McNamara, John M; Houston, Alasdair I

2003-12-01

We look at a simple model in which an animal makes behavioural decisions over time in an environment in which all parameters are known to the animal except predation risk. In the model there is a trade-off between gaining information about predation risk and anti-predator behaviour. All predator attacks lead to death for the prey, so that the prey learns about predation risk by virtue of the fact that it is still alive. We show that it is not usually optimal to behave as if the current unbiased estimate of the predation risk is its true value. We consider two different ways to model reproduction; in the first scenario the animal reproduces throughout its life until it dies, and in the second scenario expected reproductive success depends on the level of energy reserves the animal has gained by some point in time. For both of these scenarios we find results on the form of the optimal strategy and give numerical examples which compare optimal behaviour with behaviour under simple rules of thumb. The numerical examples suggest that the value of the optimal strategy over the rules of thumb is greatest when there is little current information about predation risk, learning is not too costly in terms of predation, and it is energetically advantageous to learn about predation. We find that for the model and parameters investigated, a very simple rule of thumb such as 'use the best constant control' performs well.

Estimating micro area behavioural risk factor prevalence from large population-based surveys: a full Bayesian approach.

PubMed

Seliske, L; Norwood, T A; McLaughlin, J R; Wang, S; Palleschi, C; Holowaty, E

2016-06-07

An important public health goal is to decrease the prevalence of key behavioural risk factors, such as tobacco use and obesity. Survey information is often available at the regional level, but heterogeneity within large geographic regions cannot be assessed. Advanced spatial analysis techniques are demonstrated to produce sensible micro area estimates of behavioural risk factors that enable identification of areas with high prevalence. A spatial Bayesian hierarchical model was used to estimate the micro area prevalence of current smoking and excess bodyweight for the Erie-St. Clair region in southwestern Ontario. Estimates were mapped for male and female respondents of five cycles of the Canadian Community Health Survey (CCHS). The micro areas were 2006 Census Dissemination Areas, with an average population of 400-700 people. Two individual-level models were specified: one controlled for survey cycle and age group (model 1), and one controlled for survey cycle, age group and micro area median household income (model 2). Post-stratification was used to derive micro area behavioural risk factor estimates weighted to the population structure. SaTScan analyses were conducted on the granular, postal-code level CCHS data to corroborate findings of elevated prevalence. Current smoking was elevated in two urban areas for both sexes (Sarnia and Windsor), and an additional small community (Chatham) for males only. Areas of excess bodyweight were prevalent in an urban core (Windsor) among males, but not females. Precision of the posterior post-stratified current smoking estimates was improved in model 2, as indicated by narrower credible intervals and a lower coefficient of variation. For excess bodyweight, both models had similar precision. Aggregation of the micro area estimates to CCHS design-based estimates validated the findings. This is among the first studies to apply a full Bayesian model to complex sample survey data to identify micro areas with variation in risk factor prevalence, accounting for spatial correlation and other covariates. Application of micro area analysis techniques helps define areas for public health planning, and may be informative to surveillance and research modeling of relevant chronic disease outcomes.

A model for assessing the risk of human trafficking on a local level

NASA Astrophysics Data System (ADS)

Colegrove, Amanda

Human trafficking is a human rights violation that is difficult to quantify. Models for estimating the number of victims of trafficking presented by previous researchers depend on inconsistent, poor quality data. As an intermediate step to help current efforts by nonprofits to combat human trafficking, this project presents a model that is not dependent on quantitative data specific to human trafficking, but rather profiles the risk of human trafficking at the local level through causative factors. Businesses, indicated by the literature, were weighted based on the presence of characteristics that increase the likelihood of trafficking in persons. The mean risk was calculated by census tract to reveal the multiplicity of risk levels in both rural and urban settings. Results indicate that labor trafficking may be a more diffuse problem in Missouri than sex trafficking. Additionally, spatial patterns of risk remained largely the same regardless of adjustments made to the model.

A Research Roadmap for Computation-Based Human Reliability Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boring, Ronald; Mandelli, Diego; Joe, Jeffrey

2015-08-01

The United States (U.S.) Department of Energy (DOE) is sponsoring research through the Light Water Reactor Sustainability (LWRS) program to extend the life of the currently operating fleet of commercial nuclear power plants. The Risk Informed Safety Margin Characterization (RISMC) research pathway within LWRS looks at ways to maintain and improve the safety margins of these plants. The RISMC pathway includes significant developments in the area of thermalhydraulics code modeling and the development of tools to facilitate dynamic probabilistic risk assessment (PRA). PRA is primarily concerned with the risk of hardware systems at the plant; yet, hardware reliability is oftenmore » secondary in overall risk significance to human errors that can trigger or compound undesirable events at the plant. This report highlights ongoing efforts to develop a computation-based approach to human reliability analysis (HRA). This computation-based approach differs from existing static and dynamic HRA approaches in that it: (i) interfaces with a dynamic computation engine that includes a full scope plant model, and (ii) interfaces with a PRA software toolset. The computation-based HRA approach presented in this report is called the Human Unimodels for Nuclear Technology to Enhance Reliability (HUNTER) and incorporates in a hybrid fashion elements of existing HRA methods to interface with new computational tools developed under the RISMC pathway. The goal of this research effort is to model human performance more accurately than existing approaches, thereby minimizing modeling uncertainty found in current plant risk models.« less

Are fashion models a group at risk for eating disorders and substance abuse?

PubMed

Santonastaso, Paolo; Mondini, Silvia; Favaro, Angela

2002-01-01

Few studies to date have investigated whether in fact the prevalence of eating disorders (ED) and/or use of illicit drugs is higher among models than among other groups of females. A group of 63 professional fashion models of various nationalities were studied by means of self-reported questionnaires. They were compared with a control group of 126 female subjects recruited from the general population. Fashion models weigh significantly less than controls, but only a small percentage of them uses unhealthy methods to control their weight. The current frequency of full-syndrome ED did not differ between the groups, but partial-syndrome ED were significantly more common among fashion models than among controls. Current substance use or alcohol abuse was reported by 35% of fashion models and 12% of controls. Our findings suggest that fashion models are more at risk for partial ED and use of illicit drugs than females in the general population. Copyright 2002 S. Karger AG, Basel

Emerging Infectious Diseases and Blood Safety: Modeling the Transfusion-Transmission Risk.

PubMed

Kiely, Philip; Gambhir, Manoj; Cheng, Allen C; McQuilten, Zoe K; Seed, Clive R; Wood, Erica M

2017-07-01

While the transfusion-transmission (TT) risk associated with the major transfusion-relevant viruses such as HIV is now very low, during the last 20 years there has been a growing awareness of the threat to blood safety from emerging infectious diseases, a number of which are known to be, or are potentially, transfusion transmissible. Two published models for estimating the transfusion-transmission risk from EIDs, referred to as the Biggerstaff-Petersen model and the European Upfront Risk Assessment Tool (EUFRAT), respectively, have been applied to several EIDs in outbreak situations. We describe and compare the methodological principles of both models, highlighting their similarities and differences. We also discuss the appropriateness of comparing results from the two models. Quantitating the TT risk of EIDs can inform decisions about risk mitigation strategies and their cost-effectiveness. Finally, we present a qualitative risk assessment for Zika virus (ZIKV), an EID agent that has caused several outbreaks since 2007. In the latest and largest ever outbreak, several probable cases of transfusion-transmission ZIKV have been reported, indicating that it is transfusion-transmissible and therefore a risk to blood safety. We discuss why quantitative modeling the TT risk of ZIKV is currently problematic. Crown Copyright © 2017. Published by Elsevier Inc. All rights reserved.

Data Model for Multi Hazard Risk Assessment Spatial Support Decision System

NASA Astrophysics Data System (ADS)

Andrejchenko, Vera; Bakker, Wim; van Westen, Cees

2014-05-01

The goal of the CHANGES Spatial Decision Support System is to support end-users in making decisions related to risk reduction measures for areas at risk from multiple hydro-meteorological hazards. The crucial parts in the design of the system are the user requirements, the data model, the data storage and management, and the relationships between the objects in the system. The implementation of the data model is carried out entirely with an open source database management system with a spatial extension. The web application is implemented using open source geospatial technologies with PostGIS as the database, Python for scripting, and Geoserver and javascript libraries for visualization and the client-side user-interface. The model can handle information from different study areas (currently, study areas from France, Romania, Italia and Poland are considered). Furthermore, the data model handles information about administrative units, projects accessible by different types of users, user-defined hazard types (floods, snow avalanches, debris flows, etc.), hazard intensity maps of different return periods, spatial probability maps, elements at risk maps (buildings, land parcels, linear features etc.), economic and population vulnerability information dependent on the hazard type and the type of the element at risk, in the form of vulnerability curves. The system has an inbuilt database of vulnerability curves, but users can also add their own ones. Included in the model is the management of a combination of different scenarios (e.g. related to climate change, land use change or population change) and alternatives (possible risk-reduction measures), as well as data-structures for saving the calculated economic or population loss or exposure per element at risk, aggregation of the loss and exposure using the administrative unit maps, and finally, producing the risk maps. The risk data can be used for cost-benefit analysis (CBA) and multi-criteria evaluation (SMCE). The data model includes data-structures for CBA and SMCE. The model is at the stage where risk and cost-benefit calculations can be stored but the remaining part is currently under development. Multi-criteria information, user management and the relation of these with the rest of the model is our next step. Having a carefully designed data model plays a crucial role in the development of the whole system for rapid development, keeping the data consistent, and in the end, support the end-user in making good decisions in risk-reduction measures related to multiple natural hazards. This work is part of the EU FP7 Marie Curie ITN "CHANGES"project (www.changes-itn.edu)

A model of pathways to artificial superintelligence catastrophe for risk and decision analysis

NASA Astrophysics Data System (ADS)

Barrett, Anthony M.; Baum, Seth D.

2017-03-01

An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.

New Elements To Consider When Modeling the Hazards Associated with Botulinum Neurotoxin in Food.

PubMed

Ihekwaba, Adaoha E C; Mura, Ivan; Malakar, Pradeep K; Walshaw, John; Peck, Michael W; Barker, G C

2016-01-15

Botulinum neurotoxins (BoNTs) produced by the anaerobic bacterium Clostridium botulinum are the most potent biological substances known to mankind. BoNTs are the agents responsible for botulism, a rare condition affecting the neuromuscular junction and causing a spectrum of diseases ranging from mild cranial nerve palsies to acute respiratory failure and death. BoNTs are a potential biowarfare threat and a public health hazard, since outbreaks of foodborne botulism are caused by the ingestion of preformed BoNTs in food. Currently, mathematical models relating to the hazards associated with C. botulinum, which are largely empirical, make major contributions to botulinum risk assessment. Evaluated using statistical techniques, these models simulate the response of the bacterium to environmental conditions. Though empirical models have been successfully incorporated into risk assessments to support food safety decision making, this process includes significant uncertainties so that relevant decision making is frequently conservative and inflexible. Progression involves encoding into the models cellular processes at a molecular level, especially the details of the genetic and molecular machinery. This addition drives the connection between biological mechanisms and botulism risk assessment and hazard management strategies. This review brings together elements currently described in the literature that will be useful in building quantitative models of C. botulinum neurotoxin production. Subsequently, it outlines how the established form of modeling could be extended to include these new elements. Ultimately, this can offer further contributions to risk assessments to support food safety decision making. Copyright © 2015 Ihekwaba et al.

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

PubMed

Rocheleau, J P; Michel, P; Lindsay, L R; Drebot, M; Dibernardo, A; Ogden, N H; Fortin, A; Arsenault, J

2017-10-01

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

PubMed Central

Xiao, Lei; Liu, Ya; Wang, Zuoguang; Li, Chuang; Jin, Yongxin; Zhao, Qiong

2017-01-01

Background Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative. Methods Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc. Results From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%. Conclusions The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment. PMID:29084293

A Bayesian network model for predicting type 2 diabetes risk based on electronic health records

NASA Astrophysics Data System (ADS)

Xie, Jiang; Liu, Yan; Zeng, Xu; Zhang, Wu; Mei, Zhen

2017-07-01

An extensive, in-depth study of diabetes risk factors (DBRF) is of crucial importance to prevent (or reduce) the chance of suffering from type 2 diabetes (T2D). Accumulation of electronic health records (EHRs) makes it possible to build nonlinear relationships between risk factors and diabetes. However, the current DBRF researches mainly focus on qualitative analyses, and the inconformity of physical examination items makes the risk factors likely to be lost, which drives us to study the novel machine learning approach for risk model development. In this paper, we use Bayesian networks (BNs) to analyze the relationship between physical examination information and T2D, and to quantify the link between risk factors and T2D. Furthermore, with the quantitative analyses of DBRF, we adopt EHR and propose a machine learning approach based on BNs to predict the risk of T2D. The experiments demonstrate that our approach can lead to better predictive performance than the classical risk model.

The Tripartite Model of Risk Perception (TRIRISK): Distinguishing Deliberative, Affective, and Experiential Components of Perceived Risk.

PubMed

Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal

2016-10-01

Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.

Hepatitis B vaccination and changes in sexual risk behaviour among men who have sex with men in Amsterdam.

PubMed

Xiridou, M; Wallinga, J; Dukers-Muijers, N; Coutinho, R

2009-04-01

The impact of hepatitis B vaccination in men having sex with men in Amsterdam has been marginal until now, possibly because of increases in sexual risk behaviour counterbalancing the effect of vaccination. A mathematical model is used to describe the hepatitis B epidemic. The model shows that, with the current vaccination coverage, the decrease in incidence is small in the beginning. However, the number of infections prevented per vaccine administered rises over time. Nevertheless, increased risk behaviour reduces the benefit of vaccination. Targeting high-risk men is more successful in reducing and containing the epidemic than targeting low-risk men. In conclusion, the vaccination campaign is effective and should be intensified. High-risk men should be targeted for vaccination and for risk reduction.

Development and validation of QDiabetes-2018 risk prediction algorithm to estimate future risk of type 2 diabetes: cohort study.

PubMed

Hippisley-Cox, Julia; Coupland, Carol

2017-11-20

Objectives  To derive and validate updated QDiabetes-2018 prediction algorithms to estimate the 10 year risk of type 2 diabetes in men and women, taking account of potential new risk factors, and to compare their performance with current approaches. Design  Prospective open cohort study. Setting  Routinely collected data from 1457 general practices in England contributing to the QResearch database: 1094 were used to develop the scores and a separate set of 363 were used to validate the scores. Participants  11.5 million people aged 25-84 and free of diabetes at baseline: 8.87 million in the derivation cohort and 2.63 million in the validation cohort. Methods  Cox proportional hazards models were used in the derivation cohort to derive separate risk equations in men and women for evaluation at 10 years. Risk factors considered included those already in QDiabetes (age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids) and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, gestational diabetes, and polycystic ovary syndrome. Additional models included fasting blood glucose and glycated haemoglobin (HBA1c). Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for individual subgroups by age group, ethnicity, and baseline disease status. Main outcome measure  Incident type 2 diabetes recorded on the general practice record. Results  In the derivation cohort, 178 314 incident cases of type 2 diabetes were identified during follow-up arising from 42.72 million person years of observation. In the validation cohort, 62 326 incident cases of type 2 diabetes were identified from 14.32 million person years of observation. All new risk factors considered met our model inclusion criteria. Model A included age, ethnicity, deprivation, body mass index, smoking, family history of diabetes in a first degree relative, cardiovascular disease, treated hypertension, and regular use of corticosteroids, and new risk factors: atypical antipsychotics, statins, schizophrenia or bipolar affective disorder, learning disability, and gestational diabetes and polycystic ovary syndrome in women. Model B included the same variables as model A plus fasting blood glucose. Model C included HBA1c instead of fasting blood glucose. All three models had good calibration and high levels of explained variation and discrimination. In women, model B explained 63.3% of the variation in time to diagnosis of type 2 diabetes (R 2 ), the D statistic was 2.69 and the Harrell's C statistic value was 0.89. The corresponding values for men were 58.4%, 2.42, and 0.87. Model B also had the highest sensitivity compared with current recommended practice in the National Health Service based on bands of either fasting blood glucose or HBA1c. However, only 16% of patients had complete data for blood glucose measurements, smoking, and body mass index. Conclusions  Three updated QDiabetes risk models to quantify the absolute risk of type 2 diabetes were developed and validated: model A does not require a blood test and can be used to identify patients for fasting blood glucose (model B) or HBA1c (model C) testing. Model B had the best performance for predicting 10 year risk of type 2 diabetes to identify those who need interventions and more intensive follow-up, improving on current approaches. Additional external validation of models B and C in datasets with more completely collected data on blood glucose would be valuable before the models are used in clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Breast cancer risks and risk prediction models.

PubMed

Engel, Christoph; Fischer, Christine

2015-02-01

BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

Predicting the Mobility and Burial of Underwater Unexploded Ordnance (UXO) Using the UXO Mobility Model (ESTCP) 200417

DTIC Science & Technology

2009-11-01

Abbreviations and Acronyms Acronym Definition ADCP Acoustic Doppler Current Profiler AGD Applications Guidance Document ARAMS Army Risk Assessment Modeling...Center iv NESDI Navy Environmental Sustainability Development to Integration NOS National Ocean Service NS Naval Station NWS Naval Weapons...Plan QAS Quality Assurance Specialist RAC Risk Assessment Code REF/DIF Refraction/Diffraction ROI Return on Investment SAJ Dr. Scott A. Jenkins

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment.

PubMed

Rice, F L; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust. Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death. Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m(3) for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000). There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.

Mechanistic modeling of insecticide risks to breeding birds in ...

EPA Pesticide Factsheets

Insecticide usage in the United States is ubiquitous in urban, suburban, and rural environments. In evaluating data for an insecticide registration application and for registration review, scientists at the United States Environmental Protection Agency (USEPA) assess the fate of the insecticide and the risk the insecticide poses to the environment and non-target wildlife. At the present time, current USEPA risk assessments do not include population-level endpoints. In this paper, we present a new mechanistic model, which allows risk assessors to estimate the effects of insecticide exposure on the survival and seasonal productivity of birds known to use agricultural fields during their breeding season. The new model was created from two existing USEPA avian risk assessment models, the Terrestrial Investigation Model (TIM v.3.0) and the Markov Chain Nest Productivity model (MCnest). The integrated TIM/MCnest model has been applied to assess the relative risk of 12 insecticides used to control corn pests on a suite of 31 avian species known to use cornfields in midwestern agroecosystems. The 12 insecticides that were assessed in this study are all used to treat major pests of corn (corn root worm borer, cutworm, and armyworm). After running the integrated TIM/MCnest model, we found extensive differences in risk to birds among insecticides, with chlorpyrifos and malathion (organophosphates) generally posing the greatest risk, and bifenthrin and ë-cyhalothrin (

ASSESSING MULTIMEDIA/MULTIPATHWAY EXPOSURE TO ARSENIC USING A MECHANISTIC SOURCE-TO-DOSE MODELING FRAMEWORK

EPA Science Inventory

A series of case studies is presented focusing on multimedia/multipathway population exposures to arsenic, employing the Population Based Modeling approach of the MENTOR (Modeling Environment for Total Risks) framework. This framework considers currently five exposure routes: i...

Utility of Risk Models in Decision Making After Radical Prostatectomy: Lessons from a Natural History Cohort of Intermediate- and High-Risk Men.

PubMed

Ross, Ashley E; Yousefi, Kasra; Davicioni, Elai; Ghadessi, Mercedeh; Johnson, Michael H; Sundi, Debasish; Tosoian, Jeffery J; Han, Misop; Humphreys, Elizabeth B; Partin, Alan W; Walsh, Patrick C; Trock, Bruce J; Schaeffer, Edward M

2016-03-01

Current guidelines suggest adjuvant radiation therapy for men with adverse pathologic features (APFs) at radical prostatectomy (RP). We examine at-risk men treated only with RP until the time of metastasis. To evaluate whether clinicopathologic risk models can help guide postoperative therapeutic decision making. Men with National Comprehensive Cancer Network intermediate- or high-risk localized prostate cancer undergoing RP in the prostate-specific antigen (PSA) era were identified (n=3089). Only men with initial undetectable PSA after surgery and who received no therapy prior to metastasis were included. APFs were defined as pT3 disease or positive surgical margins. Area under the receiver operating characteristic curve (AUC) for time to event data was used to measure the discrimination performance of the risk factors. Cumulative incidence curves were constructed using Fine and Gray competing risks analysis to estimate the risk of biochemical recurrence (BCR) or metastasis, taking censoring and death due to other causes into consideration. Overall, 43% of the cohort (n=1327) had APFs at RP. Median follow-up for censored patients was 5 yr. Cumulative incidence of metastasis was 6% at 10 yr after RP for all patients. Cumulative incidence of metastasis among men with APFs was 7.5% at 10 yr after RP. Among men with BCR, the incidence of metastasis was 38% 5 yr after BCR. At 10 yr after RP, time-dependent AUC for predicting metastasis by Cancer of the Prostate Risk Assessment Postsurgical or Eggener risk models was 0.81 (95% confidence interval [CI], 0.72-0.97) and 0.78 (95% CI, 0.67-0.97) in the APF population, respectively. At 5 yr after BCR, these values were lower (0.58 [95% CI, 0.50-0.66] and 0.70 [95% CI, 0.63-0.76]) among those who developed BCR. Use of risk model cut points could substantially reduce overtreatment while minimally increasing undertreatment (ie, use of an Eggener cut point of 2.5% for treatment of men with APFs would spare 46% from treatment while only allowing for metastatic events in 1% at 10 yr after RP). Use of risk models reduces overtreatment and should be a routine part of patient counseling when considering adjuvant therapy. Risk model performance is significantly reduced among men with BCR. Use of current risk models can help guide decision making regarding therapy after surgery and reduce overtreatment. Copyright © 2015 European Association of Urology. Published by Elsevier B.V. All rights reserved.

The Role of Body Image and Disordered Eating as Risk Factors for Depression and Suicidal Ideation in Adolescents

ERIC Educational Resources Information Center

Brausch, Amy M.; Gutierrez, Peter M.

2009-01-01

There is much empirical literature on factors for adolescent suicide risk, but body image and disordered eating are rarely included in these models. In the current study, disordered eating and body image were examined as risk factors for suicide ideation since these factors are prevalent in adolescence, particularly for females. It was…

The Victim-Offender Overlap and Fear of In-School Victimization: A Longitudinal Examination of Risk Assessment Models

ERIC Educational Resources Information Center

Melde, Chris; Esbensen, Finn-Aage

2009-01-01

Reports of serious violence in schools have raised general awareness and concern about safety in America's schools. In this article, the authors examine the extent to which in-school victimization is associated with students' perceived risk and fear of victimization. By expanding on Ferraro's risk assessment framework, the current study explores…

Risk Communication Emergency Response Preparedness: Contextual Assessment of the Protective Action Decision Model.

PubMed

Heath, Robert L; Lee, Jaesub; Palenchar, Michael J; Lemon, Laura L

2018-02-01

Studies are continuously performed to improve risk communication campaign designs to better prepare residents to act in the safest manner during an emergency. To that end, this article investigates the predictive ability of the protective action decision model (PADM), which links environmental and social cues, predecision processes (attention, exposure, and comprehension), and risk decision perceptions (threat, alternative protective actions, and stakeholder norms) with protective action decision making. This current quasi-longitudinal study of residents (N = 400 for each year) in a high-risk (chemical release) petrochemical manufacturing community investigated whether PADM core risk perceptions predict protective action decision making. Telephone survey data collected at four intervals (1995, 1998, 2002, 2012) reveal that perceptions of protective actions and stakeholder norms, but not of threat, currently predict protective action decision making (intention to shelter in place). Of significance, rather than threat perceptions, perception of Wally Wise Guy (a spokes-character who advocates shelter in place) correlates with perceptions of protective action, stakeholder norms, and protective action decision making. Wally's response-efficacy advice predicts residents' behavioral intentions to shelter in place, thereby offering contextually sensitive support and refinement for PADM. © 2017 Society for Risk Analysis.

Risk models for post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP): smoking and chronic liver disease are predictors of protection against PEP.

PubMed

DiMagno, Matthew J; Spaete, Joshua P; Ballard, Darren D; Wamsteker, Erik-Jan; Saini, Sameer D

2013-08-01

We investigated which variables independently associated with protection against or development of postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) and severity of PEP. Subsequently, we derived predictive risk models for PEP. In a case-control design, 6505 patients had 8264 ERCPs, 211 patients had PEP, and 22 patients had severe PEP. We randomly selected 348 non-PEP controls. We examined 7 established- and 9 investigational variables. In univariate analysis, 7 variables predicted PEP: younger age, female sex, suspected sphincter of Oddi dysfunction (SOD), pancreatic sphincterotomy, moderate-difficult cannulation (MDC), pancreatic stent placement, and lower Charlson score. Protective variables were current smoking, former drinking, diabetes, and chronic liver disease (CLD, biliary/transplant complications). Multivariate analysis identified seven independent variables for PEP, three protective (current smoking, CLD-biliary, CLD-transplant/hepatectomy complications) and 4 predictive (younger age, suspected SOD, pancreatic sphincterotomy, MDC). Pre- and post-ERCP risk models of 7 variables have a C-statistic of 0.74. Removing age (seventh variable) did not significantly affect the predictive value (C-statistic of 0.73) and reduced model complexity. Severity of PEP did not associate with any variables by multivariate analysis. By using the newly identified protective variables with 3 predictive variables, we derived 2 risk models with a higher predictive value for PEP compared to prior studies.

NASA Space Radiation Risk Project: Overview and Recent Results

NASA Technical Reports Server (NTRS)

Blattnig, Steve R.; Chappell, Lori J.; George, Kerry A.; Hada, Megumi; Hu, Shaowen; Kidane, Yared H.; Kim, Myung-Hee Y.; Kovyrshina, Tatiana; Norman, Ryan B.; Nounu, Hatem N.;

The Impact of Disability and Social Determinants of Health on Condition-Specific Readmissions beyond Medicare Risk Adjustments: A Cohort Study.

PubMed

Meddings, Jennifer; Reichert, Heidi; Smith, Shawna N; Iwashyna, Theodore J; Langa, Kenneth M; Hofer, Timothy P; McMahon, Laurence F

2017-01-01

Readmission rates after pneumonia, heart failure, and acute myocardial infarction hospitalizations are risk-adjusted for age, gender, and medical comorbidities and used to penalize hospitals. To assess the impact of disability and social determinants of health on condition-specific readmissions beyond current risk adjustment. Retrospective cohort study of Medicare patients using 1) linked Health and Retirement Study-Medicare claims data (HRS-CMS) and 2) Healthcare Cost and Utilization Project State Inpatient Databases (Florida, Washington) linked with ZIP Code-level measures from the Census American Community Survey (ACS-HCUP). Multilevel logistic regression models assessed the impact of disability and selected social determinants of health on readmission beyond current risk adjustment. Outcomes measured were readmissions ≤30 days after hospitalizations for pneumonia, heart failure, or acute myocardial infarction. HRS-CMS models included disability measures (activities of daily living [ADL] limitations, cognitive impairment, nursing home residence, home healthcare use) and social determinants of health (spouse, children, wealth, Medicaid, race). ACS-HCUP model measures were ZIP Code-percentage of residents ≥65 years of age with ADL difficulty, spouse, income, Medicaid, and patient-level and hospital-level race. For pneumonia, ≥3 ADL difficulties (OR 1.61, CI 1.079-2.391) and prior home healthcare needs (OR 1.68, CI 1.204-2.355) increased readmission in HRS-CMS models (N = 1631); ADL difficulties (OR 1.20, CI 1.063-1.352) and 'other' race (OR 1.14, CI 1.001-1.301) increased readmission in ACS-HCUP models (N = 27,297). For heart failure, children (OR 0.66, CI 0.437-0.984) and wealth (OR 0.53, CI 0.349-0.787) lowered readmission in HRS-CMS models (N = 2068), while black (OR 1.17, CI 1.056-1.292) and 'other' race (OR 1.14, CI 1.036-1.260) increased readmission in ACS-HCUP models (N = 37,612). For acute myocardial infarction, nursing home status (OR 4.04, CI 1.212-13.440) increased readmission in HRS-CMS models (N = 833); 'other' patient-level race (OR 1.18, CI 1.012-1.385) and hospital-level race (OR 1.06, CI 1.001-1.125) increased readmission in ACS-HCUP models (N = 17,496). Disability and social determinants of health influence readmission risk when added to the current Medicare risk adjustment models, but the effect varies by condition.

A Social-Ecological Framework of Theory, Assessment, and Prevention of Suicide

PubMed Central

Cramer, Robert J.; Kapusta, Nestor D.

2017-01-01

The juxtaposition of increasing suicide rates with continued calls for suicide prevention efforts begs for new approaches. Grounded in the Centers for Disease Control and Prevention (CDC) framework for tackling health issues, this personal views work integrates relevant suicide risk/protective factor, assessment, and intervention/prevention literatures. Based on these components of suicide risk, we articulate a Social-Ecological Suicide Prevention Model (SESPM) which provides an integration of general and population-specific risk and protective factors. We also use this multi-level perspective to provide a structured approach to understanding current theories and intervention/prevention efforts concerning suicide. Following similar multi-level prevention efforts in interpersonal violence and Human Immunodeficiency Virus (HIV) domains, we offer recommendations for social-ecologically informed suicide prevention theory, training, research, assessment, and intervention programming. Although the SESPM calls for further empirical testing, it provides a suitable backdrop for tailoring of current prevention and intervention programs to population-specific needs. Moreover, the multi-level model shows promise to move suicide risk assessment forward (e.g., development of multi-level suicide risk algorithms or structured professional judgments instruments) to overcome current limitations in the field. Finally, we articulate a set of characteristics of social-ecologically based suicide prevention programs. These include the need to address risk and protective factors with the strongest degree of empirical support at each multi-level layer, incorporate a comprehensive program evaluation strategy, and use a variety of prevention techniques across levels of prevention. PMID:29062296

Animal models of listeriosis: a comparative review of the current state of the art and lessons learned

PubMed Central

2012-01-01

Listeriosis is a leading cause of hospitalization and death due to foodborne illness in the industrialized world. Animal models have played fundamental roles in elucidating the pathophysiology and immunology of listeriosis, and will almost certainly continue to be integral components of the research on listeriosis. Data derived from animal studies helped for example characterize the importance of cell-mediated immunity in controlling infection, allowed evaluation of chemotherapeutic treatments for listeriosis, and contributed to quantitative assessments of the public health risk associated with L. monocytogenes contaminated food commodities. Nonetheless, a number of pivotal questions remain unresolved, including dose-response relationships, which represent essential components of risk assessments. Newly emerging data about species-specific differences have recently raised concern about the validity of most traditional animal models of listeriosis. However, considerable uncertainty about the best choice of animal model remains. Here we review the available data on traditional and potential new animal models to summarize currently recognized strengths and limitations of each model. This knowledge is instrumental for devising future studies and for interpreting current data. We deliberately chose a historical, comparative and cross-disciplinary approach, striving to reveal clues that may help predict the ultimate value of each animal model in spite of incomplete data. PMID:22417207

Animal models of listeriosis: a comparative review of the current state of the art and lessons learned.

PubMed

Hoelzer, Karin; Pouillot, Régis; Dennis, Sherri

2012-03-14

Listeriosis is a leading cause of hospitalization and death due to foodborne illness in the industrialized world. Animal models have played fundamental roles in elucidating the pathophysiology and immunology of listeriosis, and will almost certainly continue to be integral components of the research on listeriosis. Data derived from animal studies helped for example characterize the importance of cell-mediated immunity in controlling infection, allowed evaluation of chemotherapeutic treatments for listeriosis, and contributed to quantitative assessments of the public health risk associated with L. monocytogenes contaminated food commodities. Nonetheless, a number of pivotal questions remain unresolved, including dose-response relationships, which represent essential components of risk assessments. Newly emerging data about species-specific differences have recently raised concern about the validity of most traditional animal models of listeriosis. However, considerable uncertainty about the best choice of animal model remains. Here we review the available data on traditional and potential new animal models to summarize currently recognized strengths and limitations of each model. This knowledge is instrumental for devising future studies and for interpreting current data. We deliberately chose a historical, comparative and cross-disciplinary approach, striving to reveal clues that may help predict the ultimate value of each animal model in spite of incomplete data.

Dynamics of high-risk nonvaccine human papillomavirus types after actual vaccination scheme.

PubMed

Peralta, Raúl; Vargas-De-León, Cruz; Cabrera, Augusto; Miramontes, Pedro

2014-01-01

Human papillomavirus (HPV) has been identified as the main etiological factor in the developing of cervical cancer (CC). This finding has propitiated the development of vaccines that help to prevent the HPVs 16 and 18 infection. Both genotypes are associated with 70% of CC worldwide. In the present study, we aimed to determine the emergence of high-risk nonvaccine HPV after actual vaccination scheme to estimate the impact of the current HPV vaccines. A SIR-type model was used to study the HPV dynamics after vaccination. According to the results, our model indicates that the application of the vaccine reduces infection by target or vaccine genotypes as expected. However, numerical simulations of the model suggest the presence of the phenomenon called vaccine-induced pathogen strain replacement. Here, we report the following replacement mechanism: if the effectiveness of cross-protective immunity is not larger than the effectiveness of the vaccine, then the high-risk nonvaccine genotypes emerge. In this scenario, further studies of infection dispersion by HPV are necessary to ascertain the real impact of the current vaccines, primarily because of the different high-risk HPV types that are found in CC.

Attribution of floods in the Okavango basin, Southern Africa

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Stone, Dáithí; Tadross, Mark; Wehner, Michael; Hewitson, Bruce

2014-04-01

In the charismatic wetlands of the Okavango Delta, Botswana, the annual floods of 2009-2011 reached magnitudes last seen 20-30 years ago, considerably affecting life of local populations and the economically important tourism industry. In this study, we analyse results from an attribution modelling system designed to examine how anthropogenic greenhouse gas emissions have contributed to weather and flood risk in our current climate. The system is based on comparison of real world climate and hydrological simulations with parallel counterfactual simulations of the climate and hydrological responses under conditions that might have been had human activities not emitted greenhouse gases. The analyses allow us to address the question of whether anthropogenic climate change contributed to increasing the risk of these high flood events in the Okavango system. Results show that the probability of occurrence of high floods during 2009-2011 in the current climate is likely lower than it would have been in a climate without anthropogenic greenhouse gases. This result is robust across the two climate models and various data processing procedures, although the exact figures for the associated decrease in risk differ. Results also differ between the three years examined, indicating that the “time-slice” method used here needs to be applied to multiple years in order to accurately estimate the contribution of emissions to current risk. Simple sensitivity analyses indicate that the reduction in flood risk is attributed to higher temperatures (and thus evaporation) in the current world, with little difference in the analysed domain's rainfall simulated in the two scenarios.

[Problems of work world and its impact on health. Current financial crisis].

PubMed

Tomasina, Fernando

2012-06-01

Health and work are complex processes. Besides, they are multiple considering the forms they take. These two processes are linked to each other and they are influenced by each other. According to this, it is possible to establish that work world is extremely complex and heterogeneous. In this world, "old" or traditional risks coexist with "modern risks", derived from the new models of work organization and the incorporation of new technologies. Unemployment, work relationships precariousness and work risks outsourcing are results of neoliberal strategies. Some negative results of health-sickness process derived from transformation in work world and current global economic crisis have been noticed in current work conditions. Finally, the need for reconstructing policies focusing on this situation derived from work world is suggested.

Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm.

PubMed

Sun, Xiangqing; Elston, Robert C; Barnholtz-Sloan, Jill S; Falk, Gary W; Grady, William M; Faulx, Ashley; Mittal, Sumeet K; Canto, Marcia; Shaheen, Nicholas J; Wang, Jean S; Iyer, Prasad G; Abrams, Julian A; Tian, Ye D; Willis, Joseph E; Guda, Kishore; Markowitz, Sanford D; Chandar, Apoorva; Warfe, James M; Brock, Wendy; Chak, Amitabh

2016-05-01

Barrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed. We developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees. Our results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy. Our model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR. ©2016 American Association for Cancer Research.

Risk adjustment for health care financing in chronic disease: what are we missing by failing to account for disease severity?

PubMed

Omachi, Theodore A; Gregorich, Steven E; Eisner, Mark D; Penaloza, Renee A; Tolstykh, Irina V; Yelin, Edward H; Iribarren, Carlos; Dudley, R Adams; Blanc, Paul D

2013-08-01

Adjustment for differing risks among patients is usually incorporated into newer payment approaches, and current risk models rely on age, sex, and diagnosis codes. It is unknown the extent to which controlling additionally for disease severity improves cost prediction. Failure to adjust for within-disease variation may create incentives to avoid sicker patients. We address this issue among patients with chronic obstructive pulmonary disease (COPD). Cost and clinical data were collected prospectively from 1202 COPD patients at Kaiser Permanente. Baseline analysis included age, sex, and diagnosis codes (using the Diagnostic Cost Group Relative Risk Score) in a general linear model predicting total medical costs in the following year. We determined whether adding COPD severity measures-forced expiratory volume in 1 second, 6-Minute Walk Test, dyspnea score, body mass index, and BODE Index (composite of the other 4 measures)-improved predictions. Separately, we examined household income as a cost predictor. Mean costs were $12,334/y. Controlling for Relative Risk Score, each ½ SD worsening in COPD severity factor was associated with $629 to $1135 in increased annual costs (all P<0.01). The lowest stratum of forced expiratory volume in 1 second (<30% normal) predicted $4098 (95% confidence interval, $576-$8773) additional costs. Household income predicted excess costs when added to the baseline model (P=0.038), but this became nonsignificant when also incorporating the BODE Index. Disease severity measures explain significant cost variations beyond current risk models, and adding them to such models appears important to fairly compensate organizations that accept responsibility for sicker COPD patients. Appropriately controlling for disease severity also accounts for costs otherwise associated with lower socioeconomic status.

New Zealand Diabetes Cohort Study cardiovascular risk score for people with Type 2 diabetes: validation in the PREDICT cohort.

PubMed

Robinson, Tom; Elley, C Raina; Wells, Sue; Robinson, Elizabeth; Kenealy, Tim; Pylypchuk, Romana; Bramley, Dale; Arroll, Bruce; Crengle, Sue; Riddell, Tania; Ameratunga, Shanthi; Metcalf, Patricia; Drury, Paul L

2012-09-01

New Zealand (NZ) guidelines recommend treating people for cardiovascular disease (CVD) risk on the basis of five-year absolute risk using a NZ adaptation of the Framingham risk equation. A diabetes-specific Diabetes Cohort Study (DCS) CVD predictive risk model has been developed and validated using NZ Get Checked data. To revalidate the DCS model with an independent cohort of people routinely assessed using PREDICT, a web-based CVD risk assessment and management programme. People with Type 2 diabetes without pre-existing CVD were identified amongst people who had a PREDICT risk assessment between 2002 and 2005. From this group we identified those with sufficient data to allow estimation of CVD risk with the DCS models. We compared the DCS models with the NZ Framingham risk equation in terms of discrimination, calibration, and reclassification implications. Of 3044 people in our study cohort, 1829 people had complete data and therefore had CVD risks calculated. Of this group, 12.8% (235) had a cardiovascular event during the five-year follow-up. The DCS models had better discrimination than the currently used equation, with C-statistics being 0.68 for the two DCS models and 0.65 for the NZ Framingham model. The DCS models were superior to the NZ Framingham equation at discriminating people with diabetes who will have a cardiovascular event. The adoption of a DCS model would lead to a small increase in the number of people with diabetes who are treated with medication, but potentially more CVD events would be avoided.

An Integrated Risk Management Model for Source Water Protection Areas

PubMed Central

Chiueh, Pei-Te; Shang, Wei-Ting; Lo, Shang-Lien

2012-01-01

Watersheds are recognized as the most effective management unit for the protection of water resources. For surface water supplies that use water from upstream watersheds, evaluating threats to water quality and implementing a watershed management plan are crucial for the maintenance of drinking water safe for humans. The aim of this article is to establish a risk assessment model that provides basic information for identifying critical pollutants and areas at high risk for degraded water quality. In this study, a quantitative risk model that uses hazard quotients for each water quality parameter was combined with a qualitative risk model that uses the relative risk level of potential pollution events in order to characterize the current condition and potential risk of watersheds providing drinking water. In a case study of Taipei Source Water Area in northern Taiwan, total coliforms and total phosphorus were the top two pollutants of concern. Intensive tea-growing and recreational activities around the riparian zone may contribute the greatest pollution to the watershed. Our risk assessment tool may be enhanced by developing, recording, and updating information on pollution sources in the water supply watersheds. Moreover, management authorities could use the resultant information to create watershed risk management plans. PMID:23202770

Determination of viable legionellae in engineered water systems: Do we find what we are looking for?

PubMed Central

Kirschner, Alexander K.T.

2016-01-01

In developed countries, legionellae are one of the most important water-based bacterial pathogens caused by management failure of engineered water systems. For routine surveillance of legionellae in engineered water systems and outbreak investigations, cultivation-based standard techniques are currently applied. However, in many cases culture-negative results are obtained despite the presence of viable legionellae, and clinical cases of legionellosis cannot be traced back to their respective contaminated water source. Among the various explanations for these discrepancies, the presence of viable but non-culturable (VBNC) Legionella cells has received increased attention in recent discussions and scientific literature. Alternative culture-independent methods to detect and quantify legionellae have been proposed in order to complement or even substitute the culture method in the future. Such methods should detect VBNC Legionella cells and provide a more comprehensive picture of the presence of legionellae in engineered water systems. However, it is still unclear whether and to what extent these VBNC legionellae are hazardous to human health. Current risk assessment models to predict the risk of legionellosis from Legionella concentrations in the investigated water systems contain many uncertainties and are mainly based on culture-based enumeration. If VBNC legionellae should be considered in future standard analysis, quantitative risk assessment models including VBNC legionellae must be proven to result in better estimates of human health risk than models based on cultivation alone. This review critically evaluates current methods to determine legionellae in the VBNC state, their potential to complement the standard culture-based method in the near future, and summarizes current knowledge on the threat that VBNC legionellae may pose to human health. PMID:26928563

Determination of viable legionellae in engineered water systems: Do we find what we are looking for?

PubMed

Kirschner, Alexander K T

2016-04-15

In developed countries, legionellae are one of the most important water-based bacterial pathogens caused by management failure of engineered water systems. For routine surveillance of legionellae in engineered water systems and outbreak investigations, cultivation-based standard techniques are currently applied. However, in many cases culture-negative results are obtained despite the presence of viable legionellae, and clinical cases of legionellosis cannot be traced back to their respective contaminated water source. Among the various explanations for these discrepancies, the presence of viable but non-culturable (VBNC) Legionella cells has received increased attention in recent discussions and scientific literature. Alternative culture-independent methods to detect and quantify legionellae have been proposed in order to complement or even substitute the culture method in the future. Such methods should detect VBNC Legionella cells and provide a more comprehensive picture of the presence of legionellae in engineered water systems. However, it is still unclear whether and to what extent these VBNC legionellae are hazardous to human health. Current risk assessment models to predict the risk of legionellosis from Legionella concentrations in the investigated water systems contain many uncertainties and are mainly based on culture-based enumeration. If VBNC legionellae should be considered in future standard analysis, quantitative risk assessment models including VBNC legionellae must be proven to result in better estimates of human health risk than models based on cultivation alone. This review critically evaluates current methods to determine legionellae in the VBNC state, their potential to complement the standard culture-based method in the near future, and summarizes current knowledge on the threat that VBNC legionellae may pose to human health. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Mechanisms, Prediction, and Prevention of ACL Injuries: Cut Risk With Three Sharpened and Validated Tools

PubMed Central

Hewett, Timothy E.; Myer, Gregory D.; Ford, Kevin R.; Paterno, Mark V.; Quatman, Carmen E.

2017-01-01

Economic and societal pressures influence modern medical practice to develop and implement prevention strategies. Anterior cruciate ligament (ACL) injury devastates the knee joint leading to short term disability and long term sequelae. Due to the high risk of long term osteoarthritis in all treatment populations following ACL injury, prevention is the only effective intervention for this life-altering disruption in knee health. The “Sequence of Prevention” Model provides a framework to monitor progress towards the ultimate goal of preventing ACL injuries. Utilizing this model, our multidisciplinary collaborative research team has spent the last decade working to delineate injury mechanisms, identify injury risk factors, predict which athletes are at-risk for injury, and develop ACL injury prevention programs. Within this model of injury prevention, modifiable factors (biomechanical and neuromuscular) related to injury mechanisms likely provide the best opportunity for intervention strategies aimed to decrease the risk of ACL injury, particularly in female athletes. Knowledge advancements have led to the development of potential solutions that allow athletes to compete with lowered risk of ACL injury. Design and integration of personalized clinical assessment tools and targeted prevention strategies for athletes at high risk for ACL injury may transform current prevention practices and ultimately significantly reduce ACL injury incidence. This 2016 OREF Clinical Research Award focuses on the authors' work and contributions to the field. The author's acknowledge the many research groups who have contributed to the current state of knowledge in the fields of ACL injury mechanisms, injury risk screening and injury prevention strategies. PMID:27612195

A quantitative risk assessment model to evaluate effective border control measures for rabies prevention.

PubMed

Weng, Hsin-Yi; Wu, Pei-I; Yang, Ping-Cheng; Tsai, Yi-Lun; Chang, Chao-Chin

2010-01-01

Border control is the primary method to prevent rabies emergence. This study developed a quantitative risk model incorporating stochastic processes to evaluate whether border control measures could efficiently prevent rabies introduction through importation of cats and dogs using Taiwan as an example. Both legal importation and illegal smuggling were investigated. The impacts of reduced quarantine and/or waiting period on the risk of rabies introduction were also evaluated. The results showed that Taiwan's current animal importation policy could effectively prevent rabies introduction through legal importation of cats and dogs. The median risk of a rabid animal to penetrate current border control measures and enter Taiwan was 5.33 x 10(-8) (95th percentile: 3.20 x 10(-7)). However, illegal smuggling may pose Taiwan to the great risk of rabies emergence. Reduction of quarantine and/or waiting period would affect the risk differently, depending on the applied assumptions, such as increased vaccination coverage, enforced custom checking, and/or change in number of legal importations. Although the changes in the estimated risk under the assumed alternatives were not substantial except for completely abolishing quarantine, the consequences of rabies introduction may yet be considered to be significant in a rabies-free area. Therefore, a comprehensive benefit-cost analysis needs to be conducted before recommending these alternative measures.

Associations of Bar and Restaurant Smoking Bans With Smoking Behavior in the CARDIA Study: A 25-Year Study.

PubMed

Mayne, Stephanie L; Auchincloss, Amy H; Tabb, Loni Philip; Stehr, Mark; Shikany, James M; Schreiner, Pamela J; Widome, Rachel; Gordon-Larsen, Penny

2018-06-01

Indoor smoking bans have often been associated with reductions in smoking prevalence. However, few studies have evaluated their association with within-person changes in smoking behaviors. We linked longitudinal data from 5,105 adults aged 18-30 years at baseline from the Coronary Artery Risk Development in Young Adults (CARDIA) Study (1985-2011) to state, county, and local policies mandating 100% smoke-free bars and restaurants by census tract. We used fixed-effects models to examine the association of smoking bans with within-person change in current smoking risk, smoking intensity (smoking ≥10 cigarettes/day on average vs. <10 cigarettes/day), and quitting attempts, using both linear and nonlinear adjustment for secular trends. In models assuming a linear secular trend, smoking bans were associated with a decline in current smoking risk and smoking intensity and an increased likelihood of a quitting attempt. The association with current smoking was greatest among participants with a bachelor's degree or higher. In models with a nonlinear secular trend, pooled results were attenuated (confidence intervals included the null), but effect modification results were largely unchanged. Findings suggest that smoking ban associations may be difficult to disentangle from other tobacco control interventions and emphasize the importance of evaluating equity throughout policy implementation.

Are Centers for Disease Control and Prevention Guidelines for Preexposure Prophylaxis Specific Enough? Formulation of a Personalized HIV Risk Score for Pre-Exposure Prophylaxis Initiation.

PubMed

Beymer, Matthew R; Weiss, Robert E; Sugar, Catherine A; Bourque, Linda B; Gee, Gilbert C; Morisky, Donald E; Shu, Suzanne B; Javanbakht, Marjan; Bolan, Robert K

2017-01-01

Preexposure prophylaxis (PrEP) has emerged as a human immunodeficiency virus (HIV) prevention tool for populations at highest risk for HIV infection. Current US Centers for Disease Control and Prevention (CDC) guidelines for identifying PrEP candidates may not be specific enough to identify gay, bisexual, and other men who have sex with men (MSM) at the highest risk for HIV infection. We created an HIV risk score for HIV-negative MSM based on Syndemics Theory to develop a more targeted criterion for assessing PrEP candidacy. Behavioral risk assessment and HIV testing data were analyzed for HIV-negative MSM attending the Los Angeles LGBT Center between January 2009 and June 2014 (n = 9481). Syndemics Theory informed the selection of variables for a multivariable Cox proportional hazards model. Estimated coefficients were summed to create an HIV risk score, and model fit was compared between our model and CDC guidelines using the Akaike Information Criterion and Bayesian Information Criterion. Approximately 51% of MSM were above a cutpoint that we chose as an illustrative risk score to qualify for PrEP, identifying 75% of all seroconverting MSM. Our model demonstrated a better overall fit when compared with the CDC guidelines (Akaike Information Criterion Difference = 68) in addition to identifying a greater proportion of HIV infections. Current CDC PrEP guidelines should be expanded to incorporate substance use, partner-level, and other Syndemic variables that have been shown to contribute to HIV acquisition. Deployment of such personalized algorithms may better hone PrEP criteria and allow providers and their patients to make a more informed decision prior to PrEP use.

Two-protein signature of novel serological markers apolipoprotein-A2 and serum amyloid alpha predicts prognosis in patients with metastatic renal cell cancer and improves the currently used prognostic survival models.

PubMed

Vermaat, J S; van der Tweel, I; Mehra, N; Sleijfer, S; Haanen, J B; Roodhart, J M; Engwegen, J Y; Korse, C M; Langenberg, M H; Kruit, W; Groenewegen, G; Giles, R H; Schellens, J H; Beijnen, J H; Voest, E E

2010-07-01

In metastatic renal cell cancer (mRCC), the Memorial Sloan-Kettering Cancer Center (MSKCC) risk model is widely used for clinical trial design and patient management. To improve prognostication, we applied proteomics to identify novel serological proteins associated with overall survival (OS). Sera from 114 mRCC patients were screened by surface-enhanced laser desorption ionization time-of-flight mass spectrometry (SELDI-TOF MS). Identified proteins were related to OS. Three proteins were subsequently validated with enzyme-linked immunosorbent assays and immunoturbidimetry. Prognostic models were statistically bootstrapped to correct for overestimation. SELDI-TOF MS detected 10 proteins associated with OS. Of these, apolipoprotein A2 (ApoA2), serum amyloid alpha (SAA) and transthyretin were validated for their association with OS (P = 5.5 x 10(-9), P = 1.1 x 10(-7) and P = 0.0004, respectively). Combining ApoA2 and SAA yielded a prognostic two-protein signature [Akaike's Information Criteria (AIC) = 732, P = 5.2 x 10(-7)]. Including previously identified prognostic factors, multivariable Cox regression analysis revealed ApoA2, SAA, lactate dehydrogenase, performance status and number of metastasis sites as independent factors for survival. Using these five factors, categorization of patients into three risk groups generated a novel protein-based model predicting patient prognosis (AIC = 713, P = 4.3 x 10(-11)) more robustly than the MSKCC model (AIC = 729, P = 1.3 x 10(-7)). Applying this protein-based model instead of the MSKCC model would have changed the risk group in 38% of the patients. Proteomics and subsequent validation yielded two novel prognostic markers and survival models which improved prediction of OS in mRCC patients over commonly used risk models. Implementation of these models has the potential to improve current risk stratification, although prospective validation will still be necessary.

Age at exposure and attained age variations of cancer risk in the Japanese A-bomb and radiotherapy cohorts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schneider, Uwe, E-mail: uwe.schneider@uzh.ch; Walsh, Linda

Purpose: Phenomenological risk models for radiation-induced cancer are frequently applied to estimate the risk of radiation-induced cancers at radiotherapy doses. Such models often include the effect modification, of the main risk to radiation dose response, by age at exposure and attained age. The aim of this paper is to compare the patterns in risk effect modification by age, between models obtained from the Japanese atomic-bomb (A-bomb) survivor data and models for cancer risks previously reported for radiotherapy patients. Patterns in risk effect modification by age from the epidemiological studies of radiotherapy patients were also used to refine and extend themore » risk effect modification by age obtained from the A-bomb survivor data, so that more universal models can be presented here. Methods: Simple log-linear and power functions of age for the risk effect modification applied in models of the A-bomb survivor data are compared to risks from epidemiological studies of second cancers after radiotherapy. These functions of age were also refined and fitted to radiotherapy risks. The resulting age models provide a refined and extended functional dependence of risk with age at exposure and attained age especially beyond 40 and 65 yr, respectively, and provide a better representation than the currently available simple age functions. Results: It was found that the A-bomb models predict risk similarly to the outcomes of testicular cancer survivors. The survivors of Hodgkin’s disease show steeper variations of risk with both age at exposure and attained age. The extended models predict solid cancer risk increase as a function of age at exposure beyond 40 yr and the risk decrease as a function of attained age beyond 65 yr better than the simple models. Conclusions: The standard functions for risk effect modification by age, based on the A-bomb survivor data, predict second cancer risk in radiotherapy patients for ages at exposure prior to 40 yr and attained ages before 55 yr reasonably well. However, for larger ages, the refined and extended models can be applied to predict the risk as a function of age.« less

Age at exposure and attained age variations of cancer risk in the Japanese A-bomb and radiotherapy cohorts.

PubMed

Schneider, Uwe; Walsh, Linda

2015-08-01

Phenomenological risk models for radiation-induced cancer are frequently applied to estimate the risk of radiation-induced cancers at radiotherapy doses. Such models often include the effect modification, of the main risk to radiation dose response, by age at exposure and attained age. The aim of this paper is to compare the patterns in risk effect modification by age, between models obtained from the Japanese atomic-bomb (A-bomb) survivor data and models for cancer risks previously reported for radiotherapy patients. Patterns in risk effect modification by age from the epidemiological studies of radiotherapy patients were also used to refine and extend the risk effect modification by age obtained from the A-bomb survivor data, so that more universal models can be presented here. Simple log-linear and power functions of age for the risk effect modification applied in models of the A-bomb survivor data are compared to risks from epidemiological studies of second cancers after radiotherapy. These functions of age were also refined and fitted to radiotherapy risks. The resulting age models provide a refined and extended functional dependence of risk with age at exposure and attained age especially beyond 40 and 65 yr, respectively, and provide a better representation than the currently available simple age functions. It was found that the A-bomb models predict risk similarly to the outcomes of testicular cancer survivors. The survivors of Hodgkin's disease show steeper variations of risk with both age at exposure and attained age. The extended models predict solid cancer risk increase as a function of age at exposure beyond 40 yr and the risk decrease as a function of attained age beyond 65 yr better than the simple models. The standard functions for risk effect modification by age, based on the A-bomb survivor data, predict second cancer risk in radiotherapy patients for ages at exposure prior to 40 yr and attained ages before 55 yr reasonably well. However, for larger ages, the refined and extended models can be applied to predict the risk as a function of age.

Risk of breast cancer following exposure to tetrachloroethylene-contaminated drinking water in Cape Cod, Massachusetts: reanalysis of a case-control study using a modified exposure assessment

PubMed Central

2011-01-01

Background Tetrachloroethylene (PCE) is an important occupational chemical used in metal degreasing and drycleaning and a prevalent drinking water contaminant. Exposure often occurs with other chemicals but it occurred alone in a pattern that reduced the likelihood of confounding in a unique scenario on Cape Cod, Massachusetts. We previously found a small to moderate increased risk of breast cancer among women with the highest exposures using a simple exposure model. We have taken advantage of technical improvements in publically available software to incorporate a more sophisticated determination of water flow and direction to see if previous results were robust to more accurate exposure assessment. Methods The current analysis used PCE exposure estimates generated with the addition of water distribution modeling software (EPANET 2.0) to test model assumptions, compare exposure distributions to prior methods, and re-examine the risk of breast cancer. In addition, we applied data smoothing to examine nonlinear relationships between breast cancer and exposure. We also compared a set of measured PCE concentrations in water samples collected in 1980 to modeled estimates. Results Thirty-nine percent of individuals considered unexposed in prior epidemiological analyses were considered exposed using the current method, but mostly at low exposure levels. As a result, the exposure distribution was shifted downward resulting in a lower value for the 90th percentile, the definition of "high exposure" in prior analyses. The current analyses confirmed a modest increase in the risk of breast cancer for women with high PCE exposure levels defined by either the 90th percentile (adjusted ORs 1.0-1.5 for 0-19 year latency assumptions) or smoothing analysis cut point (adjusted ORs 1.3-2.0 for 0-15 year latency assumptions). Current exposure estimates had a higher correlation with PCE concentrations in water samples (Spearman correlation coefficient = 0.65, p < 0.0001) than estimates generated using the prior method (0.54, p < 0.0001). Conclusions The incorporation of sophisticated flow estimates in the exposure assessment method shifted the PCE exposure distribution downward, but did not meaningfully affect the exposure ranking of subjects or the strength of the association with the risk of breast cancer found in earlier analyses. Thus, the current analyses show a slightly elevated breast cancer risk for highly exposed women, with strengthened exposure assessment and minimization of misclassification by using the latest technology. PMID:21600013

Household portfolio choices, health status and health care systems: A cross-country analysis based on SHARE.

PubMed

Atella, Vincenzo; Brunetti, Marianna; Maestas, Nicole

2012-05-01

Health risk is increasingly viewed as an important form of background risk that affects household portfolio decisions. However, its role might be mediated by the presence of a protective full-coverage national health service that could reduce households' probability of incurring current and future out-of-pocket medical expenditures. We use SHARE data to study the influence of current health status and future health risk on the decision to hold risky assets, across ten European countries with different health systems, each offering a different degree of protection against out-of-pocket medical expenditures. We find robust empirical evidence that perceived health status matters more than objective health status and, consistent with the theory of background risk, health risk affects portfolio choices only in countries with less protective health care systems. Furthermore, portfolio decisions consistent with background risk models are observed only with respect to middle-aged and highly-educated investors.

A REGIONAL APPROACH TO ECOLOGICAL RISK ASSESSMENTS FOR PESTICIDE REGISTRATION

EPA Science Inventory

Currently, most ecological risk assessments for EPA pesticide registration are evaluated at the national scale using a predetermined list of test species (OPPTS 850.4225 and 8504250) as a model system with little regard to where and how the product will ultimately be used. The a...

NEW TECHNOLOGIES TO SOLVE OLD PROBLEMS AND ADDRESS ISSUES IN RISK ASSESSMENT

EPA Science Inventory

Appropriate utilization of data is an ongoing concern of the regulated industries and the agencies charged with assessing safety or risk. An area of current interest is the possibility that toxicogenomics will enhance our ability to develop higher or high-throughput models for pr...

Environmental Health and Aging: Activity, Exposure and Biological Models to Improve Risk Assessment and Health Promotion

EPA Science Inventory

The US Environmental Protection Agency (EPA) and other public health agencies are concerned that the environmental health of America’s growing population of older adults has not been taken into consideration in current approaches to risk assessment. The reduced capacity to respo...

Risk-Based Models for Managing Data Privacy in Healthcare

ERIC Educational Resources Information Center

AL Faresi, Ahmed

2011-01-01

Current research in health care lacks a systematic investigation to identify and classify various sources of threats to information privacy when sharing health data. Identifying and classifying such threats would enable the development of effective information security risk monitoring and management policies. In this research I put the first step…

Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks.

PubMed

Coiera, Enrico; Wang, Ying; Magrabi, Farah; Concha, Oscar Perez; Gallego, Blanca; Runciman, William

2014-05-21

Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model performance was evaluated alone, and in combination with simple disease-specific models. Patients admitted between 2000 and 2006 from 501 public and private hospitals in NSW, Australia were used for training and 2007 data for evaluation. The impact of hospital care delivered over different days of the week and or times of the day was modeled by separating hospitalization risk into 21 separate time periods (morning, day, night across the days of the week). Three models were developed to predict death up to 7-days post-discharge: 1/a simple background risk model using age, gender; 2/a time-varying risk model for exposure to hospitalization (admission time, days in hospital); 3/disease specific models (Charlson co-morbidity index, DRG). Combining these three generated a full model. Models were evaluated by accuracy, AUC, Akaike and Bayesian information criteria. There was a clear diurnal rhythm to hospital mortality in the data set, peaking in the evening, as well as the well-known 'weekend-effect' where mortality peaks with weekend admissions. Individual models had modest performance on the test data set (AUC 0.71, 0.79 and 0.79 respectively). The combined model which included time-varying risk however yielded an average AUC of 0.92. This model performed best for stays up to 7-days (93% of admissions), peaking at days 3 to 5 (AUC 0.94). Risks of hospitalization vary not just with the day of the week but also time of the day, and can be used to make predictions about the cumulative risk of death associated with an individual's hospitalization. Combining disease specific models with such time varying- estimates appears to result in robust predictive performance. Such risk exposure models should find utility both in enhancing standard prognostic models as well as estimating the risk of continuation of hospitalization.

Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

PubMed

Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

2012-08-01

Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis.

PubMed

Crowson, Cynthia S; Rollefstad, Silvia; Kitas, George D; van Riel, Piet L C M; Gabriel, Sherine E; Semb, Anne Grete

2017-01-01

Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

Identification of foot and mouth disease risk areas using a multi-criteria analysis approach

PubMed Central

Silva, Gustavo Sousa e; Weber, Eliseu José; Hasenack, Heinrich; Groff, Fernando Henrique Sautter; Todeschini, Bernardo; Borba, Mauro Riegert; Medeiros, Antonio Augusto Rosa; Leotti, Vanessa Bielefeldt; Canal, Cláudio Wageck; Corbellini, Luis Gustavo

2017-01-01

Foot and mouth disease (FMD) is a highly infectious disease that affects cloven-hoofed livestock and wildlife. FMD has been a problem for decades, which has led to various measures to control, eradicate and prevent FMD by National Veterinary Services worldwide. Currently, the identification of areas that are at risk of FMD virus incursion and spread is a priority for FMD target surveillance after FMD is eradicated from a given country or region. In our study, a knowledge-driven spatial model was built to identify risk areas for FMD occurrence and to evaluate FMD surveillance performance in Rio Grande do Sul state, Brazil. For this purpose, multi-criteria decision analysis was used as a tool to seek multiple and conflicting criteria to determine a preferred course of action. Thirteen South American experts analyzed 18 variables associated with FMD introduction and dissemination pathways in Rio Grande do Sul. As a result, FMD higher risk areas were identified at international borders and in the central region of the state. The final model was expressed as a raster surface. The predictive ability of the model assessed by comparing, for each cell of the raster surface, the computed model risk scores with a binary variable representing the presence or absence of an FMD outbreak in that cell during the period 1985 to 2015. Current FMD surveillance performance was assessed, and recommendations were made to improve surveillance activities in critical areas. PMID:28552973

Impacts of climate change on current methodologies for flood risk analysis: Watershed-scale analyses using the Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Spellman, P.; Griffis, V. W.; LaFond, K.

2013-12-01

A changing climate brings about new challenges for flood risk analysis and water resources planning and management. Current methods for estimating flood risk in the US involve fitting the Pearson Type III (P3) probability distribution to the logarithms of the annual maximum flood (AMF) series using the method of moments. These methods are employed under the premise of stationarity, which assumes that the fitted distribution is time invariant and variables affecting stream flow such as climate do not fluctuate. However, climate change would bring about shifts in meteorological forcings which can alter the summary statistics (mean, variance, skew) of flood series used for P3 parameter estimation, resulting in erroneous flood risk projections. To ascertain the degree to which future risk may be misrepresented by current techniques, we use climate scenarios generated from global climate models (GCMs) as input to a hydrological model to explore how relative changes to current climate affect flood response for watersheds in the northeastern United States. The watersheds were calibrated and run on a daily time step using the continuous, semi-distributed, process based Soil and Water Assessment Tool (SWAT). Nash Sutcliffe Efficiency (NSE), RMSE to Standard Deviation ratio (RSR) and Percent Bias (PBIAS) were all used to assess model performance. Eight climate scenarios were chosen from GCM output based on relative precipitation and temperature changes from the current climate of the watershed and then further bias-corrected. Four of the scenarios were selected to represent warm-wet, warm-dry, cool-wet and cool-dry future climates, and the other four were chosen to represent more extreme, albeit possible, changes in precipitation and temperature. We quantify changes in response by comparing the differences in total mass balance and summary statistics of the logarithms of the AMF series from historical baseline values. We then compare forecasts of flood quantiles from fitting a P3 distribution to the logs of historical AMF data to that of generated AMF series.

Concepts and challenges in cancer risk prediction for the space radiation environment

NASA Astrophysics Data System (ADS)

Barcellos-Hoff, Mary Helen; Blakely, Eleanor A.; Burma, Sandeep; Fornace, Albert J.; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G.; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M.

2015-07-01

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program.

Developing Statistical Models to Assess Transplant Outcomes Using National Registries: The Process in the United States.

PubMed

Snyder, Jon J; Salkowski, Nicholas; Kim, S Joseph; Zaun, David; Xiong, Hui; Israni, Ajay K; Kasiske, Bertram L

2016-02-01

Created by the US National Organ Transplant Act in 1984, the Scientific Registry of Transplant Recipients (SRTR) is obligated to publicly report data on transplant program and organ procurement organization performance in the United States. These reports include risk-adjusted assessments of graft and patient survival, and programs performing worse or better than expected are identified. The SRTR currently maintains 43 risk adjustment models for assessing posttransplant patient and graft survival and, in collaboration with the SRTR Technical Advisory Committee, has developed and implemented a new systematic process for model evaluation and revision. Patient cohorts for the risk adjustment models are identified, and single-organ and multiorgan transplants are defined, then each risk adjustment model is developed following a prespecified set of steps. Model performance is assessed, the model is refit to a more recent cohort before each evaluation cycle, and then it is applied to the evaluation cohort. The field of solid organ transplantation is unique in the breadth of the standardized data that are collected. These data allow for quality assessment across all transplant providers in the United States. A standardized process of risk model development using data from national registries may enhance the field.

Socioeconomic indicators of heat-related health risk supplemented with remotely sensed data

PubMed Central

Johnson, Daniel P; Wilson, Jeffrey S; Luber, George C

2009-01-01

Background Extreme heat events are the number one cause of weather-related fatalities in the United States. The current system of alert for extreme heat events does not take into account intra-urban spatial variation in risk. The purpose of this study is to evaluate a potential method to improve spatial delineation of risk from extreme heat events in urban environments by integrating sociodemographic risk factors with estimates of land surface temperature derived from thermal remote sensing data. Results Comparison of logistic regression models indicates that supplementing known sociodemographic risk factors with remote sensing estimates of land surface temperature improves the delineation of intra-urban variations in risk from extreme heat events. Conclusion Thermal remote sensing data can be utilized to improve understanding of intra-urban variations in risk from extreme heat. The refinement of current risk assessment systems could increase the likelihood of survival during extreme heat events and assist emergency personnel in the delivery of vital resources during such disasters. PMID:19835578

How to use mechanistic effect models in environmental risk assessment of pesticides: Case studies and recommendations from the SETAC workshop MODELINK.

PubMed

Hommen, Udo; Forbes, Valery; Grimm, Volker; Preuss, Thomas G; Thorbek, Pernille; Ducrot, Virginie

2016-01-01

Mechanistic effect models (MEMs) are useful tools for ecological risk assessment of chemicals to complement experimentation. However, currently no recommendations exist for how to use them in risk assessments. Therefore, the Society of Environmental Toxicology and Chemistry (SETAC) MODELINK workshop aimed at providing guidance for when and how to apply MEMs in regulatory risk assessments. The workshop focused on risk assessment of plant protection products under Regulation (EC) No 1107/2009 using MEMs at the organism and population levels. Realistic applications of MEMs were demonstrated in 6 case studies covering assessments for plants, invertebrates, and vertebrates in aquatic and terrestrial habitats. From the case studies and their evaluation, 12 recommendations on the future use of MEMs were formulated, addressing the issues of how to translate specific protection goals into workable questions, how to select species and scenarios to be modeled, and where and how to fit MEMs into current and future risk assessment schemes. The most important recommendations are that protection goals should be made more quantitative; the species to be modeled must be vulnerable not only regarding toxic effects but also regarding their life history and dispersal traits; the models should be as realistic as possible for a specific risk assessment question, and the level of conservatism required for a specific risk assessment should be reached by designing appropriately conservative environmental and exposure scenarios; scenarios should include different regions of the European Union (EU) and different crops; in the long run, generic MEMs covering relevant species based on representative scenarios should be developed, which will require EU-level joint initiatives of all stakeholders involved. The main conclusion from the MODELINK workshop is that the considerable effort required for making MEMs an integral part of environmental risk assessment of pesticides is worthwhile, because it will make risk assessments not only more ecologically relevant and less uncertain but also more comprehensive, coherent, and cost effective. © 2015 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC.

Review of methods for developing regional probabilistic risk assessments, part 2: modeling invasive plant, insect, and pathogen species

Treesearch

P. B. Woodbury; D. A. Weinstein

2010-01-01

We reviewed probabilistic regional risk assessment methodologies to identify the methods that are currently in use and are capable of estimating threats to ecosystems from fire and fuels, invasive species, and their interactions with stressors. In a companion chapter, we highlight methods useful for evaluating risks from fire. In this chapter, we highlight methods...

Risk Aversion and Public Reporting. Part 2: Mitigation Strategies.

PubMed

Shahian, David M; Jacobs, Jeffrey P; Badhwar, Vinay; D'Agostino, Richard S; Bavaria, Joseph E; Prager, Richard L

2017-12-01

Part 1 of this review summarizes the consequences of risk aversion and the observational studies and surveys relevant to this phenomenon, almost all of which are derived from cardiac surgery and interventional cardiology. In Part 2, we describe the root cause of risk aversion-the belief by providers that current risk adjustment is inadequate to account for the severity of their highest-risk patients, thereby prejudicing their publicly reported performance scores. Evidence supporting the robustness of current risk adjustment is presented, as well as nine potential strategies to further mitigate risk aversion: optimization of data source, risk models, and performance measures; exclusion of high-risk patients; exclusion of non-procedure-related end points; separate reporting of high-risk patients; reporting by condition or diagnosis rather than by procedures; reporting at the hospital or program level rather than the physician level; collaborative, cross-disciplinary decision making; active surveillance for risk aversion; and improved stakeholder education. Of these, the first is most desirable, widely applicable, and resistant to gaming. Copyright © 2017 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Two risk score models for predicting incident Type 2 diabetes in Japan.

PubMed

Doi, Y; Ninomiya, T; Hata, J; Hirakawa, Y; Mukai, N; Iwase, M; Kiyohara, Y

2012-01-01

Risk scoring methods are effective for identifying persons at high risk of Type 2 diabetes mellitus, but such approaches have not yet been established in Japan. A total of 1935 subjects of a derivation cohort were followed up for 14 years from 1988 and 1147 subjects of a validation cohort independent of the derivation cohort were followed up for 5 years from 2002. Risk scores were estimated based on the coefficients (β) of Cox proportional hazards model in the derivation cohort and were verified in the validation cohort. In the derivation cohort, the non-invasive risk model was established using significant risk factors; namely, age, sex, family history of diabetes, abdominal circumference, body mass index, hypertension, regular exercise and current smoking. We also created another scoring risk model by adding fasting plasma glucose levels to the non-invasive model (plus-fasting plasma glucose model). The area under the curve of the non-invasive model was 0.700 and it increased significantly to 0.772 (P < 0.001) in the plus-fasting plasma glucose model. The ability of the non-invasive model to predict Type 2 diabetes was comparable with that of impaired glucose tolerance, and the plus-fasting plasma glucose model was superior to it. The cumulative incidence of Type 2 diabetes was significantly increased with elevating quintiles of the sum scores of both models in the validation cohort (P for trend < 0.001). We developed two practical risk score models for easily identifying individuals at high risk of incident Type 2 diabetes without an oral glucose tolerance test in the Japanese population. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

Framework for Modeling High-Impact, Low-Frequency Power Grid Events to Support Risk-Informed Decisions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veeramany, Arun; Unwin, Stephen D.; Coles, Garill A.

2015-12-03

Natural and man-made hazardous events resulting in loss of grid infrastructure assets challenge the electric power grid’s security and resilience. However, the planning and allocation of appropriate contingency resources for such events requires an understanding of their likelihood and the extent of their potential impact. Where these events are of low likelihood, a risk-informed perspective on planning can be problematic as there exists an insufficient statistical basis to directly estimate the probabilities and consequences of their occurrence. Since risk-informed decisions rely on such knowledge, a basis for modeling the risk associated with high-impact low frequency events (HILFs) is essential. Insightsmore » from such a model can inform where resources are most rationally and effectively expended. The present effort is focused on development of a HILF risk assessment framework. Such a framework is intended to provide the conceptual and overarching technical basis for the development of HILF risk models that can inform decision makers across numerous stakeholder sectors. The North American Electric Reliability Corporation (NERC) 2014 Standard TPL-001-4 considers severe events for transmission reliability planning, but does not address events of such severity that they have the potential to fail a substantial fraction of grid assets over a region, such as geomagnetic disturbances (GMD), extreme seismic events, and coordinated cyber-physical attacks. These are beyond current planning guidelines. As noted, the risks associated with such events cannot be statistically estimated based on historic experience; however, there does exist a stable of risk modeling techniques for rare events that have proven of value across a wide range of engineering application domains. There is an active and growing interest in evaluating the value of risk management techniques in the State transmission planning and emergency response communities, some of this interest in the context of grid modernization activities. The availability of a grid HILF risk model, integrated across multi-hazard domains which, when interrogated, can support transparent, defensible and effective decisions, is an attractive prospect among these communities. In this report, we document an integrated HILF risk framework intended to inform the development of risk models. These models would be based on the systematic and comprehensive (to within scope) characterization of hazards to the level of detail required for modeling risk, identification of the stressors associated with the hazards (i.e., the means of impacting grid and supporting infrastructure), characterization of the vulnerability of assets to these stressors and the probabilities of asset compromise, the grid’s dynamic response to the asset failures, and assessment of subsequent severities of consequence with respect to selected impact metrics, such as power outage duration and geographic reach. Specifically, the current framework is being developed to;1. Provide the conceptual and overarching technical paradigms for the development of risk models; 2. Identify the classes of models required to implement the framework - providing examples of existing models, and also identifying where modeling gaps exist; 3. Identify the types of data required, addressing circumstances under which data are sparse and the formal elicitation of informed judgment might be required; and 4. Identify means by which the resultant risk models might be interrogated to form the necessary basis for risk management.« less

Are engineered nano iron oxide particles safe? an environmental risk assessment by probabilistic exposure, effects and risk modeling.

PubMed

Wang, Yan; Deng, Lei; Caballero-Guzman, Alejandro; Nowack, Bernd

2016-12-01

Nano iron oxide particles are beneficial to our daily lives through their use in paints, construction materials, biomedical imaging and other industrial fields. However, little is known about the possible risks associated with the current exposure level of engineered nano iron oxides (nano-FeOX) to organisms in the environment. The goal of this study was to predict the release of nano-FeOX to the environment and assess their risks for surface waters in the EU and Switzerland. The material flows of nano-FeOX to technical compartments (waste incineration and waste water treatment plants) and to the environment were calculated with a probabilistic modeling approach. The mean value of the predicted environmental concentrations (PECs) of nano-FeOX in surface waters in the EU for a worst-case scenario (no particle sedimentation) was estimated to be 28 ng/l. Using a probabilistic species sensitivity distribution, the predicted no-effect concentration (PNEC) was determined from ecotoxicological data. The risk characterization ratio, calculated by dividing the PEC by PNEC values, was used to characterize the risks. The mean risk characterization ratio was predicted to be several orders of magnitude smaller than 1 (1.4 × 10 - 4 ). Therefore, this modeling effort indicates that only a very limited risk is posed by the current release level of nano-FeOX to organisms in surface waters. However, a better understanding of the hazards of nano-FeOX to the organisms in other ecosystems (such as sediment) needs to be assessed to determine the overall risk of these particles to the environment.

Comparison of current distributions in electroconvulsive therapy and transcranial magnetic stimulation

NASA Astrophysics Data System (ADS)

Sekino, Masaki; Ueno, Shoogo

2002-05-01

We compared current density distributions in electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) by numerical calculations. The model consisted of an air region and three types of tissues with different conductivities representing the brain, the skull, and the scalp. In the ECT model, electric currents were applied through electrodes with a voltage of 100 V. In the TMS model, a figure-eight coil (6 cm diameter per coil) was placed on the vertex of the head model. An alternating current with a peak intensity of 3.0 kA and a frequency of 4.2 kHz was applied to the coil. The maximum current densities inside the brain in ECT (bilateral electrode position) and TMS were 234 and 322 A/m2, respectively. The results indicate that magnetic stimulators can generate comparable current densities to ECT. While the skull significantly affected current distributions in ECT, TMS efficiently induced eddy currents in the brain. In addition, TMS is more beneficial than ECT because the localized current distribution reduces the risk of adverse side effects.

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

NASA Technical Reports Server (NTRS)

2012-01-01

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model1 reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties--2010 . The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables. The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements. However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors, transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Improving poverty and inequality modelling in climate research

NASA Astrophysics Data System (ADS)

Rao, Narasimha D.; van Ruijven, Bas J.; Riahi, Keywan; Bosetti, Valentina

2017-12-01

As climate change progresses, the risk of adverse impacts on vulnerable populations is growing. As governments seek increased and drastic action, policymakers are likely to seek quantification of climate-change impacts and the consequences of mitigation policies on these populations. Current models used in climate research have a limited ability to represent the poor and vulnerable, or the different dimensions along which they face these risks. Best practices need to be adopted more widely, and new model features that incorporate social heterogeneity and different policy mechanisms need to be developed. Increased collaboration between modellers, economists, and other social scientists could aid these developments.

Quantitative risk assessment of human salmonellosis in Canadian broiler chicken breast from retail to consumption.

PubMed

Smadi, Hanan; Sargeant, Jan M

2013-02-01

The current quantitative risk assessment model followed the framework proposed by the Codex Alimentarius to provide an estimate of the risk of human salmonellosis due to consumption of chicken breasts which were bought from Canadian retail stores and prepared in Canadian domestic kitchens. The model simulated the level of Salmonella contamination on chicken breasts throughout the retail-to-table pathway. The model used Canadian input parameter values, where available, to represent risk of salmonellosis. From retail until consumption, changes in the concentration of Salmonella on each chicken breast were modeled using equations for growth and inactivation. The model predicted an average of 318 cases of salmonellosis per 100,000 consumers per year. Potential reasons for this overestimation were discussed. A sensitivity analysis showed that concentration of Salmonella on chicken breasts at retail and food hygienic practices in private kitchens such as cross-contamination due to not washing cutting boards (or utensils) and hands after handling raw meat along with inadequate cooking contributed most significantly to the risk of human salmonellosis. The outcome from this model emphasizes that responsibility for protection from Salmonella hazard on chicken breasts is a shared responsibility. Data needed for a comprehensive Canadian Salmonella risk assessment were identified for future research. © 2012 Society for Risk Analysis.

Development and validation of risk models and molecular diagnostics to permit personalized management of cancer.

PubMed

Pu, Xia; Ye, Yuanqing; Wu, Xifeng

2014-01-01

Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.

[Remuneration distribution - should morbidity-dependent overall remuneration also be distributed after adjustments for morbidity?].

PubMed

Walendzik, A; Trottmann, M; Leonhardt, R; Wasem, J

2013-04-01

In the 2009 reform of the German collective remuneration system for outpatient medical care, on the level of overall remuneration, the morbidity risk was transferred to the health funds fulfilling a long-term demand of physicians. Nevertheless not transferring morbidity adjustment to the levels of physician groups and singular practices can lead to budgets not related to patient needs and to incentives for risk selection for individual doctors. The systematics of the distribution of overall remuneration in the German remuneration system for outpatient care are analysed focusing on the aspect of morbidity adjustment. Using diagnostic and pharmaceutical information of about half a million insured subjects, a risk adjustment model able to predict individual expenditures for outpatient care for different provider groups is presented. This model enables to additively split the individual care burden into several parts attributed to different physician groups. Conditions for the use of the model in the distribution of overall remuneration between physician groups are developed. A simulation of the use of diagnoses-based risk adjustment in standard service volumes then highlights the conditions for a successfull installation of standard service volumes representing a higher degree of risk adjustment. The presented estimation model is generally applicable for the distribution of overall remuneration to different physician groups. The simulation of standard service volumes using diagnosis-based risk adjustment does not provide a more accurate prediction of the expenditures on the level of physician practices than the age-related calculation currently used in the German remuneration system for outpatient medical care. Using elements of morbidity-based risk adjustment the current German collective system for outpatient medical care could be transformed towards a higher degree of distributional justice concerning medical care for patients and more appropriate incentives avoiding risk selection. Limitations of the applicability of risk-adjustment can be especially pointed out when a high share of lump-sum-payments is used for the remuneration of some physician groups. © Georg Thieme Verlag KG Stuttgart · New York.

Relative risk of reducing the lifetime blood donation deferral for men who have had sex with men versus currently tolerated transfusion risks.

PubMed

Vamvakas, Eleftherios C

2011-01-01

The risks of known and emerging transfusion-transmitted infections (TTIs) from reducing the current lifetime blood donation deferral for men who have had sex with men (MSM) to 1 or 5 years were compared to the risk from continuing to transfuse in the United States 12.5% of platelet doses as pooled whole-blood-derived (rather than single-donor) platelets. Assumptions made in mathematical models and blood donor/transfusion studies of the risks of TTIs since 2000 were evaluated. The number of HIV, hepatitis B virus, or hepatitis C virus TTIs from reducing the MSM deferral to 1 year is, respectively, 0.88, 2.94, or 66.9, many more than 10 times smaller than the risk from pooled platelets. If erroneous release of HIV-positive units (a risk independent of a donor's source of infection) is not considered, the MSM risk is 1 HIV-infectious donation per 17 to 56 million MSM donations. Any purportedly increased risk of human herpesvirus-8 transmission from MSM donors is far smaller than the risk of transfusion-associated sepsis from pooled platelets. Single-donor platelets from MSM after 5 years' abstinence are as safe or 5 times safer than our current pooled platelets--if the next TTI to emerge were transmitted, respectively, sexually or by another route. Thus, acceptance of MSM as blood donors after 1 or 5 years' abstinence may result in a postulated increase in risk that is so much smaller than the currently tolerated transfusion risk and so small in absolute terms that the ethical question of fairness to the MSM group justifies the change in policy. Copyright © 2011 Elsevier Inc. All rights reserved.

Biomechanical analysis on fracture risk associated with bone deformity

NASA Astrophysics Data System (ADS)

Kamal, Nur Amalina Nadiah Mustafa; Som, Mohd Hanafi Mat; Basaruddin, Khairul Salleh; Daud, Ruslizam

2017-09-01

Osteogenesis Imperfecta (OI) is a disease related to bone deformity and is also known as `brittle bone' disease. Currently, medical personnel predict the bone fracture solely based on their experience. In this study, the prediction for risk of fracture was carried out by using finite element analysis on the simulated OI bone of femur. The main objective of this research was to analyze the fracture risk of OI-affected bone with respect to various loadings. A total of 12 models of OI bone were developed by applying four load cases and the angle of deformation for each of the models was calculated. The models were differentiated into four groups, namely standard, light, mild and severe. The results show that only a small amount of load is required to increase the fracture risk of the bone when the model is tested with hopping conditions. The analysis also shows that the torsional load gives a small effect to the increase of the fracture risk of the bone.

Past Decline Versus Current eGFR and Subsequent ESRD Risk.

PubMed

Kovesdy, Csaba P; Coresh, Josef; Ballew, Shoshana H; Woodward, Mark; Levin, Adeera; Naimark, David M J; Nally, Joseph; Rothenbacher, Dietrich; Stengel, Benedicte; Iseki, Kunitoshi; Matsushita, Kunihiro; Levey, Andrew S

2016-08-01

eGFR is a robust predictor of ESRD risk. However, the prognostic information gained from the past trajectory (slope) beyond that of the current eGFR is unclear. We examined 22 cohorts to determine the association of past slopes and current eGFR level with subsequent ESRD. We modeled hazard ratios as a spline function of slopes, adjusting for demographic variables, eGFR, and comorbidities. We used random effects meta-analyses to combine results across studies stratified by cohort type. We calculated the absolute risk of ESRD at 5 years after the last eGFR using the weighted average baseline risk. Overall, 1,080,223 participants experienced 5163 ESRD events during a mean follow-up of 2.0 years. In CKD cohorts, a slope of -6 versus 0 ml/min per 1.73 m(2) per year over the previous 3 years (a decline of 18 ml/min per 1.73 m(2) versus no decline) associated with an adjusted hazard ratio of ESRD of 2.28 (95% confidence interval, 1.88 to 2.76). In contrast, a current eGFR of 30 versus 50 ml/min per 1.73 m(2) (a difference of 20 ml/min per 1.73 m(2)) associated with an adjusted hazard ratio of 19.9 (95% confidence interval, 13.6 to 29.1). Past decline contributed more to the absolute risk of ESRD at lower than higher levels of current eGFR. In conclusion, during a follow-up of 2 years, current eGFR associates more strongly with future ESRD risk than the magnitude of past eGFR decline, but both contribute substantially to the risk of ESRD, especially at eGFR<30 ml/min per 1.73 m(2). Copyright © 2016 by the American Society of Nephrology.

Official Positions for FRAX® clinical regarding falls and frailty: can falls and frailty be used in FRAX®? From Joint Official Positions Development Conference of the International Society for Clinical Densitometry and International Osteoporosis Foundation on FRAX®.

PubMed

Masud, Tahir; Binkley, Neil; Boonen, Steven; Hannan, Marian T

2011-01-01

Risk factors for fracture can be purely skeletal, e.g., bone mass, microarchitecture or geometry, or a combination of bone and falls risk related factors such as age and functional status. The remit of this Task Force was to review the evidence and consider if falls should be incorporated into the FRAX® model or, alternatively, to provide guidance to assist clinicians in clinical decision-making for patients with a falls history. It is clear that falls are a risk factor for fracture. Fracture probability may be underestimated by FRAX® in individuals with a history of frequent falls. The substantial evidence that various interventions are effective in reducing falls risk was reviewed. Targeting falls risk reduction strategies towards frail older people at high risk for indoor falls is appropriate. This Task Force believes that further fracture reduction requires measures to reduce falls risk in addition to bone directed therapy. Clinicians should recognize that patients with frequent falls are at higher fracture risk than currently estimated by FRAX® and include this in decision-making. However, quantitative adjustment of the FRAX® estimated risk based on falls history is not currently possible. In the long term, incorporation of falls as a risk factor in the FRAX® model would be ideal. Copyright © 2011 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

A fuzzy model for assessing risk of occupational safety in the processing industry.

PubMed

Tadic, Danijela; Djapan, Marko; Misita, Mirjana; Stefanovic, Miladin; Milanovic, Dragan D

2012-01-01

Managing occupational safety in any kind of industry, especially in processing, is very important and complex. This paper develops a new method for occupational risk assessment in the presence of uncertainties. Uncertain values of hazardous factors and consequence frequencies are described with linguistic expressions defined by a safety management team. They are modeled with fuzzy sets. Consequence severities depend on current hazardous factors, and their values are calculated with the proposed procedure. The proposed model is tested with real-life data from fruit processing firms in Central Serbia.

GREENSCOPE: A Method for Modeling Chemical Process Sustainability

EPA Science Inventory

Current work within the U.S. Environmental Protection Agency’s National Risk Management Research Laboratory is focused on the development of a method for modeling chemical process sustainability. The GREENSCOPE methodology, defined for the four bases of Environment, Economics, Ef...

MODEL HARMONIZATION POTENTIAL AND BENEFITS

EPA Science Inventory

The IPCS Harmonization Project, which is currently ongoing under the auspices of the WHO, in the context of chemical risk assessment or exposure modeling, does not imply global standardization. Instead, harmonization is thought of as an effort to strive for consistency among appr...

Alternative Strategies to Achieve Cardiovascular Mortality Goals in China and India: A Microsimulation of Target- Versus Risk-Based Blood Pressure Treatment.

PubMed

Basu, Sanjay; Yudkin, John S; Sussman, Jeremy B; Millett, Christopher; Hayward, Rodney A

2016-03-01

The World Health Organization aims to reduce mortality from chronic diseases including cardiovascular disease (CVD) by 25% by 2025. High blood pressure is a leading CVD risk factor. We sought to compare 3 strategies for treating blood pressure in China and India: a treat-to-target (TTT) strategy emphasizing lowering blood pressure to a target, a benefit-based tailored treatment (BTT) strategy emphasizing lowering CVD risk, or a hybrid strategy currently recommended by the World Health Organization. We developed a microsimulation model of adults aged 30 to 70 years in China and in India to compare the 2 treatment approaches across a 10-year policy-planning horizon. In the model, a BTT strategy treating adults with a 10-year CVD event risk of ≥ 10% used similar financial resources but averted ≈ 5 million more disability-adjusted life-years in both China and India than a TTT approach based on current US guidelines. The hybrid strategy in the current World Health Organization guidelines produced no substantial benefits over TTT. BTT was more cost-effective at $205 to $272/disability-adjusted life-year averted, which was $142 to $182 less per disability-adjusted life-year than TTT or hybrid strategies. The comparative effectiveness of BTT was robust to uncertainties in CVD risk estimation and to variations in the age range analyzed, the BTT treatment threshold, or rates of treatment access, adherence, or concurrent statin therapy. In model-based analyses, a simple BTT strategy was more effective and cost-effective than TTT or hybrid strategies in reducing mortality. © 2016 American Heart Association, Inc.

Visualization of risk of radiogenic second cancer in the organs and tissues of the human body.

PubMed

Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D

2015-04-28

Radiogenic second cancer is a common late effect in long term cancer survivors. Currently there are few methods or tools available to visually evaluate the spatial distribution of risks of radiogenic late effects in the human body. We developed a risk visualization method and demonstrated it for radiogenic second cancers in tissues and organs of one patient treated with photon volumetric modulated arc therapy and one patient treated with proton craniospinal irradiation. Treatment plans were generated using radiotherapy treatment planning systems (TPS) and dose information was obtained from TPS. Linear non-threshold risk coefficients for organs at risk of second cancer incidence were taken from the Biological Effects of Ionization Radiation VII report. Alternative risk models including linear exponential model and linear plateau model were also examined. The predicted absolute lifetime risk distributions were visualized together with images of the patient anatomy. The risk distributions of second cancer for the two patients were visually presented. The risk distributions varied with tissue, dose, dose-risk model used, and the risk distribution could be similar to or very different from the dose distribution. Our method provides a convenient way to directly visualize and evaluate the risks of radiogenic second cancer in organs and tissues of the human body. In the future, visual assessment of risk distribution could be an influential determinant for treatment plan scoring.

Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

NASA Astrophysics Data System (ADS)

Niu, Wei; Wang, Xifu

2018-01-01

The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

Higher Mortality in registrants with sudden model for end-stage liver disease increase: Disadvantaged by the current allocation policy.

PubMed

Massie, Allan B; Luo, Xun; Alejo, Jennifer L; Poon, Anna K; Cameron, Andrew M; Segev, Dorry L

2015-05-01

Liver allocation is based on current Model for End-Stage Liver Disease (MELD) scores, with priority in the case of a tie being given to those waiting the longest with a given MELD score. We hypothesized that this priority might not reflect risk: registrants whose MELD score has recently increased receive lower priority but might have higher wait-list mortality. We studied wait-list and posttransplant mortality in 69,643 adult registrants from 2002 to 2013. By likelihood maximization, we empirically defined a MELD spike as a MELD increase ≥ 30% over the previous 7 days. At any given time, only 0.6% of wait-list patients experienced a spike; however, these patients accounted for 25% of all wait-list deaths. Registrants who reached a given MELD score after a spike had higher wait-list mortality in the ensuing 7 days than those with the same resulting MELD score who did not spike, but they had no difference in posttransplant mortality. The spike-associated wait-list mortality increase was highest for registrants with medium MELD scores: specifically, 2.3-fold higher (spike versus no spike) for a MELD score of 10, 4.0-fold higher for a MELD score of 20, and 2.5-fold higher for a MELD score of 30. A model incorporating the MELD score and spikes predicted wait-list mortality risk much better than a model incorporating only the MELD score. Registrants with a sudden MELD increase have a higher risk of short-term wait-list mortality than is indicated by their current MELD score but have no increased risk of posttransplant mortality; allocation policy should be adjusted accordingly. © 2015 American Association for the Study of Liver Diseases.

A partial Hamiltonian approach for current value Hamiltonian systems

NASA Astrophysics Data System (ADS)

Naz, R.; Mahomed, F. M.; Chaudhry, Azam

2014-10-01

We develop a partial Hamiltonian framework to obtain reductions and closed-form solutions via first integrals of current value Hamiltonian systems of ordinary differential equations (ODEs). The approach is algorithmic and applies to many state and costate variables of the current value Hamiltonian. However, we apply the method to models with one control, one state and one costate variable to illustrate its effectiveness. The current value Hamiltonian systems arise in economic growth theory and other economic models. We explain our approach with the help of a simple illustrative example and then apply it to two widely used economic growth models: the Ramsey model with a constant relative risk aversion (CRRA) utility function and Cobb Douglas technology and a one-sector AK model of endogenous growth are considered. We show that our newly developed systematic approach can be used to deduce results given in the literature and also to find new solutions.

Empirically evaluating decision-analytic models.

PubMed

Goldhaber-Fiebert, Jeremy D; Stout, Natasha K; Goldie, Sue J

2010-08-01

Model-based cost-effectiveness analyses support decision-making. To augment model credibility, evaluation via comparison to independent, empirical studies is recommended. We developed a structured reporting format for model evaluation and conducted a structured literature review to characterize current model evaluation recommendations and practices. As an illustration, we applied the reporting format to evaluate a microsimulation of human papillomavirus and cervical cancer. The model's outputs and uncertainty ranges were compared with multiple outcomes from a study of long-term progression from high-grade precancer (cervical intraepithelial neoplasia [CIN]) to cancer. Outcomes included 5 to 30-year cumulative cancer risk among women with and without appropriate CIN treatment. Consistency was measured by model ranges overlapping study confidence intervals. The structured reporting format included: matching baseline characteristics and follow-up, reporting model and study uncertainty, and stating metrics of consistency for model and study results. Structured searches yielded 2963 articles with 67 meeting inclusion criteria and found variation in how current model evaluations are reported. Evaluation of the cervical cancer microsimulation, reported using the proposed format, showed a modeled cumulative risk of invasive cancer for inadequately treated women of 39.6% (30.9-49.7) at 30 years, compared with the study: 37.5% (28.4-48.3). For appropriately treated women, modeled risks were 1.0% (0.7-1.3) at 30 years, study: 1.5% (0.4-3.3). To support external and projective validity, cost-effectiveness models should be iteratively evaluated as new studies become available, with reporting standardized to facilitate assessment. Such evaluations are particularly relevant for models used to conduct comparative effectiveness analyses.

Effects of risk disclosure prominence in direct-to-consumer advertising (DTCA) of prescription drugs: An integrative cognitive process model.

PubMed

Ju, Ilwoo; Park, Jin Seong

2018-01-01

The literature shows that the prominence of risk disclosure influences consumer responses to direct-to-consumer advertising of prescription drugs. However, little is known about the psychological process whereby disclosure prominence exerts its influences on health beliefs and behavior. Based on a review of the literature on health cognition and behavior, the current study proposed and tested a model to show that risk disclosure prominence affects consumers' drug choice intention through the mediating roles of awareness of drug adverse reactions (ARs), perceived control over ARs, and perceived risk of ARs. The findings were discussed in terms of their theoretical and managerial implications.

Estimating community health needs against a Triple Aim background: What can we learn from current predictive risk models?

PubMed

Elissen, Arianne M J; Struijs, Jeroen N; Baan, Caroline A; Ruwaard, Dirk

2015-05-01

To support providers and commissioners in accurately assessing their local populations' health needs, this study produces an overview of Dutch predictive risk models for health care, focusing specifically on the type, combination and relevance of included determinants for achieving the Triple Aim (improved health, better care experience, and lower costs). We conducted a mixed-methods study combining document analyses, interviews and a Delphi study. Predictive risk models were identified based on a web search and expert input. Participating in the study were Dutch experts in predictive risk modelling (interviews; n=11) and experts in healthcare delivery, insurance and/or funding methodology (Delphi panel; n=15). Ten predictive risk models were analysed, comprising 17 unique determinants. Twelve were considered relevant by experts for estimating community health needs. Although some compositional similarities were identified between models, the combination and operationalisation of determinants varied considerably. Existing predictive risk models provide a good starting point, but optimally balancing resources and targeting interventions on the community level will likely require a more holistic approach to health needs assessment. Development of additional determinants, such as measures of people's lifestyle and social network, may require policies pushing the integration of routine data from different (healthcare) sources. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

A modeling framework for exposing risks in complex systems.

PubMed

Sharit, J

2000-08-01

This article introduces and develops a modeling framework for exposing risks in the form of human errors and adverse consequences in high-risk systems. The modeling framework is based on two components: a two-dimensional theory of accidents in systems developed by Perrow in 1984, and the concept of multiple system perspectives. The theory of accidents differentiates systems on the basis of two sets of attributes. One set characterizes the degree to which systems are interactively complex; the other emphasizes the extent to which systems are tightly coupled. The concept of multiple perspectives provides alternative descriptions of the entire system that serve to enhance insight into system processes. The usefulness of these two model components derives from a modeling framework that cross-links them, enabling a variety of work contexts to be exposed and understood that would otherwise be very difficult or impossible to identify. The model components and the modeling framework are illustrated in the case of a large and comprehensive trauma care system. In addition to its general utility in the area of risk analysis, this methodology may be valuable in applications of current methods of human and system reliability analysis in complex and continually evolving high-risk systems.

Using the negative exponential distribution to quantitatively review the evidence on how rapidly the excess risk of ischaemic heart disease declines following quitting smoking.

PubMed

Lee, Peter N; Fry, John S; Hamling, Jan S

2012-10-01

No previous review has formally modelled the decline in IHD risk following quitting smoking. From PubMed searches and other sources we identified 15 prospective and eight case-control studies that compared IHD risk in current smokers, never smokers, and quitters by time period of quit, some studies providing separate blocks of results by sex, age or amount smoked. For each of 41 independent blocks, we estimated, using the negative exponential model, the time, H, when the excess risk reduced to half that caused by smoking. Goodness-of-fit to the model was adequate for 35 blocks, others showing a non-monotonic pattern of decline following quitting, with a variable pattern of misfit. After omitting one block with a current smoker RR 1.0, the combined H estimate was 4.40 (95% CI 3.26-5.95) years. There was considerable heterogeneity, H being <2years for 10 blocks and >10years for 12. H increased (p<0.001) with mean age at study start, but not clearly with other factors. Sensitivity analyses allowing for reverse causation, or varying assumed midpoint times for the final open-ended quitting period little affected goodness-of-fit of the combined estimate. The US Surgeon-General's view that excess risk approximately halves after a year's abstinence seems over-optimistic. Copyright © 2012 Elsevier Inc. All rights reserved.

Age-Dependent Risk of Graft Failure in Young Kidney Transplant Recipients.

PubMed

Kaboré, Rémi; Couchoud, Cécile; Macher, Marie-Alice; Salomon, Rémi; Ranchin, Bruno; Lahoche, Annie; Roussey-Kesler, Gwenaelle; Garaix, Florentine; Decramer, Stéphane; Pietrement, Christine; Lassalle, Mathilde; Baudouin, Véronique; Cochat, Pierre; Niaudet, Patrick; Joly, Pierre; Leffondré, Karen; Harambat, Jérôme

2017-06-01

The risk of graft failure in young kidney transplant recipients has been found to increase during adolescence and early adulthood. However, this question has not been addressed outside the United States so far. Our objective was to investigate whether the hazard of graft failure also increases during this age period in France irrespective of age at transplantation. Data of all first kidney transplantation performed before 30 years of age between 1993 and 2012 were extracted from the French kidney transplant database. The hazard of graft failure was estimated at each current age using a 2-stage modelling approach that accounted for both age at transplantation and time since transplantation. Hazard ratios comparing the risk of graft failure during adolescence or early adulthood to other periods were estimated from time-dependent Cox models. A total of 5983 renal transplant recipients were included. The risk of graft failure was found to increase around the age of 13 years until the age of 21 years, and decrease thereafter. Results from the Cox model indicated that the hazard of graft failure during the age period 13 to 23 years was almost twice as high as than during the age period 0 to 12 years, and 25% higher than after 23 years. Among first kidney transplant recipients younger than 30 years in France, those currently in adolescence or early adulthood have the highest risk of graft failure.

Building a Better Model: A Personalized Breast Cancer Risk Model Incorporating Breast Density to Stratify Risk and Improve Application of Resources

DTIC Science & Technology

2013-10-01

a GE unit and 100 images from a Hologic unit. These were reviewed during Dr. Harvey’s visit to Toronto October 2012. The ...patient underwent the standard of practice 4-view mammogram. Following this, a different technologist obtained a second craniocaudal image of the left...project and one related to a current event. Representatives from the project were present to provide information at the Charlottesville Four

Asteroid-Generated Tsunami and Impact Risk

NASA Astrophysics Data System (ADS)

Boslough, M.; Aftosmis, M.; Berger, M. J.; Ezzedine, S. M.; Gisler, G.; Jennings, B.; LeVeque, R. J.; Mathias, D.; McCoy, C.; Robertson, D.; Titov, V. V.; Wheeler, L.

2016-12-01

The justification for planetary defense comes from a cost/benefit analysis, which includes risk assessment. The contribution from ocean impacts and airbursts is difficult to quantify and represents a significant uncertainty in our assessment of the overall risk. Our group is currently working toward improved understanding of impact scenarios that can generate dangerous tsunami. The importance of asteroid-generated tsunami research has increased because a new Science Definition Team, at the behest of NASA's Planetary Defense Coordinating Office, is now updating the results of a 2003 study on which our current planetary defense policy is based Our group was formed to address this question on many fronts, including asteroid entry modeling, tsunami generation and propagation simulations, modeling of coastal run-ups, inundation, and consequences, infrastructure damage estimates, and physics-based probabilistic impact risk assessment. We also organized the Second International Workshop on Asteroid Threat Assessment, focused on asteroid-generated tsunami and associated risk (Aug. 23-24, 2016). We will summarize our progress and present the highlights of our workshop, emphasizing its relevance to earth and planetary science. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract DE-AC04-94AL85000.

Space-based solar power conversion and delivery systems study. Volume 5: Economic analysis

NASA Technical Reports Server (NTRS)

1977-01-01

Space-based solar power conversion and delivery systems are studied along with a variety of economic and programmatic issues relevant to their development and deployment. The costs, uncertainties and risks associated with the current photovoltaic Satellite Solar Power System (SSPS) configuration, and issues affecting the development of an economically viable SSPS development program are addressed. In particular, the desirability of low earth orbit (LEO) and geosynchronous (GEO) test satellites is examined and critical technology areas are identified. The development of SSPS unit production (nth item), and operation and maintenance cost models suitable for incorporation into a risk assessment (Monte Carlo) model (RAM) are reported. The RAM was then used to evaluate the current SSPS configuration expected costs and cost-risk associated with this configuration. By examining differential costs and cost-risk as a function of postulated technology developments, the critical technologies, that is, those which drive costs and/or cost-risk, are identified. It is shown that the key technology area deals with productivity in space, that is, the ability to fabricate and assemble large structures in space, not, as might be expected, with some hardware component technology.

Machine Learning for Social Services: A Study of Prenatal Case Management in Illinois.

PubMed

Pan, Ian; Nolan, Laura B; Brown, Rashida R; Khan, Romana; van der Boor, Paul; Harris, Daniel G; Ghani, Rayid

2017-06-01

To evaluate the positive predictive value of machine learning algorithms for early assessment of adverse birth risk among pregnant women as a means of improving the allocation of social services. We used administrative data for 6457 women collected by the Illinois Department of Human Services from July 2014 to May 2015 to develop a machine learning model for adverse birth prediction and improve upon the existing paper-based risk assessment. We compared different models and determined the strongest predictors of adverse birth outcomes using positive predictive value as the metric for selection. Machine learning algorithms performed similarly, outperforming the current paper-based risk assessment by up to 36%; a refined paper-based assessment outperformed the current assessment by up to 22%. We estimate that these improvements will allow 100 to 170 additional high-risk pregnant women screened for program eligibility each year to receive services that would have otherwise been unobtainable. Our analysis exhibits the potential for machine learning to move government agencies toward a more data-informed approach to evaluating risk and providing social services. Overall, such efforts will improve the efficiency of allocating resource-intensive interventions.

Contribution of nonprimate animal models in understanding the etiology of schizophrenia

PubMed Central

Lazar, Noah L.; Neufeld, Richard W.J.; Cain, Donald P.

2011-01-01

Schizophrenia is a severe psychiatric disorder that is characterized by positive and negative symptoms and cognitive impairments. The etiology of the disorder is complex, and it is thought to follow a multifactorial threshold model of inheritance with genetic and neurodevelopmental contributions to risk. Human studies are particularly useful in capturing the richness of the phenotype, but they are often limited to the use of correlational approaches. By assessing behavioural abnormalities in both humans and rodents, nonprimate animal models of schizophrenia provide unique insight into the etiology and mechanisms of the disorder. This review discusses the phenomenology and etiology of schizophrenia and the contribution of current nonprimate animal models with an emphasis on how research with models of neurotransmitter dysregulation, environmental risk factors, neurodevelopmental disruption and genetic risk factors can complement the literature on schizophrenia in humans. PMID:21247514

Drug development costs when financial risk is measured using the Fama-French three-factor model.

PubMed

Vernon, John A; Golec, Joseph H; Dimasi, Joseph A

2010-08-01

In a widely cited article, DiMasi, Hansen, and Grabowski (2003) estimate the average pre-tax cost of bringing a new molecular entity to market. Their base case estimate, excluding post-marketing studies, was $802 million (in $US 2000). Strikingly, almost half of this cost (or $399 million) is the cost of capital (COC) used to fund clinical development expenses to the point of FDA marketing approval. The authors used an 11% real COC computed using the capital asset pricing model (CAPM). But the CAPM is a single factor risk model, and multi-factor risk models are the current state of the art in finance. Using the Fama-French three factor model we find that the cost of drug development to be higher than the earlier estimate. Copyright (c) 2009 John Wiley & Sons, Ltd.

Application of Ecosystem Models to Assess Environmental Drivers of Mosquito Abundance and Virus Transmission Risk and Associated Public Health Implications of Climate and Land Use Change

NASA Astrophysics Data System (ADS)

Melton, F.; Barker, C.; Park, B.; Reisen, W.; Michaelis, A.; Wang, W.; Hashimoto, H.; Milesi, C.; Hiatt, S.; Nemani, R.

2008-12-01

The NASA Terrestrial Observation and Prediction System (TOPS) is a modeling framework that integrates satellite observations, meteorological observations, and ancillary data to support monitoring and modeling of ecosystem and land surface conditions in near real-time. TOPS provides spatially continuous gridded estimates of a suite of measurements describing environmental conditions, and these data products are currently being applied to support the development of new models capable of forecasting estimated mosquito abundance and transmission risk for mosquito-borne diseases such as West Nile virus. We present results from the modeling analyses, describe their incorporation into the California Vectorborne Disease Surveillance System, and describe possible implications of projected climate and land use change for patterns in mosquito abundance and transmission risk for West Nile virus in California.

Network simulation modeling of equine infectious anemia in the non-racehorse population in Japan.

PubMed

Hayama, Yoko; Kobayashi, Sota; Nishida, Takeshi; Muroga, Norihiko; Tsutsui, Toshiyuki

2012-01-01

An equine infectious anemia (EIA) transmission model was developed by constructing a network structure of horse movement patterns in a non-racehorse population. This model was then used to evaluate the effectiveness and efficiency of several EIA surveillance strategies. Because EIA had not been detected in Japan since 1993, it was appropriate to review the current surveillance strategy, which aims to eradicate EIA by intensive testing, and to consider alternative strategies suitable for the current EIA status in Japan. The non-racehorse population was divided into four sectors based on horse usage: the equestrian sector, private owner sector, exhibition sector, and fattening sector. To evaluate the risk of disease spread within and between sectors accompanied by horse movements, a stochastic individual-based network model was developed based on a previous survey of horse movement patterns. Surveillance parameters such as targeting sectors and frequency of testing were added into the model to compare surveillance strategies. The disease spread heterogeneously among sectors. Infection occurred mainly in the equestrian sector; the infection was less disseminated in other sectors. Therefore, we considered that the equestrian sector posed a higher risk of disease dissemination within and between sectors through horse movements. However, surveillance strategies targeting only the equestrian sector were not effective enough for early detection of the disease. Alternatively, targeting horses that moved permanently and those in the private owner sector in addition to the equestrian sector is recommended to achieve effectiveness equivalent to that of the current surveillance. In terms of surveillance efficacy, by increasing the testing interval (once yearly to once every 3 years), this testing scheme could reduce the number of tested horses to 44% of the current surveillance, while maintaining almost equivalent effectiveness. Intensive strategies targeting high-risk populations are considered to enhance effectiveness and efficiency of surveillance. The approach in this study may be helpful in the decision-making process that is involved in setting up strategies for risk-based surveillance. Copyright © 2011 Elsevier B.V. All rights reserved.

Estimating the decline in excess risk of cerebrovascular disease following quitting smoking--a systematic review based on the negative exponential model.

PubMed

Lee, Peter N; Fry, John S; Thornton, Alison J

2014-02-01

We attempted to quantify the decline in stroke risk following quitting using the negative exponential model, with methodology previously employed for IHD. We identified 22 blocks of RRs (from 13 studies) comparing current smokers, former smokers (by time quit) and never smokers. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We tried to estimate the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block. The method failed to converge or produced very variable estimates of H in nine blocks with a current smoker RR <1.40. Rejecting these, and combining blocks by amount smoked in one study where problems arose in model-fitting, the final analyses used 11 blocks. Goodness-of-fit was adequate for each block, the combined estimate of H being 4.78(95%CI 2.17-10.50) years. However, considerable heterogeneity existed, unexplained by any factor studied, with the random-effects estimate 3.08(1.32-7.16). Sensitivity analyses allowing for reverse causation or differing assumed times for the final quitting period gave similar results. The estimates of H are similar for stroke and IHD, and the individual estimates similarly heterogeneous. Fitting the model is harder for stroke, due to its weaker association with smoking. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Risk Management and Physical Modelling for Mountainous Natural Hazards

NASA Astrophysics Data System (ADS)

Lehning, Michael; Wilhelm, Christian

Population growth and climate change cause rapid changes in mountainous regions resulting in increased risks of floods, avalanches, debris flows and other natural hazards. Xevents are of particular concern, since attempts to protect against them result in exponentially growing costs. In this contribution, we suggest an integral risk management approach to dealing with natural hazards that occur in mountainous areas. Using the example of a mountain pass road, which can be protected from the danger of an avalanche by engineering (galleries) and/or organisational (road closure) measures, we show the advantage of an optimal combination of both versus the traditional approach, which is to rely solely on engineering structures. Organisational measures become especially important for Xevents because engineering structures cannot be designed for those events. However, organisational measures need a reliable and objective forecast of the hazard. Therefore, we further suggest that such forecasts should be developed using physical numerical modelling. We present the status of current approaches to using physical modelling to predict snow cover stability for avalanche warnings and peak runoff from mountain catchments for flood warnings. While detailed physical models can already predict peak runoff reliably, they are only used to support avalanche warnings. With increased process knowledge and computer power, current developments should lead to a enhanced role for detailed physical models in natural mountain hazard prediction.

An automated method to morph finite element whole-body human models with a wide range of stature and body shape for both men and women.

PubMed

Zhang, Kai; Cao, Libo; Fanta, Abeselom; Reed, Matthew P; Neal, Mark; Wang, Jenne-Tai; Lin, Chin-Hsu; Hu, Jingwen

2017-07-26

Field data analyses have shown that small female, obese, and/or older occupants are at increased risks of death and serious injury in motor-vehicle crashes compared with mid-size young men. The current adult finite element (FE) human models represent occupants in the same three body sizes (large male, mid-size male, and small female) as those for the contemporary adult crash dummies. Further, the time needed to develop an FE human model using the traditional method is measured in months or even years. In the current study, an improved regional mesh morphing method based on landmark-based radial basis function (RBF) interpolation was developed to rapidly morph a mid-size male FE human model into different geometry targets. A total of 100 human models with a wide range of human attributes were generated. A pendulum chest impact condition was applied to each model as an initial assessment of the resulting variability in response. The morphed models demonstrated mesh quality similar to the baseline model. The peak impact forces and chest deflections in the chest pendulum impacts varied substantially with different models, supportive of consideration of population variation in evaluating the occupant injury risks. The method developed in this study will enable future safety design optimizations targeting at various vulnerable populations that cannot be considered with the current models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating pixel- and polygon-based approaches to wildfire risk assessment: Application to a high-value watershed on the Pike and San Isabel National Forests, Colorado, USA

Treesearch

Matthew P. Thompson; Julie W. Gilbertson-Day; Joe H. Scott

2015-01-01

We develop a novel risk assessment approach that integrates complementary, yet distinct, spatial modeling approaches currently used in wildfire risk assessment. Motivation for this work stems largely from limitations of existing stochastic wildfire simulation systems, which can generate pixel-based outputs of fire behavior as well as polygon-based outputs of simulated...

COST VS. QUALITY IN DEMOGRAPHIC MODELLING: WHEN IS A VITAL RATE GOOD ENOUGH?

EPA Science Inventory

This presentation will focus on the assessment of quality for demographic parameters to be used in population-level risk assessment. Current population models can handle genetic, demographic, and environmental stochasticity, density dependence, and multiple stressors. However, cu...

Global risk from the atmospheric dispersion of radionuclides by nuclear power plant accidents in the coming decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2014-05-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 years (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential doses to humans from inhalation and ground-deposition exposures to radionuclides. We find that the risk of harmful doses due to inhalation is typically highest in the Northern Hemisphere during boreal winter, due to relatively shallow boundary layer development and limited mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed, our results suggest that the risk will become highest in China, followed by India and the USA.

Global risk from the atmospheric dispersion of radionuclides by nuclear power plant accidents in the coming decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2013-11-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 yr (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential dosages to humans from the inhalation and the exposure to ground deposited radionuclides. We find that the risk of harmful doses due to inhalation is typically highest during boreal winter due to relatively shallow boundary layer development and reduced mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed our results suggest that the risk will become highest in China, followed by India and the USA.

Global Risk from the Atmospheric Dispersion of Radionuclides by Nuclear Power Plant Accidents in the Coming Decades

NASA Astrophysics Data System (ADS)

Christoudias, T.; Proestos, Y.; Lelieveld, J.

2014-12-01

We estimate the global risk from the release and atmospheric dispersion of radionuclides from nuclear power plant accidents using the EMAC atmospheric chemistry-general circulation model. We included all nuclear reactors that are currently operational, under construction and planned or proposed. We implemented constant continuous emissions from each location in the model and simulated atmospheric transport and removal via dry and wet deposition processes over 20 years (2010-2030), driven by boundary conditions based on the IPCC A2 future emissions scenario. We present global overall and seasonal risk maps for potential surface layer concentrations and ground deposition of radionuclides, and estimate potential doses to humans from inhalation and ground-deposition exposures to radionuclides. We find that the risk of harmful doses due to inhalation is typically highest in the Northern Hemisphere during boreal winter, due to relatively shallow boundary layer development and limited mixing. Based on the continued operation of the current nuclear power plants, we calculate that the risk of radioactive contamination to the citizens of the USA will remain to be highest worldwide, followed by India and France. By including stations under construction and those that are planned and proposed, our results suggest that the risk will become highest in China, followed by India and the USA.

Predicting the risk of sudden cardiac death.

PubMed

Lerma, Claudia; Glass, Leon

2016-05-01

Sudden cardiac death (SCD) is the result of a change of cardiac activity from normal (typically sinus) rhythm to a rhythm that does not pump adequate blood to the brain. The most common rhythms leading to SCD are ventricular tachycardia (VT) or ventricular fibrillation (VF). These result from an accelerated ventricular pacemaker or ventricular reentrant waves. Despite significant efforts to develop accurate predictors for the risk of SCD, current methods for risk stratification still need to be improved. In this article we briefly review current approaches to risk stratification. Then we discuss the mathematical basis for dynamical transitions (called bifurcations) that may lead to VT and VF. One mechanism for transition to VT or VF involves a perturbation by a premature ventricular complex (PVC) during sinus rhythm. We describe the main mechanisms of PVCs (reentry, independent pacemakers and abnormal depolarizations). An emerging approach to risk stratification for SCD involves the development of individualized dynamical models of a patient based on measured anatomy and physiology. Careful analysis and modelling of dynamics of ventricular arrhythmia on an individual basis will be essential in order to improve risk stratification for SCD and to lay a foundation for personalized (precision) medicine in cardiology. © 2015 The Authors. The Journal of Physiology © 2015 The Physiological Society.

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2012 CFR

2012-10-01

... nature of the rail system, each carrier must select and document the analysis method/model used and identify the routes to be analyzed. D. The safety and security risk analysis must consider current data and... curvature; 7. Presence or absence of signals and train control systems along the route (“dark” versus...

Quantum chemistry in environmental pesticide risk assessment.

PubMed

Villaverde, Juan J; López-Goti, Carmen; Alcamí, Manuel; Lamsabhi, Al Mokhtar; Alonso-Prados, José L; Sandín-España, Pilar

2017-11-01

The scientific community and regulatory bodies worldwide, currently promote the development of non-experimental tests that produce reliable data for pesticide risk assessment. The use of standard quantum chemistry methods could allow the development of tools to perform a first screening of compounds to be considered for the experimental studies, improving the risk assessment. This fact results in a better distribution of resources and in better planning, allowing a more exhaustive study of the pesticides and their metabolic products. The current paper explores the potential of quantum chemistry in modelling toxicity and environmental behaviour of pesticides and their by-products by using electronic descriptors obtained computationally. Quantum chemistry has potential to estimate the physico-chemical properties of pesticides, including certain chemical reaction mechanisms and their degradation pathways, allowing modelling of the environmental behaviour of both pesticides and their by-products. In this sense, theoretical methods can contribute to performing a more focused risk assessment of pesticides used in the market, and may lead to higher quality and safer agricultural products. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Risk-Hedged Approach for Re-Routing Air Traffic Under Weather Uncertainty

NASA Technical Reports Server (NTRS)

Sadovsky, Alexander V.; Bilimoria, Karl D.

2016-01-01

This presentation corresponds to: our paper explores a new risk-hedged approach for re-routing air traffic around forecast convective weather. In this work, flying through a more likely weather instantiation is considered to pose a higher level of risk. Current operational practice strategically plans re-routes to avoid only the most likely (highest risk) weather instantiation, and then tactically makes any necessary adjustments as the weather evolves. The risk-hedged approach strategically plans re-routes by minimizing the risk-adjusted path length, incorporating multiple possible weather instantiations with associated likelihoods (risks). The resulting model is transparent and is readily analyzed for realism and treated with well-understood shortest-path algorithms. Risk-hedged re-routes are computed for some example weather instantiations. The main result is that in some scenarios, relative to an operational-practice proxy solution, the risk-hedged solution provides the benefits of lower risk as well as shorter path length. In other scenarios, the benefits of the risk-hedged solution are ambiguous, because the solution is characterized by a tradeoff between risk and path length. The risk-hedged solution can be executed in those scenarios where it provides a clear benefit over current operational practice.

Inclusion of Highest Glasgow Coma Scale Motor Component Score in Mortality Risk Adjustment for Benchmarking of Trauma Center Performance.

PubMed

Gomez, David; Byrne, James P; Alali, Aziz S; Xiong, Wei; Hoeft, Chris; Neal, Melanie; Subacius, Harris; Nathens, Avery B

2017-12-01

The Glasgow Coma Scale (GCS) is the most widely used measure of traumatic brain injury (TBI) severity. Currently, the arrival GCS motor component (mGCS) score is used in risk-adjustment models for external benchmarking of mortality. However, there is evidence that the highest mGCS score in the first 24 hours after injury might be a better predictor of death. Our objective was to evaluate the impact of including the highest mGCS score on the performance of risk-adjustment models and subsequent external benchmarking results. Data were derived from the Trauma Quality Improvement Program analytic dataset (January 2014 through March 2015) and were limited to the severe TBI cohort (16 years or older, isolated head injury, GCS ≤8). Risk-adjustment models were created that varied in the mGCS covariates only (initial score, highest score, or both initial and highest mGCS scores). Model performance and fit, as well as external benchmarking results, were compared. There were 6,553 patients with severe TBI across 231 trauma centers included. Initial and highest mGCS scores were different in 47% of patients (n = 3,097). Model performance and fit improved when both initial and highest mGCS scores were included, as evidenced by improved C-statistic, Akaike Information Criterion, and adjusted R-squared values. Three-quarters of centers changed their adjusted odds ratio decile, 2.6% of centers changed outlier status, and 45% of centers exhibited a ≥0.5-SD change in the odds ratio of death after including highest mGCS score in the model. This study supports the concept that additional clinical information has the potential to not only improve the performance of current risk-adjustment models, but can also have a meaningful impact on external benchmarking strategies. Highest mGCS score is a good potential candidate for inclusion in additional models. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

[From "deadly quartet" to "metabolic syndrome". An analysis of its clinical relevance].

PubMed

Vancheri, Federico; Burgio, Antonio; Dovico, Rossana

2007-03-01

The metabolic syndrome denotes a clustering of specific risk factors for both cardiovascular disease and type 2 diabetes, whose underlying pathophysiology is believed to include insulin resistance. It has been widely reported that the syndrome is a simple clinical tool to identify people at high long term risk of cardiovascular disease and diabetes. However, its clinical importance is under debate. There are substantial uncertainties about the clinical definition of the syndrome, as to whether the risk factors clustering indicates a single unifying disorder, whether the risk conferred by the condition as a whole is higher risk than its individual components, and whether its predictive value of future cardiovascular events or diabetes is greater than established predicting models such as the Framingham Risk Score and the Diabetes Risk Score. We undertook an extensive review of the literature. Our analysis indicates that current definitions of the syndrome are incomplete or ambiguous, more than one pathophysiological process underlies the syndrome, although the combination of insulin resistance and hyperinsulinemia are related to most cases; the risk associated with the syndrome is no greater than that explained by the presence of its components, and the syndrome is less effective in predicting the future development of cardiovascular events and diabetes than established predicting models. Although the syndrome has some importance in understanding the pathophysiology of cardiovascular and diabetes risk factors clustering, its use as a clinical syndrome is not justified by current data.

Modified wind chill temperatures determined by a whole body thermoregulation model and human-based facial convective coefficients.

PubMed

Shabat, Yael Ben; Shitzer, Avraham; Fiala, Dusan

2014-08-01

Wind chill equivalent temperatures (WCETs) were estimated by a modified Fiala's whole body thermoregulation model of a clothed person. Facial convective heat exchange coefficients applied in the computations concurrently with environmental radiation effects were taken from a recently derived human-based correlation. Apart from these, the analysis followed the methodology used in the derivation of the currently used wind chill charts. WCET values are summarized by the following equation:[Formula: see text]Results indicate consistently lower estimated facial skin temperatures and consequently higher WCETs than those listed in the literature and used by the North American weather services. Calculated dynamic facial skin temperatures were additionally applied in the estimation of probabilities for the occurrence of risks of frostbite. Predicted weather combinations for probabilities of "Practically no risk of frostbite for most people," for less than 5 % risk at wind speeds above 40 km h(-1), were shown to occur at air temperatures above -10 °C compared to the currently published air temperature of -15 °C. At air temperatures below -35 °C, the presently calculated weather combination of 40 km h(-1)/-35 °C, at which the transition for risks to incur a frostbite in less than 2 min, is less conservative than that published: 60 km h(-1)/-40 °C. The present results introduce a fundamentally improved scientific basis for estimating facial skin temperatures, wind chill temperatures and risk probabilities for frostbites over those currently practiced.

Modified wind chill temperatures determined by a whole body thermoregulation model and human-based facial convective coefficients

NASA Astrophysics Data System (ADS)

Shabat, Yael Ben; Shitzer, Avraham; Fiala, Dusan

2014-08-01

Wind chill equivalent temperatures (WCETs) were estimated by a modified Fiala's whole body thermoregulation model of a clothed person. Facial convective heat exchange coefficients applied in the computations concurrently with environmental radiation effects were taken from a recently derived human-based correlation. Apart from these, the analysis followed the methodology used in the derivation of the currently used wind chill charts. WCET values are summarized by the following equation: Results indicate consistently lower estimated facial skin temperatures and consequently higher WCETs than those listed in the literature and used by the North American weather services. Calculated dynamic facial skin temperatures were additionally applied in the estimation of probabilities for the occurrence of risks of frostbite. Predicted weather combinations for probabilities of "Practically no risk of frostbite for most people," for less than 5 % risk at wind speeds above 40 km h-1, were shown to occur at air temperatures above -10 °C compared to the currently published air temperature of -15 °C. At air temperatures below -35 °C, the presently calculated weather combination of 40 km h-1/-35 °C, at which the transition for risks to incur a frostbite in less than 2 min, is less conservative than that published: 60 km h-1/-40 °C. The present results introduce a fundamentally improved scientific basis for estimating facial skin temperatures, wind chill temperatures and risk probabilities for frostbites over those currently practiced.

Applying risk and resilience models to predicting the effects of media violence on development.

PubMed

Prot, Sara; Gentile, Douglas A

2014-01-01

Although the effects of media violence on children and adolescents have been studied for over 50 years, they remain controversial. Much of this controversy is driven by a misunderstanding of causality that seeks the cause of atrocities such as school shootings. Luckily, several recent developments in risk and resilience theories offer a way out of this controversy. Four risk and resilience models are described, including the cascade model, dose-response gradients, pathway models, and turning-point models. Each is described and applied to the existing media effects literature. Recommendations for future research are discussed with regard to each model. In addition, we examine current developments in theorizing that stressors have sensitizing versus steeling effects and recent interest in biological and gene by environment interactions. We also discuss several of the cultural aspects that have supported the polarization and misunderstanding of the literature, and argue that applying risk and resilience models to the theories and data offers a more balanced way to understand the subtle effects of media violence on aggression within a multicausal perspective.

[Study on building index system of risk assessment of post-marketing Chinese patent medicine based on AHP-fuzzy neural network].

PubMed

Li, Yuanyuan; Xie, Yanming; Fu, Yingkun

2011-10-01

Currently massive researches have been launched about the safety, efficiency and economy of post-marketing Chinese patent medicine (CPM) proprietary Chinese medicine, but it was lack of a comprehensive interpretation. Establishing the risk evaluation index system and risk assessment model of CPM is the key to solve drug safety problems and protect people's health. The clinical risk factors of CPM exist similarities with the Western medicine, can draw lessons from foreign experience, but also have itself multi-factor multivariate multi-level complex features. Drug safety risk assessment for the uncertainty and complexity, using analytic hierarchy process (AHP) to empower the index weights, AHP-based fuzzy neural network to build post-marketing CPM risk evaluation index system and risk assessment model and constantly improving the application of traditional Chinese medicine characteristic is accord with the road and feasible beneficial exploration.

Development of a Risk-Based Comparison Methodology of Carbon Capture Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engel, David W.; Dalton, Angela C.; Dale, Crystal

2014-06-01

Given the varying degrees of maturity among existing carbon capture (CC) technology alternatives, an understanding of the inherent technical and financial risk and uncertainty associated with these competing technologies is requisite to the success of carbon capture as a viable solution to the greenhouse gas emission challenge. The availability of tools and capabilities to conduct rigorous, risk–based technology comparisons is thus highly desirable for directing valuable resources toward the technology option(s) with a high return on investment, superior carbon capture performance, and minimum risk. To address this research need, we introduce a novel risk-based technology comparison method supported by anmore » integrated multi-domain risk model set to estimate risks related to technological maturity, technical performance, and profitability. Through a comparison between solid sorbent and liquid solvent systems, we illustrate the feasibility of estimating risk and quantifying uncertainty in a single domain (modular analytical capability) as well as across multiple risk dimensions (coupled analytical capability) for comparison. This method brings technological maturity and performance to bear on profitability projections, and carries risk and uncertainty modeling across domains via inter-model sharing of parameters, distributions, and input/output. The integration of the models facilitates multidimensional technology comparisons within a common probabilistic risk analysis framework. This approach and model set can equip potential technology adopters with the necessary computational capabilities to make risk-informed decisions about CC technology investment. The method and modeling effort can also be extended to other industries where robust tools and analytical capabilities are currently lacking for evaluating nascent technologies.« less

Direct potable reuse microbial risk assessment methodology: Sensitivity analysis and application to State log credit allocations.

PubMed

Soller, Jeffrey A; Eftim, Sorina E; Nappier, Sharon P

2018-01-01

Understanding pathogen risks is a critically important consideration in the design of water treatment, particularly for potable reuse projects. As an extension to our published microbial risk assessment methodology to estimate infection risks associated with Direct Potable Reuse (DPR) treatment train unit process combinations, herein, we (1) provide an updated compilation of pathogen density data in raw wastewater and dose-response models; (2) conduct a series of sensitivity analyses to consider potential risk implications using updated data; (3) evaluate the risks associated with log credit allocations in the United States; and (4) identify reference pathogen reductions needed to consistently meet currently applied benchmark risk levels. Sensitivity analyses illustrated changes in cumulative annual risks estimates, the significance of which depends on the pathogen group driving the risk for a given treatment train. For example, updates to norovirus (NoV) raw wastewater values and use of a NoV dose-response approach, capturing the full range of uncertainty, increased risks associated with one of the treatment trains evaluated, but not the other. Additionally, compared to traditional log-credit allocation approaches, our results indicate that the risk methodology provides more nuanced information about how consistently public health benchmarks are achieved. Our results indicate that viruses need to be reduced by 14 logs or more to consistently achieve currently applied benchmark levels of protection associated with DPR. The refined methodology, updated model inputs, and log credit allocation comparisons will be useful to regulators considering DPR projects and design engineers as they consider which unit treatment processes should be employed for particular projects. Published by Elsevier Ltd.

USE OF BIOLOGICALLY BASED COMPUTATIONAL MODELING IN MODE OF ACTION-BASED RISK ASSESSMENT – AN EXAMPLE OF CHLOROFORM

EPA Science Inventory

The objective of current work is to develop a new cancer dose-response assessment for chloroform using a physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) model. The PBPK/PD model is based on a mode of action in which the cytolethality of chloroform occurs when the ...

An approach for the anticipatory and participatory management of current and future flood risks

NASA Astrophysics Data System (ADS)

Luther, J.

2012-04-01

Despite the fact that many measures to attenuate flood hazards and reduce vulnerabilities are being implemented, adverse effects of floods are ever-increasing in most parts of the world. On the one hand this holds true for economically and/or demographically growing regions. On the other hand this applies also to areas that face population shrinkage and economic problems. Such flood risks occur in human-environment systems and are subject to dynamics caused by a number of drivers such as climate change, land-use changes, and others. Many drivers evolve slowly over time or show time-lag effects and long return periods. Moreover, certain decisions may determine the control actions of the following decades. At present, current flood risks are mostly determined based on historic developments and the ex post analysis of flood events. Approaches that look at the future dynamics of both hazards and vulnerable elements ex ante in an integrated manner are rare. Instead, future hazard scenarios are often just overlaid with current socio-economic data, which poses a strong inconsistency. Usually the focus lies on rather short-term, specific or local problems. But many developments and measures show their effects only after long time periods and when considering the whole catchment area. This calls for a holistic and long-term view into the future and implies the challenge of dealing with many uncertainties due to the system's complexity. In order to anticipate and react to these developments, this contribution suggests developing a flexible, yet holistic approach to design, analyse and evaluate alternative futures of such human-environment systems. These futures follow a scenario understanding that considers both specific (current) factor constellations as well as consistent assumptions on autonomous developments (so-called development frameworks) and potentials for control (strategic alternatives) of the interacting entities that influence flood risk. Different scenario concepts and the application of respective techniques are thus reviewed and incorporated with regard to their suitability for an integrated management of current and future flood risks. In particular, "hybrid scenarios" with qualitative and quantitative components represented by nested models as well as assumptions across different spatiotemporal scales, respectively, are suggested for dealing with the uncertainties when assessing flood risks throughout a system's possible evolution. The (initially top-down developed) approach and its components will be briefly presented. These "scenario products" could later serve as a stimulus for discussions that bring together different actors and enhance - and eventually legitimise - the scenarios further in a "scenario process": (1) A first step is the conceptualisation of a flood risk system following the SPRC-model. Its physical geographical and anthropogenic factors may either be subject to autonomous trends, target-oriented control, or facultative system behaviour (e.g. dike breaches). With this concept, the integration of different processes and scales is aspired. (2) Secondly, it is conceptually shown how the risk cascade for present and future states of the flood risk system can be calculated based on coupled models ranging from climate change projections to a damage simulation models. (3) Thirdly, ways to develop socioeconomic storylines for the development frameworks and guiding principles for the strategic alternatives are presented and the futures are combined. This involves making plausible and consistent assumptions for many system factors and their drivers and finding ways to harmonise existing data for the same areas and time steps. (4) Fourthly, selected futures can be analysed and evaluated ex ante applying the coupled models of the second step to derive the emerging flood risks. The evaluation addresses, amongst other aspects, the identification of (i) the sensitivity of all scenarios against the current strategic alternative; (ii) the resulting risks when applying different strategic alternatives against one selected scenario; (iii) the efficiency (as cost-effectiveness) and robustness of one selected strategic alternative against the different scenarios; and (iv) the model uncertainty, for example caused by different climate downscaling methods. It is of growing importance to place any scenario/simulation results in a societal or even individual context and confront them with the perspectives of the people potentially affected. Only this yields a holistic picture and may lead to sustainable, comprehensible decisions. The approach is partly exemplified with research conducted in Saxony (Germany) and the Elbe River catchment in Central Europe and concentrates on river or plain floods, neglecting water quality issues.

Current but not past smoking increases the risk of cardiac events: insights from coronary computed tomographic angiography

PubMed Central

Nakanishi, Rine; Berman, Daniel S.; Budoff, Matthew J.; Gransar, Heidi; Achenbach, Stephan; Al-Mallah, Mouaz; Andreini, Daniele; Cademartiri, Filippo; Callister, Tracy Q.; Chang, Hyuk-Jae; Cheng, Victor Y.; Chinnaiyan, Kavitha; Chow, Benjamin J.W.; Cury, Ricardo; Delago, Augustin; Hadamitzky, Martin; Hausleiter, Jörg; Feuchtner, Gudrun; Kim, Yong-Jin; Kaufmann, Philipp A.; Leipsic, Jonathon; Lin, Fay Y.; Maffei, Erica; Pontone, Gianluca; Raff, Gilbert; Shaw, Leslee J.; Villines, Todd C.; Dunning, Allison; Min, James K.

2015-01-01

Aims We evaluated coronary artery disease (CAD) extent, severity, and major adverse cardiac events (MACEs) in never, past, and current smokers undergoing coronary CT angiography (CCTA). Methods and results We evaluated 9456 patients (57.1 ± 12.3 years, 55.5% male) without known CAD (1588 current smokers; 2183 past smokers who quit ≥3 months before CCTA; and 5685 never smokers). By risk-adjusted Cox proportional-hazards models, we related smoking status to MACE (all-cause death or non-fatal myocardial infarction). We further performed 1:1:1 propensity matching for 1000 in each group evaluate event risk among individuals with similar age, gender, CAD risk factors, and symptom presentation. During a mean follow-up of 2.8 ± 1.9 years, 297 MACE occurred. Compared with never smokers, current and past smokers had greater atherosclerotic burden including extent of plaque defined as segments with any plaque (2.1 ± 2.8 vs. 2.6 ± 3.2 vs. 3.1 ± 3.3, P < 0.0001) and prevalence of obstructive CAD [1-vessel disease (VD): 10.6% vs. 14.9% vs. 15.2%, P < 0.001; 2-VD: 4.4% vs. 6.1% vs. 6.2%, P = 0.001; 3-VD: 3.1% vs. 5.2% vs. 4.3%, P < 0.001]. Compared with never smokers, current smokers experienced higher MACE risk [hazard ratio (HR) 1.9, 95% confidence interval (CI) 1.4–2.6, P < 0.001], while past smokers did not (HR 1.2, 95% CI 0.8–1.6, P = 0.35). Among matched individuals, current smokers had higher MACE risk (HR 2.6, 95% CI 1.6–4.2, P < 0.001), while past smokers did not (HR 1.3, 95% CI 0.7–2.4, P = 0.39). Similar findings were observed for risk of all-cause death. Conclusion Among patients without known CAD undergoing CCTA, current and past smokers had increased burden of atherosclerosis compared with never smokers; however, risk of MACE was heightened only in current smokers. PMID:25666322

Applications of the International Space Station Probabilistic Risk Assessment Model

NASA Technical Reports Server (NTRS)

Grant, Warren; Lutomski, Michael G.

2011-01-01

Recently the International Space Station (ISS) has incorporated more Probabilistic Risk Assessments (PRAs) in the decision making process for significant issues. Future PRAs will have major impact to ISS and future spacecraft development and operations. These PRAs will have their foundation in the current complete ISS PRA model and the current PRA trade studies that are being analyzed as requested by ISS Program stakeholders. ISS PRAs have recently helped in the decision making process for determining reliability requirements for future NASA spacecraft and commercial spacecraft, making crew rescue decisions, as well as making operational requirements for ISS orbital orientation, planning Extravehicular activities (EVAs) and robotic operations. This paper will describe some applications of the ISS PRA model and how they impacted the final decision. This paper will discuss future analysis topics such as life extension, requirements of new commercial vehicles visiting ISS.

The Food Marketing Defense Model: Integrating Psychological Research to Protect Youth and Inform Public Policy.

PubMed

Harris, Jennifer L; Brownell, Kelly D; Bargh, John A

2009-12-01

Marketing practices that promote calorie-dense, nutrient-poor foods directly to children and adolescents present significant public health risk. Worldwide, calls for government action and industry change to protect young people from the negative effects of food marketing have increased. Current proposals focus on restricting television advertising to children under 12 years old, but current psychological models suggest that much more is required. All forms of marketing pose considerable risk; adolescents are also highly vulnerable; and food marketing may produce far-reaching negative health outcomes. We propose a food marketing defense model that posits four necessary conditions to effectively counter harmful food marketing practices: awareness, understanding, ability and motivation to resist. A new generation of psychological research is needed to examine each of these processes, including the psychological mechanisms through which food marketing affects young people, to identify public policy that will effectively protect them from harmful influence.

The Food Marketing Defense Model: Integrating Psychological Research to Protect Youth and Inform Public Policy

PubMed Central

Harris, Jennifer L.; Brownell, Kelly D.; Bargh, John A.

2009-01-01

Marketing practices that promote calorie-dense, nutrient-poor foods directly to children and adolescents present significant public health risk. Worldwide, calls for government action and industry change to protect young people from the negative effects of food marketing have increased. Current proposals focus on restricting television advertising to children under 12 years old, but current psychological models suggest that much more is required. All forms of marketing pose considerable risk; adolescents are also highly vulnerable; and food marketing may produce far-reaching negative health outcomes. We propose a food marketing defense model that posits four necessary conditions to effectively counter harmful food marketing practices: awareness, understanding, ability and motivation to resist. A new generation of psychological research is needed to examine each of these processes, including the psychological mechanisms through which food marketing affects young people, to identify public policy that will effectively protect them from harmful influence. PMID:20182647

A model for translating ethnography and theory into culturally constructed clinical practices.

PubMed

Nastasi, Bonnie Kaul; Schensul, Jean J; Schensul, Stephen L; Mekki-Berrada, Abelwahed; Pelto, Pertti J; Maitra, Shubhada; Verma, Ravi; Saggurti, Niranjan

2015-03-01

This article describes the development of a dynamic culturally constructed clinical practice model for HIV/STI prevention, the Narrative Intervention Model (NIM), and illustrates its application in practice, within the context of a 6-year transdisciplinary research program in Mumbai, India. Theory and research from anthropology, psychology, and public health, and mixed-method ethnographic research with practitioners, patients, and community members, contributed to the articulation of the NIM for HIV/STI risk reduction and prevention among married men living in low-income communities. The NIM involves a process of negotiation of patient narratives regarding their sexual health problems and related risk factors to facilitate risk reduction. The goal of the NIM is to facilitate cognitive-behavioral change through a three-stage process of co-construction (eliciting patient narrative), deconstruction (articulating discrepancies between current and desired narrative), and reconstruction (proposing alternative narratives that facilitate risk reduction). The NIM process extends the traditional clinical approach through the integration of biological, psychological, interpersonal, and cultural factors as depicted in the patient narrative. Our work demonstrates the use of a recursive integration of research and practice to address limitations of current evidence-based intervention approaches that fail to address the diversity of cultural constructions across populations and contexts.

A Model for Translating Ethnography and Theory into Culturally Constructed Clinical Practices

PubMed Central

Schensul, Jean J.; Schensul, Stephen L.; Mekki-Berrada, Abelwahed; Pelto, Pertti J.; Maitra, Shubhada; Verma, Ravi; Saggurti, Niranjan

2015-01-01

This article describes the development of a dynamic culturally constructed clinical practice model for HIV/STI prevention, the Narrative Intervention Model (NIM), and illustrates its application in practice, within the context of a 6-year transdisciplinary research program in Mumbai, India. Theory and research from anthropology, psychology, and public health, and mixed-method ethnographic research with practitioners, patients, and community members, contributed to the articulation of the NIM for HIV/STI risk reduction and prevention among married men living in low-income communities. The NIM involves a process of negotiation of patient narratives regarding their sexual health problems and related risk factors to facilitate risk reduction. The goal of the NIM is to facilitate cognitive-behavioral change through a three-stage process of co-construction (eliciting patient narrative), deconstruction (articulating discrepancies between current and desired narrative), and reconstruction (proposing alternative narratives that facilitate risk reduction). The NIM process extends the traditional clinical approach through the integration of biological, psychological, interpersonal, and cultural factors as depicted in the patient narrative. Our work demonstrates the use of a recursive integration of research and practice to address limitations of current evidence-based intervention approaches that fail to address the diversity of cultural constructions across populations and contexts. PMID:25292448

A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening

PubMed Central

Katki, Hormuzd A.; Cheung, Li C.; Fetterman, Barbara; Castle, Philip E.; Sundaram, Rajeshwari

2014-01-01

Summary New cervical cancer screening guidelines in the US and many European countries recommend that women get tested for human papillomavirus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer/cancer risk per year of continued HPV infection. However, both time to onset of precancer/cancer and time to HPV clearance are interval-censored, and onset of precancer/cancer strongly informatively censors HPV clearance. We analyze this bivariate informatively interval-censored data by developing a novel joint model for time to clearance of HPV and time to precancer/cancer using shared random-effects, where the estimated mean duration of each woman’s HPV infection is a covariate in the submodel for time to precancer/cancer. The model was fit to data on 9,553 HPV-positive/Pap-negative women undergoing cervical cancer screening at Kaiser Permanente Northern California, data that were pivotal to the development of US screening guidelines. We compare the implications for screening intervals of this joint model to those from population-average marginal models of precancer/cancer risk. In particular, after 2 years the marginal population-average precancer/cancer risk was 5%, suggesting a 2-year interval to control population-average risk at 5%. In contrast, the joint model reveals that almost all women exceeding 5% individual risk in 2 years also exceeded 5% in 1 year, suggesting that a 1-year interval is better to control individual risk at 5%. The example suggests that sophisticated risk models capable of predicting individual risk may have different implications than population-average risk models that are currently used for informing medical guideline development. PMID:26556961

A joint model of persistent human papillomavirus infection and cervical cancer risk: Implications for cervical cancer screening.

PubMed

Katki, Hormuzd A; Cheung, Li C; Fetterman, Barbara; Castle, Philip E; Sundaram, Rajeshwari

2015-10-01

New cervical cancer screening guidelines in the US and many European countries recommend that women get tested for human papillomavirus (HPV). To inform decisions about screening intervals, we calculate the increase in precancer/cancer risk per year of continued HPV infection. However, both time to onset of precancer/cancer and time to HPV clearance are interval-censored, and onset of precancer/cancer strongly informatively censors HPV clearance. We analyze this bivariate informatively interval-censored data by developing a novel joint model for time to clearance of HPV and time to precancer/cancer using shared random-effects, where the estimated mean duration of each woman's HPV infection is a covariate in the submodel for time to precancer/cancer. The model was fit to data on 9,553 HPV-positive/Pap-negative women undergoing cervical cancer screening at Kaiser Permanente Northern California, data that were pivotal to the development of US screening guidelines. We compare the implications for screening intervals of this joint model to those from population-average marginal models of precancer/cancer risk. In particular, after 2 years the marginal population-average precancer/cancer risk was 5%, suggesting a 2-year interval to control population-average risk at 5%. In contrast, the joint model reveals that almost all women exceeding 5% individual risk in 2 years also exceeded 5% in 1 year, suggesting that a 1-year interval is better to control individual risk at 5%. The example suggests that sophisticated risk models capable of predicting individual risk may have different implications than population-average risk models that are currently used for informing medical guideline development.

Radiation and cancer risk: a continuing challenge for epidemiologists

PubMed Central

2011-01-01

This paper provides a perspective on epidemiological research on radiation and cancer, a field that has evolved over its six decade history. The review covers the current framework for assessing radiation risk and persistent questions about the details of these risks: is there a threshold and more generally, what is the shape of the dose-response relationship? How do risks vary over time and with age? What factors modify the risk of radiation? The example of radon progeny and lung cancer is considered as a case study, illustrating the modeling of epidemiological data to derive quantitative models and the coherence of the epidemiological and biological evidence. Finally, the manuscript considers the need for ongoing research, even in the face of research over a 60-year span. PMID:21489214

Tumor necrosis factor-α inhibitor treatment and the risk of incident cardiovascular events in patients with early rheumatoid arthritis: a nested case-control study.

PubMed

Desai, Rishi J; Rao, Jaya K; Hansen, Richard A; Fang, Gang; Maciejewski, Matthew; Farley, Joel

2014-11-01

To compare the risk of cardiovascular (CV) events between use of tumor necrosis factor-α inhibitors (TNFi) and nonbiologic disease-modifying antirheumatic drugs (DMARD) in patients with early rheumatoid arthritis (RA). A nested case-control study was conducted using data from Truven's MarketScan commercial and Medicare claims database for patients with early RA who started treatment with either a TNFi or a nonbiologic DMARD between January 1, 2008, and December 31, 2010. Date of CV event diagnosis for cases was defined as the event date, and 12 age-matched and sex-matched controls were sampled using incidence density sampling. Drug exposure was defined into the following mutually exclusive categories hierarchically: (1) current use of TNFi (with or without nonbiologics), (2) past use of TNFi (with or without nonbiologics), (3) current use of nonbiologics only, and (4) past use of nonbiologics only. Current use was defined as any use in the period 90 days prior to the event date. Conditional logistic regression models were used to derive incidence rate ratios (IRR). From the cohort of patients with early RA, 279 cases of incident CV events and 3348 matched controls were identified. The adjusted risk of CV events was not significantly different between current TNFi users and current nonbiologic users (IRR 0.92, 95% CI 0.59-1.44). However, past users of nonbiologics showed significantly higher risk compared to current nonbiologic users (IRR 1.47, 95% CI 1.04-2.08). No differences in the CV risk were found between current TNFi and current nonbiologic DMARD treatment in patients with early RA.

Risk factors of autistic symptoms in children with ADHD.

PubMed

Kröger, Anne; Hänig, Susann; Seitz, Christiane; Palmason, Haukur; Meyer, Jobst; Freitag, Christine M

2011-12-01

Autistic symptoms are frequently observed in children with attention-deficit/hyperactivity disorder (ADHD), but their etiology remains unclear. The main aim of this study was to describe risk factors for increased autistic symptoms in children with ADHD without an autism or autism-spectrum diagnosis. Comorbid psychiatric disorders, developmental delay, current medication, prenatal biological and postnatal psychosocial risk factors as well as parental autistic traits were assessed in 205 children with ADHD. Linear regression models identified maternal autistic traits, current familial risk factors and hyperactive symptoms as predictors of autistic symptoms in children with ADHD. Findings are indicative of possible genetic as well as environmental risk factors mediating autistic symptoms in children with ADHD. An additional validity analysis by ROC, area under the curve (AUC), suggested a cut-off of 11 to differentiate between ADHD and high-functioning ASD by the Social Communication Questionnaire (SCQ).

Prediction of cardiovascular disease risk among low-income urban dwellers in metropolitan Kuala Lumpur, Malaysia.

PubMed

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Bulgiba, Awang; Majid, Hazreen Abdul

2015-01-01

We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers.

Prediction of Cardiovascular Disease Risk among Low-Income Urban Dwellers in Metropolitan Kuala Lumpur, Malaysia

PubMed Central

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Majid, Hazreen Abdul

2015-01-01

We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers. PMID:25821810

A quantitative risk assessment model to evaluate effective border control measures for rabies prevention

PubMed Central

Weng, Hsin-Yi; Wu, Pei-I; Yang, Ping-Cheng; Tsai, Yi-Lun; Chang, Chao-Chin

2009-01-01

Border control is the primary method to prevent rabies emergence. This study developed a quantitative risk model incorporating stochastic processes to evaluate whether border control measures could efficiently prevent rabies introduction through importation of cats and dogs using Taiwan as an example. Both legal importation and illegal smuggling were investigated. The impacts of reduced quarantine and/or waiting period on the risk of rabies introduction were also evaluated. The results showed that Taiwan’s current animal importation policy could effectively prevent rabies introduction through legal importation of cats and dogs. The median risk of a rabid animal to penetrate current border control measures and enter Taiwan was 5.33 × 10−8 (95th percentile: 3.20 × 10−7). However, illegal smuggling may pose Taiwan to the great risk of rabies emergence. Reduction of quarantine and/or waiting period would affect the risk differently, depending on the applied assumptions, such as increased vaccination coverage, enforced custom checking, and/or change in number of legal importations. Although the changes in the estimated risk under the assumed alternatives were not substantial except for completely abolishing quarantine, the consequences of rabies introduction may yet be considered to be significant in a rabies-free area. Therefore, a comprehensive benefit-cost analysis needs to be conducted before recommending these alternative measures. PMID:19822125

Smoking and Risk of Ischemic Stroke in Young Men.

PubMed

Markidan, Janina; Cole, John W; Cronin, Carolyn A; Merino, Jose G; Phipps, Michael S; Wozniak, Marcella A; Kittner, Steven J

2018-05-01

There is a strong dose-response relationship between smoking and risk of ischemic stroke in young women, but there are few data examining this association in young men. We examined the dose-response relationship between the quantity of cigarettes smoked and the odds of developing an ischemic stroke in men under age 50 years. The Stroke Prevention in Young Men Study is a population-based case-control study of risk factors for ischemic stroke in men ages 15 to 49 years. The χ 2 test was used to test categorical comparisons. Logistic regression models were used to calculate the odds ratio for ischemic stroke occurrence comparing current and former smokers to never smokers. In the first model, we adjusted solely for age. In the second model, we adjusted for potential confounding factors, including age, race, education, hypertension, myocardial infarction, angina, diabetes mellitus, and body mass index. The study population consisted of 615 cases and 530 controls. The odds ratio for the current smoking group compared with never smokers was 1.88. Furthermore, when the current smoking group was stratified by number of cigarettes smoked, there was a dose-response relationship for the odds ratio, ranging from 1.46 for those smoking <11 cigarettes per day to 5.66 for those smoking 40+ cigarettes per day. We found a strong dose-response relationship between the number of cigarettes smoked daily and ischemic stroke among young men. Although complete smoking cessation is the goal, even smoking fewer cigarettes may reduce the risk of ischemic stroke in young men. © 2018 American Heart Association, Inc.

Dactinomycin and Vincristine Toxicity in the Treatment of Childhood Cancer: A Retrospective Study from the Children’s Oncology Group

PubMed Central

Langholz, Bryan; Skolnik, Jeffrey M.; Barrett, Jeffrey S.; Renbarger, Jamie; Seibel, Nita L.; Zajicek, Anne; Arndt, Carola A.S.

2011-01-01

Background Dactinomycin (AMD) and vincristine (VCR) have been used for the treatment of childhood cancer over the past 40 years but evidence-based dosing guidance is lacking. Methods Patient AMD and VCR dose and drug-related adverse event (AE) information from four rhabdomyosarcoma (RMS) and two Wilms tumor (WT) studies were assembled. Statistical modeling was used to account for differences in AE data collection across studies, develop rate models for grade 3/4 CTCAE v3 hepatic- (AMD) and neuro- (AMD) toxicity, assess variation in toxicity rates over age and other factors, and predict toxicity risk under current dosing guidelines. Results For the same dose/body size, AMD toxicity rates were higher in patients <1 year than older patients and VCR toxicity rates increased with age. The statistical model provided estimates for AMD and VCR toxicity risk under current dosing schedules and indicated that patients of smaller body size were at lower risk of VCR toxicity than larger patients of the same age. The rate of AMD toxicity was highest early in treatment and was lower in patients who tolerated initial AMD without toxicity. Conclusion The observed decrease in AMD toxicity rate with cumulative dose may indicate sensitivity in a subgroup of patients while the observed increase in VCR toxicity risk with age may indicate changing sensitivity to VCR. Current dosing practices result in a fairly uniform toxicity profile within age group. However, PK/PD studies should be done to provide further provide further information on best dosing guidelines. PMID:21671362

Mouse Models for Unraveling the Importance of Diet in Colon Cancer Prevention

PubMed Central

Tammariello, Alexandra E.; Milner, John A.

2010-01-01

Diet and genetics are both considered important risk determinants for colorectal cancer, a leading cause of death worldwide. Several genetically engineered mouse models have been created, including the ApcMin mouse, to aid in the identification of key cancer related processes and to assist with the characterization of environmental factors, including the diet, which influence risk. Current research using these models provides evidence that several bioactive food components can inhibit genetically predisposed colorectal cancer, while others increase risk. Specifically, calorie restriction or increased exposure to n-3 fatty acids, sulforaphane, chafuroside, curcumin, and dibenzoylmethane were reported protective. Total fat, calories and all-trans retinoic acid are associated with an increased risk. Unraveling the importance of specific dietary components in these models is complicated by the basal diet used, the quantity of test components provided, and interactions among food components. Newer models are increasingly available to evaluate fundamental cellular processes, including DNA mismatch repair, immune function and inflammation as markers for colon cancer risk. Unfortunately, these models have been used infrequently to examine the influence of specific dietary components. The enhanced use of these models can shed mechanistic insights about the involvement of specific bioactive food and components and energy as determinants of colon cancer risk. However, the use of available mouse models to exactly represent processes important to human gastrointestinal cancers will remain a continued scientific challenge. PMID:20122631

The association between smoking and blood pressure in men: a cross-sectional study.

PubMed

Li, Guoju; Wang, Hailing; Wang, Ke; Wang, Wenrui; Dong, Fen; Qian, Yonggang; Gong, Haiying; Hui, Chunxia; Xu, Guodong; Li, Yanlong; Pan, Li; Zhang, Biao; Shan, Guangliang

2017-10-10

Cigarette smoking is a known risk factor for cardiovascular disease (CVD), but the association between smoking and blood pressure is unclear. Thus, the current study examined the association between cigarette smoking and blood pressure in men. Systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP) were examined using digital blood pressure measuring device, and smoking status was determined with China National Health Survey. The ANCOVA showed that the adjusted DBP and MAP were lower in current smokers versus nonsmokers and the adjusted SBP was lower in current smokers versus former smokers (P < 0.05). Additionally, the adjusted PP tend to be decreased steadily as the pack·years increased in current smokers. In a fully adjusted logistic regression model, former smokers had increased ORs (95% CI) of 1.48 (1.01, 2.18) of hypertension and current smokers had not increased ORs (95% CI) of 0.83 (0.61, 1.12), compared with never smokers. The findings revealed that the adjusted blood pressure were lower in current smokers versus nonsmokers and former smokers. No significant dose-dependent effect of current smoking on blood pressure indices except PP was observed. Smoking cessation was significantly associated with an increased risk of hypertension. However, current smoking was not a risk factor of hypertension.

Crystalline silica exposure and lung cancer mortality in diatomaceous earth industry workers: a quantitative risk assessment

PubMed Central

Rice, F; Park, R; Stayner, L; Smith, R; Gilbert, S; Checkoway, H

2001-01-01

OBJECTIVE—To use various exposure-response models to estimate the risk of mortality from lung cancer due to occupational exposure to respirable crystalline silica dust.
METHODS—Data from a cohort mortality study of 2342 white male California diatomaceous earth mining and processing workers exposed to crystalline silica dust (mainly cristobalite) were reanalyzed with Poisson regression and Cox's proportional hazards models. Internal and external adjustments were used to control for potential confounding from the effects of time since first observation, calendar time, age, and Hispanic ethnicity. Cubic smoothing spline models were used to assess the fit of the models. Exposures were lagged by 10 years. Evaluations of the fit of the models were performed by comparing their deviances. Lifetime risks of lung cancer were estimated up to age 85 with an actuarial approach that accounted for competing causes of death.
RESULTS—Exposure to respirable crystalline silica dust was a significant predictor (p<0.05) in nearly all of the models evaluated and the linear relative rate model with a 10 year exposure lag seemed to give the best fit in the Poisson regression analysis. For those who died of lung cancer the linear relative rate model predicted rate ratios for mortality from lung cancer of about 1.6 for the mean cumulative exposure to respirable silica compared with no exposure. The excess lifetime risk (to age 85) of mortality from lung cancer for white men exposed for 45 years and with a 10 year lag period at the current Occupational Safety and Health Administration (OSHA) standard of about 0.05 mg/m3 for respirable cristobalite dust is 19/1000 (95% confidence interval (95% CI) 5/1000 to 46/1000).
CONCLUSIONS—There was a significant risk of mortality from lung cancer that increased with cumulative exposure to respirable crystalline silica dust. The predicted number of deaths from lung cancer suggests that current occupational health standards may not be adequately protecting workers from the risk of lung cancer.


Keywords: crystalline silica; cristobalite; lung cancer PMID:11119633

Preclinical Torsades-de-Pointes screens: advantages and limitations of surrogate and direct approaches in evaluating proarrhythmic risk.

PubMed

Gintant, Gary A

2008-08-01

The successful development of novel drugs requires the ability to detect (and avoid) compounds that may provoke Torsades-de-Pointes (TdeP) arrhythmia while endorsing those compounds with minimal torsadogenic risk. As TdeP is a rare arrhythmia not readily observed during clinical or post-marketing studies, numerous preclinical models are employed to assess delayed or altered ventricular repolarization (surrogate markers linked to enhanced proarrhythmic risk). This review evaluates the advantages and limitations of selected preclinical models (ranging from the simplest cellular hERG current assay to the more complex in vitro perfused ventricular wedge and Langendorff heart preparations and in vivo chronic atrio-ventricular (AV)-node block model). Specific attention is paid to the utility of concentration-response relationships and "risk signatures" derived from these studies, with the intention of moving beyond predicting clinical QT prolongation and towards prediction of TdeP risk. While the more complex proarrhythmia models may be suited to addressing questionable or conflicting proarrhythmic signals obtained with simpler preclinical assays, further benchmarking of proarrhythmia models is required for their use in the robust evaluation of safety margins. In the future, these models may be able to reduce unwarranted attrition of evolving compounds while becoming pivotal in the balanced integrated risk assessment of advancing compounds.

Revised simulation model does not predict rebound in gonorrhoea prevalence where core groups are treated in the presence of antimicrobial resistance.

PubMed

Trecker, Molly A; Hogan, Daniel J; Waldner, Cheryl L; Dillon, Jo-Anne R; Osgood, Nathaniel D

2015-06-01

To determine the effects of using discrete versus continuous quantities of people in a compartmental model examining the contribution of antimicrobial resistance (AMR) to rebound in the prevalence of gonorrhoea. A previously published transmission model was reconfigured to represent the occurrence of gonorrhoea in discrete persons, rather than allowing fractions of infected individuals during simulations. In the revised model, prevalence only rebounded under scenarios reproduced from the original paper when AMR occurrence was increased by 10(5) times. In such situations, treatment of high-risk individuals yielded outcomes very similar to those resulting from treatment of low-risk and intermediate-risk individuals. Otherwise, in contrast with the original model, prevalence was the lowest when the high-risk group was treated, supporting the current policy of targeting treatment to high-risk groups. Simulation models can be highly sensitive to structural features. Small differences in structure and parameters can substantially influence predicted outcomes and policy prescriptions, and must be carefully considered. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Modeling insurer-homeowner interactions in managing natural disaster risk.

PubMed

Kesete, Yohannes; Peng, Jiazhen; Gao, Yang; Shan, Xiaojun; Davidson, Rachel A; Nozick, Linda K; Kruse, Jamie

2014-06-01

The current system for managing natural disaster risk in the United States is problematic for both homeowners and insurers. Homeowners are often uninsured or underinsured against natural disaster losses, and typically do not invest in retrofits that can reduce losses. Insurers often do not want to insure against these losses, which are some of their biggest exposures and can cause an undesirably high chance of insolvency. There is a need to design an improved system that acknowledges the different perspectives of the stakeholders. In this article, we introduce a new modeling framework to help understand and manage the insurer's role in catastrophe risk management. The framework includes a new game-theoretic optimization model of insurer decisions that interacts with a utility-based homeowner decision model and is integrated with a regional catastrophe loss estimation model. Reinsurer and government roles are represented as bounds on the insurer-insured interactions. We demonstrate the model for a full-scale case study for hurricane risk to residential buildings in eastern North Carolina; present the results from the perspectives of all stakeholders-primary insurers, homeowners (insured and uninsured), and reinsurers; and examine the effect of key parameters on the results. © 2014 Society for Risk Analysis.

Consumer product in vitro digestion model: Bioaccessibility of contaminants and its application in risk assessment.

PubMed

Brandon, Esther F A; Oomen, Agnes G; Rompelberg, Cathy J M; Versantvoort, Carolien H M; van Engelen, Jacqueline G M; Sips, Adrienne J A M

2006-03-01

This paper describes the applicability of in vitro digestion models as a tool for consumer products in (ad hoc) risk assessment. In current risk assessment, oral bioavailability from a specific product is considered to be equal to bioavailability found in toxicity studies in which contaminants are usually ingested via liquids or food matrices. To become bioavailable, contaminants must first be released from the product during the digestion process (i.e. become bioaccessible). Contaminants in consumer products may be less bioaccessible than contaminants in liquid or food. Therefore, the actual risk after oral exposure could be overestimated. This paper describes the applicability of a simple, reliable, fast and relatively inexpensive in vitro method for determining the bioaccessibility of a contaminant from a consumer product. Different models, representing sucking and/or swallowing were developed. The experimental design of each model can be adjusted to the appropriate exposure scenarios as determined by the risk assessor. Several contaminated consumer products were tested in the various models. Although relevant in vivo data are scare, we succeeded to preliminary validate the model for one case. This case showed good correlation and never underestimated the bioavailability. However, validation check needs to be continued.

Estimating wildfire risk on a Mojave Desert landscape using remote sensing and field sampling

USGS Publications Warehouse

Van Linn, Peter F.; Nussear, Kenneth E.; Esque, Todd C.; DeFalco, Lesley A.; Inman, Richard D.; Abella, Scott R.

2013-01-01

Predicting wildfires that affect broad landscapes is important for allocating suppression resources and guiding land management. Wildfire prediction in the south-western United States is of specific concern because of the increasing prevalence and severe effects of fire on desert shrublands and the current lack of accurate fire prediction tools. We developed a fire risk model to predict fire occurrence in a north-eastern Mojave Desert landscape. First we developed a spatial model using remote sensing data to predict fuel loads based on field estimates of fuels. We then modelled fire risk (interactions of fuel characteristics and environmental conditions conducive to wildfire) using satellite imagery, our model of fuel loads, and spatial data on ignition potential (lightning strikes and distance to roads), topography (elevation and aspect) and climate (maximum and minimum temperatures). The risk model was developed during a fire year at our study landscape and validated at a nearby landscape; model performance was accurate and similar at both sites. This study demonstrates that remote sensing techniques used in combination with field surveys can accurately predict wildfire risk in the Mojave Desert and may be applicable to other arid and semiarid lands where wildfires are prevalent.

Modeling Fecundity in Birds: Conceptual Overview, Current Models, and Considerations for Future Developments

EPA Science Inventory

Understanding fecundity is fundamental to understanding fitness, population dynamics, conservation, ecological risk, and management issues of birds. For all the efforts placed in measuring fecundity or its surrogates over the past century of avian research, it is still poorly me...

Relationship between long working hours and depression: a 3-year longitudinal study of clerical workers.

PubMed

Amagasa, Takashi; Nakayama, Takeo

2013-08-01

To clarify how long working hours affect the likelihood of current and future depression. Using data from four repeated measurements collected from 218 clerical workers, four models associating work-related factors to the depressive mood scale were established. The final model was constructed after comparing and testing the goodness-of-fit index using structural equation modeling. Multiple logistic regression analysis was also performed. The final model showed the best fit (normed fit index = 0.908; goodness-of-fit index = 0.936; root-mean-square error of approximation = 0.018). Its standardized total effect indicated that long working hours affected depression at the time of evaluation and 1 to 3 years later. The odds ratio for depression risk was 14.7 in employees who were not long-hours overworked according to the initial survey but who were long-hours overworked according to the second survey. Long working hours increase current and future risks of depression.

The association of statin therapy with the risk of recurrent venous thrombosis.

PubMed

Smith, N L; Harrington, L B; Blondon, M; Wiggins, K L; Floyd, J S; Sitlani, C M; McKnight, B; Larson, E B; Rosendaal, F R; Heckbert, S R; Psaty, B M

2016-07-01

Essentials A lowered risk of recurrent venous thrombosis (VT) with statin treatment is controversial. Among observational inception cohort of 2,798 adults with incident VT, 457 had recurrent VT. Time-to-event models with time-varying statin use and adjustment for potential confounders was used for analysis. Compared to nonuse, current statin use was associated with 26% lower risk of recurrent VT. Click to hear Prof. Büller's perspective on Anticoagulant Therapy in the Treatment of Venous Thromboembolism Background Meta-analyses of randomized controlled trials suggest that treatment with hydroxymethylglutaryl-coenzyme A reductase inhibitors (statins) lowers the risk of incident venous thrombosis (VT), particularly among those without prevalent clinical cardiovascular disease (CVD). Whether this is true for the prevention of recurrent VT is debated. We used an observational inception cohort to estimate the association of current statin use with the risk of recurrent VT. Methods and Results The study setting was a large healthcare organization with detailed medical record and pharmacy information at cohort entry and throughout follow-up. We followed 2798 subjects 18-89 years of age who experienced a validated incident VT between January 1, 2002, and December 31, 2010, for a first recurrent VT, validated by medical record review. During follow-up, 457 (16%) developed a first recurrent VT. In time-to-event models incorporating time-varying statin use and adjusting for potential confounders, current statin use was associated with a 26% lower risk of recurrent VT: hazard ratio 0.74, 95% confidence interval 0.59-0.94. Among cohort members free of CVD (n = 2134), current statin use was also associated with a lower risk (38%) of recurrent VT: hazard ratio 0.62, 95% confidence interval 0.45-0.85. We found similar results when restricting to new users of statins and in subgroups of different statin types and doses. Conclusions In a population-based cohort of subjects who had experienced an incident VT, statin use, compared with nonuse, was associated with a clinically relevant lower risk of recurrent VT. These findings suggest a potential secondary benefit of statins among patients who have experienced an incident VT. © 2016 International Society on Thrombosis and Haemostasis.

Catchment scale afforestation for mitigating flooding

NASA Astrophysics Data System (ADS)

Barnes, Mhari; Quinn, Paul; Bathurst, James; Birkinshaw, Stephen

2016-04-01

After the 2013-14 floods in the UK there were calls to 'forest the uplands' as a solution to reducing flood risk across the nation. At present, 1 in 6 homes in Britain are at risk of flooding and current EU legislation demands a sustainable, 'nature-based solution'. However, the role of forests as a natural flood management technique remains highly controversial, due to a distinct lack of robust evidence into its effectiveness in reducing flood risk during extreme events. SHETRAN, physically-based spatially-distributed hydrological models of the Irthing catchment and Wark forest sub-catchments (northern England) have been developed in order to test the hypothesis of the effect trees have on flood magnitude. The advanced physically-based models have been designed to model scale-related responses from 1, through 10, to 100km2, a first study of the extent to which afforestation and woody debris runoff attenuation features (RAFs) may help to mitigate floods at the full catchment scale (100-1000 km2) and on a national basis. Furthermore, there is a need to analyse the extent to which land management practices, and the installation of nature-based RAFs, such as woody debris dams, in headwater catchments can attenuate flood-wave movement, and potentially reduce downstream flood risk. The impacts of riparian planting and the benefits of adding large woody debris of several designs and on differing sizes of channels has also been simulated using advanced hydrodynamic (HiPIMS) and hydrological modelling (SHETRAN). With the aim of determining the effect forestry may have on flood frequency, 1000 years of generated rainfall data representative of current conditions has been used to determine the difference between current land-cover, different distributions of forest cover and the defining scenarios - complete forest removal and complete afforestation of the catchment. The simulations show the percentage of forestry required to have a significant impact on mitigating downstream flood risk at sub-catchment and catchment scale. Key words: Flood peak, nature-based solutions, forest hydrology, hydrological modelling, SHETRAN, flood frequency, flood magnitude, land-cover change, upland afforestation.

A Framework for Organizing Current and Future Electric Utility Regulatory and Business Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Satchwell, Andrew; Cappers, Peter; Schwartz, Lisa

In this report, we will present a descriptive and organizational framework for incremental and fundamental changes to regulatory and utility business models in the context of clean energy public policy goals. We will also discuss the regulated utility's role in providing value-added services that relate to distributed energy resources, identify the "openness" of customer information and utility networks necessary to facilitate change, and discuss the relative risks, and the shifting of risks, for utilities and customers.

The potential value of Clostridium difficile vaccine: an economic computer simulation model.

PubMed

Lee, Bruce Y; Popovich, Michael J; Tian, Ye; Bailey, Rachel R; Ufberg, Paul J; Wiringa, Ann E; Muder, Robert R

2010-07-19

Efforts are currently underway to develop a vaccine against Clostridium difficile infection (CDI). We developed two decision analytic Monte Carlo computer simulation models: (1) an Initial Prevention Model depicting the decision whether to administer C. difficile vaccine to patients at-risk for CDI and (2) a Recurrence Prevention Model depicting the decision whether to administer C. difficile vaccine to prevent CDI recurrence. Our results suggest that a C. difficile vaccine could be cost-effective over a wide range of C. difficile risk, vaccine costs, and vaccine efficacies especially, when being used post-CDI treatment to prevent recurrent disease. (c) 2010 Elsevier Ltd. All rights reserved.

The Potential Value of Clostridium difficile Vaccine: An Economic Computer Simulation Model

PubMed Central

Lee, Bruce Y.; Popovich, Michael J.; Tian, Ye; Bailey, Rachel R.; Ufberg, Paul J.; Wiringa, Ann E.; Muder, Robert R.

2010-01-01

Efforts are currently underway to develop a vaccine against Clostridium difficile infection (CDI). We developed two decision analytic Monte Carlo computer simulation models: (1) an Initial Prevention Model depicting the decision whether to administer C. difficile vaccine to patients at-risk for CDI and (2) a Recurrence Prevention Model depicting the decision whether to administer C. difficile vaccine to prevent CDI recurrence. Our results suggest that a C. difficile vaccine could be cost-effective over a wide range of C. difficile risk, vaccine costs, and vaccine efficacies especially when being used post-CDI treatment to prevent recurrent disease. PMID:20541582

Exploring Migratory Dynamics on HIV Transmission: The Case of Mexicans in New York City and Puebla, Mexico

PubMed Central

Guilamo-Ramos, Vincent; McCarthy, Katharine; Muñoz-Laboy, Miguel A.; de Lourdes Rosas López, Maria

2014-01-01

Migration and population movement are increasingly viewed as important factors associated with HIV transmission risk. With growing awareness of the potential impact of migration on HIV transmission, several perspectives have emerged that posit differing dynamics of risk. We considered available data on the role of migration on HIV transmission among Mexican migrants in New York City and Puebla, Mexico. Specifically, we examined 3 distinct models of migratory dynamics of HIV transmission—namely, the structural model, the local contextual model, and the interplay model. In doing so, we reframed current public health perspectives on the role of migration on HIV transmission. PMID:24825203

What can('t) we do with global flood risk models?

NASA Astrophysics Data System (ADS)

Ward, Philip; Jongman, Brenden; Salamon, Peter; Simpson, Alanna; Winsemius, Hessel

2015-04-01

In recent years, several global scale flood risk models have become available. Within the scientific community these have been, and are being, used to assess and map the current levels of risk faced by countries and societies. Increasingly, they are also being used to assess how that level of risk may change in the future, under scenarios of climate change and/or socioeconomic development. More and more, these 'quick and not so dirty' methods are also being used in practice, for a large range of uses and applications, and by an increasing range of practitioners and decision makers. For example, assessments can be used by: International Financing Institutes for prioritising investments in the most promising natural disaster risk reduction measures and strategies; intra-national institutes in the monitoring of progress on risk reduction activities; the (re-)insurance industry in assessing their risk portfolios and potential changes in those portfolios under climate change; by multinational companies in assessing risks to their regional investments and supply chains; and by international aid organisations for improved resource planning. However, global scale flood risk models clearly have their limits, and therefore both modellers and users need to critically address the question 'What can('t) we do with global flood risk models?'. This contribution is intended to start a dialogue between model developers, users, and decision makers to better answer this question. We will provide a number of examples of how the GLOFRIS global flood risk model has recently been used in several practical applications, and share both the positive and negative insights gained through these experiences. We wish to discuss similar experiences with other groups of modelers, users, and decision-makers, in order to better understand and harness the potential of this new generation of models, understand the differences in model approaches followed and their impacts on applicability, and develop clarity on their limits and potential misuses.

Lunar Landing Operational Risk Model

NASA Technical Reports Server (NTRS)

Mattenberger, Chris; Putney, Blake; Rust, Randy; Derkowski, Brian

2010-01-01

Characterizing the risk of spacecraft goes beyond simply modeling equipment reliability. Some portions of the mission require complex interactions between system elements that can lead to failure without an actual hardware fault. Landing risk is currently the least characterized aspect of the Altair lunar lander and appears to result from complex temporal interactions between pilot, sensors, surface characteristics and vehicle capabilities rather than hardware failures. The Lunar Landing Operational Risk Model (LLORM) seeks to provide rapid and flexible quantitative insight into the risks driving the landing event and to gauge sensitivities of the vehicle to changes in system configuration and mission operations. The LLORM takes a Monte Carlo based approach to estimate the operational risk of the Lunar Landing Event and calculates estimates of the risk of Loss of Mission (LOM) - Abort Required and is Successful, Loss of Crew (LOC) - Vehicle Crashes or Cannot Reach Orbit, and Success. The LLORM is meant to be used during the conceptual design phase to inform decision makers transparently of the reliability impacts of design decisions, to identify areas of the design which may require additional robustness, and to aid in the development and flow-down of requirements.

A Risk-Based Approach for Aerothermal/TPS Analysis and Testing

NASA Technical Reports Server (NTRS)

Wright, Michael J.; Grinstead, Jay H.; Bose, Deepak

2007-01-01

The current status of aerothermal and thermal protection system modeling for civilian entry missions is reviewed. For most such missions, the accuracy of our simulations is limited not by the tools and processes currently employed, but rather by reducible deficiencies in the underlying physical models. Improving the accuracy of and reducing the uncertainties in these models will enable a greater understanding of the system level impacts of a particular thermal protection system and of the system operation and risk over the operational life of the system. A strategic plan will be laid out by which key modeling deficiencies can be identified via mission-specific gap analysis. Once these gaps have been identified, the driving component uncertainties are determined via sensitivity analyses. A Monte-Carlo based methodology is presented for physics-based probabilistic uncertainty analysis of aerothermodynamics and thermal protection system material response modeling. These data are then used to advocate for and plan focused testing aimed at reducing key uncertainties. The results of these tests are used to validate or modify existing physical models. Concurrently, a testing methodology is outlined for thermal protection materials. The proposed approach is based on using the results of uncertainty/sensitivity analyses discussed above to tailor ground testing so as to best identify and quantify system performance and risk drivers. A key component of this testing is understanding the relationship between the test and flight environments. No existing ground test facility can simultaneously replicate all aspects of the flight environment, and therefore good models for traceability to flight are critical to ensure a low risk, high reliability thermal protection system design. Finally, the role of flight testing in the overall thermal protection system development strategy is discussed.

Neural network model for growth of Salmonella serotypes in ground chicken subjected to temperature abuse during cold storage for application in HACCP and risk assessment

USDA-ARS?s Scientific Manuscript database

With the advent of commercial software applications, it is now easy to develop neural network models for predictive microbiology applications. However, different versions of the model may be required to meet the divergent needs of model users. In the current study, the commercial software applicat...

Making Pathways: Young People and Their Informal Vocational Learning. Discussion Paper. Working Paper.

ERIC Educational Resources Information Center

Bye, Jayne

Current research into youth transitions in Australia documents an increasingly individualized process in which significant numbers of youths are deemed at risk of not making a successful transition from school to work. Many theorists are questioning the applicability of the linear model of transition to current conditions. Other theorists are…

Concepts and challenges in cancer risk prediction for the space radiation environment.

PubMed

Barcellos-Hoff, Mary Helen; Blakely, Eleanor A; Burma, Sandeep; Fornace, Albert J; Gerson, Stanton; Hlatky, Lynn; Kirsch, David G; Luderer, Ulrike; Shay, Jerry; Wang, Ya; Weil, Michael M

2015-07-01

Cancer is an important long-term risk for astronauts exposed to protons and high-energy charged particles during travel and residence on asteroids, the moon, and other planets. NASA's Biomedical Critical Path Roadmap defines the carcinogenic risks of radiation exposure as one of four type I risks. A type I risk represents a demonstrated, serious problem with no countermeasure concepts, and may be a potential "show-stopper" for long duration spaceflight. Estimating the carcinogenic risks for humans who will be exposed to heavy ions during deep space exploration has very large uncertainties at present. There are no human data that address risk from extended exposure to complex radiation fields. The overarching goal in this area to improve risk modeling is to provide biological insight and mechanistic analysis of radiation quality effects on carcinogenesis. Understanding mechanisms will provide routes to modeling and predicting risk and designing countermeasures. This white paper reviews broad issues related to experimental models and concepts in space radiation carcinogenesis as well as the current state of the field to place into context recent findings and concepts derived from the NASA Space Radiation Program. Copyright © 2015 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.

Epidemiology of Lung Cancer.

PubMed

Schwartz, Ann G; Cote, Michele L

2016-01-01

Lung cancer continues to be one of the most common causes of cancer death despite understanding the major cause of the disease: cigarette smoking. Smoking increases lung cancer risk 5- to 10-fold with a clear dose-response relationship. Exposure to environmental tobacco smoke among nonsmokers increases lung cancer risk about 20%. Risks for marijuana and hookah use, and the new e-cigarettes, are yet to be consistently defined and will be important areas for continued research as use of these products increases. Other known environmental risk factors include exposures to radon, asbestos, diesel, and ionizing radiation. Host factors have also been associated with lung cancer risk, including family history of lung cancer, history of chronic obstructive pulmonary disease and infections. Studies to identify genes associated with lung cancer susceptibility have consistently identified chromosomal regions on 15q25, 6p21 and 5p15 associated with lung cancer risk. Risk prediction models for lung cancer typically include age, sex, cigarette smoking intensity and/or duration, medical history, and occupational exposures, however there is not yet a risk prediction model currently recommended for general use. As lung cancer screening becomes more widespread, a validated model will be needed to better define risk groups to inform screening guidelines.

Development of a prototype Typhoon Risk Model over the Korean Peninsula

NASA Astrophysics Data System (ADS)

Kim, K. Y.; Cocke, S.; Shin, D. W.; CHOI, M.; Kwon, J.

2016-12-01

Risk can be defined as probability of a given hazard of a given level causing a particular level of loss of damage (Alexander, 2000). Risk management is important for mitigation and developing plans for emergencies. More effective risk management strategies can help reduce potential losses from natural disasters like typhoon, floods, earthquakes, and so on. We are developing a prototype typhoon risk model to assess the current and potentially future hazard due to typhoons in the Western Pacific. To develop the typhoon risk model, a variety of sources of data over Korea are used such as population, damage to buildings, agriculture, ships, etc. The model is based on proven concepts used in catastrophe models that have been used in the U.S. and other regions of the world. Recently, the sea surface temperatures where typhoons have occurred have tended to increase. According to recent studies of global warming, the intensity of typhoons could increase, and the frequency of typhoons may decrease in the future climate. The prototype risk model can help us determine the change in risk as a consequence of the change in typhoon activity. We focus on Korea and other regions of interest to Korean insurers, re-insurers, and related industries. The model can potentially be coupled to various damage models or emergency management systems for planning and mitigation. In addition, the assessment would be useful for emergency planners, coastal community planners, and private and governmental insurance programs. This work was funded by the Korea Meteorological Administration Research and Development Program under Grant KMIPA2016-8030.

Assessment of uncertainties in radiation-induced cancer risk predictions at clinically relevant doses

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nguyen, J.; Moteabbed, M.; Paganetti, H., E-mail: hpaganetti@mgh.harvard.edu

2015-01-15

Purpose: Theoretical dose–response models offer the possibility to assess second cancer induction risks after external beam therapy. The parameters used in these models are determined with limited data from epidemiological studies. Risk estimations are thus associated with considerable uncertainties. This study aims at illustrating uncertainties when predicting the risk for organ-specific second cancers in the primary radiation field illustrated by choosing selected treatment plans for brain cancer patients. Methods: A widely used risk model was considered in this study. The uncertainties of the model parameters were estimated with reported data of second cancer incidences for various organs. Standard error propagationmore » was then subsequently applied to assess the uncertainty in the risk model. Next, second cancer risks of five pediatric patients treated for cancer in the head and neck regions were calculated. For each case, treatment plans for proton and photon therapy were designed to estimate the uncertainties (a) in the lifetime attributable risk (LAR) for a given treatment modality and (b) when comparing risks of two different treatment modalities. Results: Uncertainties in excess of 100% of the risk were found for almost all organs considered. When applied to treatment plans, the calculated LAR values have uncertainties of the same magnitude. A comparison between cancer risks of different treatment modalities, however, does allow statistically significant conclusions. In the studied cases, the patient averaged LAR ratio of proton and photon treatments was 0.35, 0.56, and 0.59 for brain carcinoma, brain sarcoma, and bone sarcoma, respectively. Their corresponding uncertainties were estimated to be potentially below 5%, depending on uncertainties in dosimetry. Conclusions: The uncertainty in the dose–response curve in cancer risk models makes it currently impractical to predict the risk for an individual external beam treatment. On the other hand, the ratio of absolute risks between two modalities is less sensitive to the uncertainties in the risk model and can provide statistically significant estimates.« less

The Integrated Medical Model: Statistical Forecasting of Risks to Crew Health and Mission Success

NASA Technical Reports Server (NTRS)

Fitts, M. A.; Kerstman, E.; Butler, D. J.; Walton, M. E.; Minard, C. G.; Saile, L. G.; Toy, S.; Myers, J.

2008-01-01

The Integrated Medical Model (IMM) helps capture and use organizational knowledge across the space medicine, training, operations, engineering, and research domains. The IMM uses this domain knowledge in the context of a mission and crew profile to forecast crew health and mission success risks. The IMM is most helpful in comparing the risk of two or more mission profiles, not as a tool for predicting absolute risk. The process of building the IMM adheres to Probability Risk Assessment (PRA) techniques described in NASA Procedural Requirement (NPR) 8705.5, and uses current evidence-based information to establish a defensible position for making decisions that help ensure crew health and mission success. The IMM quantitatively describes the following input parameters: 1) medical conditions and likelihood, 2) mission duration, 3) vehicle environment, 4) crew attributes (e.g. age, sex), 5) crew activities (e.g. EVA's, Lunar excursions), 6) diagnosis and treatment protocols (e.g. medical equipment, consumables pharmaceuticals), and 7) Crew Medical Officer (CMO) training effectiveness. It is worth reiterating that the IMM uses the data sets above as inputs. Many other risk management efforts stop at determining only likelihood. The IMM is unique in that it models not only likelihood, but risk mitigations, as well as subsequent clinical outcomes based on those mitigations. Once the mathematical relationships among the above parameters are established, the IMM uses a Monte Carlo simulation technique (a random sampling of the inputs as described by their statistical distribution) to determine the probable outcomes. Because the IMM is a stochastic model (i.e. the input parameters are represented by various statistical distributions depending on the data type), when the mission is simulated 10-50,000 times with a given set of medical capabilities (risk mitigations), a prediction of the most probable outcomes can be generated. For each mission, the IMM tracks which conditions occurred and decrements the pharmaceuticals and supplies required to diagnose and treat these medical conditions. If supplies are depleted, then the medical condition goes untreated, and crew and mission risk increase. The IMM currently models approximately 30 medical conditions. By the end of FY2008, the IMM will be modeling over 100 medical conditions, approximately 60 of which have been recorded to have occurred during short and long space missions.

Rhinitis Associated with Pesticide Exposure among Commercial Pesticide Applicators in the Agricultural Health Study

PubMed Central

Slager, Rebecca E.; Poole, Jill A.; LeVan, Tricia D.; Sandler, Dale P.; Alavanja, Michael C. R.; Hoppin, Jane A.

2010-01-01

Objectives Rhinitis is common, but the risk factors are not well described. To investigate the association between current rhinitis and pesticide use, we used data from 2,245 Iowa commercial pesticide applicators in the Agricultural Health Study. Methods Using logistic regression models adjusted for age, education, and growing up on a farm, we evaluated the association between current rhinitis and 34 pesticides used in the past year. Results Seventy-four percent of commercial pesticide applicators reported at least one episode of rhinitis in the past year (current rhinitis). Five pesticides used in the past year were significantly positively associated with current rhinitis: the herbicides 2,4-D, glyphosate and petroleum oil, the insecticide diazinon and the fungicide benomyl. The association for 2,4-D and glyphosate was limited to individuals who used both in the past year (Odds Ratio = 1.42, 95% Confidence Interval: 1.14, 1.77). Both petroleum oil and diazinon showed consistent evidence of an association with rhinitis, based on both current use and exposure-response models. We saw no evidence of confounding by common agricultural rhinitis triggers such as handling grain or hay. Conclusions Exposure to pesticides may increase the risk of rhinitis. PMID:19289390

A Risk-based Assessment And Management Framework For Multipollutant Air Quality

PubMed Central

Frey, H. Christopher; Hubbell, Bryan

2010-01-01

The National Research Council recommended both a risk- and performance-based multipollutant approach to air quality management. Specifically, management decisions should be based on minimizing the exposure to, and risk of adverse effects from, multiple sources of air pollution and that the success of these decisions should be measured by how well they achieved this objective. We briefly describe risk analysis and its application within the current approach to air quality management. Recommendations are made as to how current practice could evolve to support a fully risk- and performance-based multipollutant air quality management system. The ability to implement a risk assessment framework in a credible and policy-relevant manner depends on the availability of component models and data which are scientifically sound and developed with an understanding of their application in integrated assessments. The same can be said about accountability assessments used to evaluate the outcomes of decisions made using such frameworks. The existing risk analysis framework, although typically applied to individual pollutants, is conceptually well suited for analyzing multipollutant management actions. Many elements of this framework, such as emissions and air quality modeling, already exist with multipollutant characteristics. However, the framework needs to be supported with information on exposure and concentration response relationships that result from multipollutant health studies. Because the causal chain that links management actions to emission reductions, air quality improvements, exposure reductions and health outcomes is parallel between prospective risk analyses and retrospective accountability assessments, both types of assessment should be placed within a single framework with common metrics and indicators where possible. Improvements in risk reductions can be obtained by adopting a multipollutant risk analysis framework within the current air quality management system, e.g. focused on standards for individual pollutants and with separate goals for air toxics and ambient pollutants. However, additional improvements may be possible if goals and actions are defined in terms of risk metrics that are comparable across criteria pollutants and air toxics (hazardous air pollutants), and that encompass both human health and ecological risks. PMID:21209847

Use of Influenza Risk Assessment Tool for Prepandemic Preparedness

PubMed Central

Trock, Susan C.

2018-01-01

In 2010, the Centers for Disease Control and Prevention began to develop an Influenza Risk Assessment Tool (IRAT) to methodically capture and assess information relating to influenza A viruses not currently circulating among humans. The IRAT uses a multiattribute, additive model to generate a summary risk score for each virus. Although the IRAT is not intended to predict the next pandemic influenza A virus, it has provided input into prepandemic preparedness decisions. PMID:29460739

Re-Evaluating the Possible Increased Risk of HIV Acquisition With Progestin-Only Injectables Versus Maternal Mortality and Life Expectancy in Africa: A Decision Analysis.

PubMed

Rodriguez, Maria Isabel; Gaffield, Mary E; Han, Leo; Caughey, Aaron B

2017-12-28

The association between increased risk of HIV acquisition and use of progestin-only injectables (POIs) is controversial. We sought to compare the competing risks of maternal mortality and HIV acquisition with use of POIs using updated data on this association and considering an expanded number of African countries. We designed a decision-analytic model to compare the benefits and risks of POIs on the competing risks of maternal mortality and HIV acquisition on life expectancy for women in 9 African countries. For the purposes of this analysis, we assumed that POIs were associated with an increased risk of HIV acquisition (hazards ratio of 1.4). Our primary outcome was life-years and the population was women of reproductive age (15-49 years) in these countries, who did not have HIV infection and were not currently planning a pregnancy. Probabilities for each variable included in the model, such as HIV incidence, access to antiretroviral therapy, and contraceptive prevalence, were obtained from the literature. Univariate and multivariate sensitivity analyses were performed to check model assumptions and explore how uncertainty in estimates would affect the model results. In all countries, discontinuation of POIs without replacement with an equally effective contraceptive method would result in decreased life expectancy due to a significant increase in maternal deaths. While the removal of POIs from the market would result in the prevention of some new cases of HIV, the life-years gained from this are mitigated due to the marked increase in neonatal HIV cases and maternal mortality with associated life-years lost. In all countries, except South Africa, typical-use contraceptive failure rates with POIs would need to exceed 39%, and more than half of women currently using POIs would have to switch to another effective method, for the removal of POIs to demonstrate an increase in total life-years. Women living in sub-Saharan Africa cope with both high rates of HIV infection and high rates of pregnancy-related maternal death relative to the rest of the world. Based on the most current estimates, our model suggests that removal of POI contraception from the market without effective and acceptable contraception replacement would have a net negative effect on maternal health, life expectancy, and mortality under a variety of scenarios. © Rodriguez et al.

"Staying safe" - a narrative review of falls prevention in people with Parkinson's - "PDSAFE".

PubMed

Hulbert, Sophia; Rochester, Lynn; Nieuwboer, Alice; Goodwin, Vicki; Fitton, Carolyn; Chivers-Seymour, Kim; Ashburn, Ann

2018-05-18

Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms. Falling is common and disabling. Current medical management shows minimal impact to reduce falls or fall-related risk factors, such as deficits in gait, strength, and postural instability. Despite evidence supporting rehabilitation in reducing fall risk factors, the most appropriate intervention to reduce overall fall rate remains inconclusive. This article aims to 1) synthesise current evidence and conceptual models of falls rehabilitation in Parkinson's in a narrative review; and based on this evidence, 2) introduce the treatment protocol used in the falls prevention and multi-centre clinical trial "PDSAFE". Search of four bibliographic databases using the terms "Parkinson*" and "Fall*" combined with each of the following; "Rehab*, Balanc*, Strength*, Strateg*and Exercis*" and a framework for narrative review was followed. A total of 3557 papers were identified, 416 were selected for review. The majority report the impact of rehabilitation on isolated fall risk factors. Twelve directly measure the impact on overall fall rate. Results were used to construct a narrative review with conceptual discussion based on the "International Classification of Functioning", leading to presentation of the "PDSAFE" intervention protocol. Evidence suggests training single, fall risk factors may not affect overall fall rate. Combining with behavioural and strategy training in a functional, personalised multi-dimensional model, addressing all components of the "International Classification of Functioning" is likely to provide a greater influence on falls reduction. "PDSAFE" is a multi-dimensional, physiotherapist delivered, individually tailored, progressive, home-based programme. It is designed with a strong evidence-based approach and illustrates a model for the clinical delivery of the conceptual theory discussed. Implications for Rehabilitation Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms, where falling is common and disabling. Current medical and surgical management have minimal impact on falls, rehabilitation of falls risk factors has strong evidence but the most appropriate intervention to reduce overall fall rate remains inconclusive. Addressing all components of the International Classification of Function in a multifactorial model when designing falls rehabilitation interventions may be more effective at reducing fall rates in people with Parkinson's than treating isolated risk factors. The clinical model for falls rehabilitation in people with Parkinson's should be multi-dimensional.

Dependence regulation in newlywed couples: A prospective examination.

PubMed

Derrick, Jaye L; Leonard, Kenneth E; Homish, Gregory G

2012-12-01

According to the Risk Regulation Model (Murray, S. L., Holmes, J. G., & Collins, N. L. (2006). Optimizing assurance: The risk regulation system in relationships. Psychological Bulletin, 132 , 641-666), people need to trust in their partner's regard before they risk interdependence. The current study prospectively examines the association between perceived regard and levels of dependence in newlywed couples over nine years of marriage. Analyses demonstrate that changes in perceived regard predict levels of dependence, changes in dependence do not predict perceived regard, and alternative explanations cannot account for these effects. Further, changes in perceived regard prospectively predict divorce, and levels of dependence mediate this association. Results are discussed in terms of the dependence regulation component of the Risk Regulation Model.

[Integrated Management Area of Vascular Risk: A new organisational model for global control of risk factors].

PubMed

Armario, P; Jericó, C; Vila, L; Freixa, R; Martin-Castillejos, C; Rotllan, M

Cardiovascular disease (CVD), is a major cause of morbidity and mortality that increases the cost of care. Currently there is a low degree of control of the main cardiovascular risk factors, although we have a good therapeutic arsenal. To achieve the improvement of this reality, a good coordination and multidisciplinary participation are essential. The development of new organizational models such as the Integrated Management Area of Vascular Risk can facilitate the therapeutic harmonization and unification of the health messages offered by different levels of care, based on clinical practice guidelines, in order to provide patient-centred integrated care. Copyright © 2016 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Fractal Risk Assessment of ISS Propulsion Module in Meteoroid and Orbital Debris Environments

NASA Technical Reports Server (NTRS)

Mog, Robert A.

2001-01-01

A unique and innovative risk assessment of the International Space Station (ISS) Propulsion Module is conducted using fractal modeling of the Module's response to the meteoroid and orbital debris environments. Both the environment models and structural failure modes due to the resultant hypervelocity impact phenomenology, as well as Module geometry, are investigated for fractal applicability. The fractal risk assessment methodology could produce a greatly simplified alternative to current methodologies, such as BUMPER analyses, while maintaining or increasing the number of complex scenarios that can be assessed. As a minimum, this innovative fractal approach will provide an independent assessment of existing methodologies in a unique way.

Evaluation of Enhanced Risk Monitors for Use on Advanced Reactors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Veeramany, Arun; Bonebrake, Christopher A.

This study provides an overview of the methodology for integrating time-dependent failure probabilities into nuclear power reactor risk monitors. This prototypic enhanced risk monitor (ERM) methodology was evaluated using a hypothetical probabilistic risk assessment (PRA) model, generated using a simplified design of a liquid-metal-cooled advanced reactor (AR). Component failure data from industry compilation of failures of components similar to those in the simplified AR model were used to initialize the PRA model. Core damage frequency (CDF) over time were computed and analyzed. In addition, a study on alternative risk metrics for ARs was conducted. Risk metrics that quantify the normalizedmore » cost of repairs, replacements, or other operations and management (O&M) actions were defined and used, along with an economic model, to compute the likely economic risk of future actions such as deferred maintenance based on the anticipated change in CDF due to current component condition and future anticipated degradation. Such integration of conventional-risk metrics with alternate-risk metrics provides a convenient mechanism for assessing the impact of O&M decisions on safety and economics of the plant. It is expected that, when integrated with supervisory control algorithms, such integrated-risk monitors will provide a mechanism for real-time control decision-making that ensure safety margins are maintained while operating the plant in an economically viable manner.« less

Sensation seeking and smoking behaviors among adolescents in the Republic of Korea.

PubMed

Hwang, Heejin; Park, Sunhee

2015-06-01

This study aimed to explore the relationship between the four components of sensation seeking (i.e., disinhibition, thrill and adventure seeking, experience seeking, and boredom susceptibility) and three types of smoking behavior (i.e., non-smoking, experimental smoking, and current smoking) among high school students in the Republic of Korea. Multivariate multinomial logistic regression analysis was performed using two models. In Model 1, the four subscales of sensation seeking were used as covariates, and in Model 2, other control factors (i.e., characteristics related to demographics, individuals, family, school, and friends) were added to Model 1 in order to adjust for their effects. In Model 1, the impact of disinhibition on experimental smoking and current smoking was statistically significant. In Model 2, the influence of disinhibition on both of these smoking behaviors remained statistically significant after controlling for all the other covariates. Also, the effect of thrill and adventure seeking on experimental smoking was statistically significant. The two statistically significant subscales of sensation seeking were positively associated with the risk of smoking behaviors. According to extant literature and current research, sensation seeking, particularly disinhibition, is strongly associated with smoking among youth. Therefore, sensation seeking should be measured among adolescents to identify those who are at greater risk of smoking and to develop more effective intervention strategies in order to curb the smoking epidemic among youth. Copyright © 2015 Elsevier Ltd. All rights reserved.

NASA Occupant Protection Standards Development

NASA Technical Reports Server (NTRS)

Somers, Jeffrey; Gernhardt, Michael; Lawrence, Charles

2012-01-01

Historically, spacecraft landing systems have been tested with human volunteers, because analytical methods for estimating injury risk were insufficient. These tests were conducted with flight-like suits and seats to verify the safety of the landing systems. Currently, NASA uses the Brinkley Dynamic Response Index to estimate injury risk, although applying it to the NASA environment has drawbacks: (1) Does not indicate severity or anatomical location of injury (2) Unclear if model applies to NASA applications. Because of these limitations, a new validated, analytical approach was desired. Leveraging off of the current state of the art in automotive safety and racing, a new approach was developed. The approach has several aspects: (1) Define the acceptable level of injury risk by injury severity (2) Determine the appropriate human surrogate for testing and modeling (3) Mine existing human injury data to determine appropriate Injury Assessment Reference Values (IARV). (4) Rigorously Validate the IARVs with sub-injurious human testing (5) Use validated IARVs to update standards and vehicle requirement

A model for simulating the active dispersal of juvenile sea turtles with a case study on western Pacific leatherback turtles.

PubMed

Gaspar, Philippe; Lalire, Maxime

2017-01-01

Oceanic currents are known to broadly shape the dispersal of juvenile sea turtles during their pelagic stage. Accordingly, simple passive drift models are widely used to investigate the distribution at sea of various juvenile sea turtle populations. However, evidence is growing that juveniles do not drift purely passively but also display some swimming activity likely directed towards favorable habitats. We therefore present here a novel Sea Turtle Active Movement Model (STAMM) in which juvenile sea turtles actively disperse under the combined effects of oceanic currents and habitat-driven movements. This model applies to all sea turtle species but is calibrated here for leatherback turtles (Dermochelys coriacea). It is first tested in a simulation of the active dispersal of juveniles originating from Jamursba-Medi, a main nesting beach of the western Pacific leatherback population. Dispersal into the North Pacific Ocean is specifically investigated. Simulation results demonstrate that, while oceanic currents broadly shape the dispersal area, modeled habitat-driven movements strongly structure the spatial and temporal distribution of juveniles within this area. In particular, these movements lead juveniles to gather in the North Pacific Transition Zone (NPTZ) and to undertake seasonal north-south migrations. More surprisingly, juveniles in the NPTZ are simulated to swim mostly towards west which considerably slows down their progression towards the American west coast. This increases their residence time, and hence the risk of interactions with fisheries, in the central and eastern part of the North Pacific basin. Simulated habitat-driven movements also strongly reduce the risk of cold-induced mortality. This risk appears to be larger among the juveniles that rapidly circulate into the Kuroshio than among those that first drift into the North Equatorial Counter Current (NECC). This mechanism might induce marked interannual variability in juvenile survival as the strength and position of the NECC are directly linked to El Niño activity.

A model for simulating the active dispersal of juvenile sea turtles with a case study on western Pacific leatherback turtles

PubMed Central

Lalire, Maxime

2017-01-01

Oceanic currents are known to broadly shape the dispersal of juvenile sea turtles during their pelagic stage. Accordingly, simple passive drift models are widely used to investigate the distribution at sea of various juvenile sea turtle populations. However, evidence is growing that juveniles do not drift purely passively but also display some swimming activity likely directed towards favorable habitats. We therefore present here a novel Sea Turtle Active Movement Model (STAMM) in which juvenile sea turtles actively disperse under the combined effects of oceanic currents and habitat-driven movements. This model applies to all sea turtle species but is calibrated here for leatherback turtles (Dermochelys coriacea). It is first tested in a simulation of the active dispersal of juveniles originating from Jamursba-Medi, a main nesting beach of the western Pacific leatherback population. Dispersal into the North Pacific Ocean is specifically investigated. Simulation results demonstrate that, while oceanic currents broadly shape the dispersal area, modeled habitat-driven movements strongly structure the spatial and temporal distribution of juveniles within this area. In particular, these movements lead juveniles to gather in the North Pacific Transition Zone (NPTZ) and to undertake seasonal north-south migrations. More surprisingly, juveniles in the NPTZ are simulated to swim mostly towards west which considerably slows down their progression towards the American west coast. This increases their residence time, and hence the risk of interactions with fisheries, in the central and eastern part of the North Pacific basin. Simulated habitat-driven movements also strongly reduce the risk of cold-induced mortality. This risk appears to be larger among the juveniles that rapidly circulate into the Kuroshio than among those that first drift into the North Equatorial Counter Current (NECC). This mechanism might induce marked interannual variability in juvenile survival as the strength and position of the NECC are directly linked to El Niño activity. PMID:28746389

Reinforcement Sensitivity and Risk for Psychopathology Following Exposure to Violence: A Vulnerability-Specificity Model in Latino Youth

ERIC Educational Resources Information Center

Gudino, Omar G.; Nadeem, Erum; Kataoka, Sheryl H.; Lau, Anna S.

2012-01-01

Urban Latino youth are exposed to high rates of violence, which increases risk for diverse forms of psychopathology. The current study aims to increase specificity in predicting responses by testing the hypothesis that youths' reinforcement sensitivity--behavioral inhibition (BIS) and behavioral approach (BAS)--is associated with specific clinical…

Prevalence and Determinants of Suicide Ideation among Lebanese Adolescents: Results of the GSHS Lebanon 2005

ERIC Educational Resources Information Center

Mahfoud, Ziyad R.; Afifi, Rema A.; Haddad, Pascale H.; DeJong, Jocelyn

2011-01-01

The current study examined prevalence and risk factors for suicide ideation in 5038 Lebanese adolescents using Global School Health Survey data. Around 16% of Lebanese adolescents thought of suicide. Multivariate logistic regression models showed that risk factors for suicide ideation included poor mental health (felt lonely, felt worried, felt…

Relationship between reported prior condom use and current self-perceived risk of acquiring HIV among mobile female sex workers in southern India

PubMed Central

2011-01-01

Background With the evolution of Health Belief Model, risk perception has been identified as one of several core components of public health interventions. While female sex workers (FSWs) in India continue to be at most risk of acquiring and transmitting HIV, little is known about their perception towards risk of acquiring HIV and how this perception depends upon their history of consistent condom use behavior with different type of partners. The objective of this study is to fill this gap in the literature by examining this relationship among mobile FSWs in southern India. Methods We analyzed data for 5,413 mobile FSWs from a cross-sectional behavioral survey conducted in 22 districts from four states in southern India. This survey assessed participants’ demographics, condom use in sex with different types of partners, continuation of sex while experiencing STI symptoms, alcohol use before having sex, and self-perceived risk of acquiring HIV. Descriptive analyses and multilevel logistic regression models were used to examine the associations between risky sexual behaviors and self-perceived risk of acquiring HIV; and to understand the geographical differences in HIV risk perception. Results Of the total mobile FSWs, only two-fifths (40%) perceived themselves to be at high risk of acquiring HIV; more so in the state of Andhra Pradesh (56%) and less in Maharashtra (17%). FSWs seem to assess their current risk of acquiring HIV primarily on the basis of their past condom use behavior with occasional clients and less on the basis of their past condom use behaviors with regular clients and non-paying partners. Prior inconsistent condom use with occasional clients was independently associated with current perception of high HIV risk (adjusted odds ratio [aOR)] = 2.1, 95% confidence interval [CI]: 1.7-2.6). In contrast, prior inconsistent condom use with non-paying partners was associated with current perception of low HIV risk (aOR= 0.7, 95% CI: 0.5-0.9). The congruence between HIV risk perception and condom use with occasional clients was high: only 12% of FSWs reported inconsistent condom use with occasional clients but perceived themselves to be at low risk of acquiring HIV. Conclusion The association between high risk perception of acquiring HIV and inconsistent condom use, especially with regular clients and non-paying partners, has not been completely internalized by this high risk group of mobile FSWs in India. Motivational efforts to prevent HIV should emphasize the importance of accurately assessing an individual’s risk of acquiring HIV based on condom use behavior with all types of partners: occasional and regular clients as well as non-paying partners; and encourage behavior change based on an accurate self-assessment of HIV risk. PMID:22375731

Household portfolio choices, health status and health care systems: A cross-country analysis based on SHARE

PubMed Central

Atella, Vincenzo; Brunetti, Marianna; Maestas, Nicole

2013-01-01

Health risk is increasingly viewed as an important form of background risk that affects household portfolio decisions. However, its role might be mediated by the presence of a protective full-coverage national health service that could reduce households’ probability of incurring current and future out-of-pocket medical expenditures. We use SHARE data to study the influence of current health status and future health risk on the decision to hold risky assets, across ten European countries with different health systems, each offering a different degree of protection against out-of-pocket medical expenditures. We find robust empirical evidence that perceived health status matters more than objective health status and, consistent with the theory of background risk, health risk affects portfolio choices only in countries with less protective health care systems. Furthermore, portfolio decisions consistent with background risk models are observed only with respect to middle-aged and highly-educated investors. PMID:23885134

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Risk factors associated with suicide in current and former US military personnel.

PubMed

LeardMann, Cynthia A; Powell, Teresa M; Smith, Tyler C; Bell, Michael R; Smith, Besa; Boyko, Edward J; Hooper, Tomoko I; Gackstetter, Gary D; Ghamsary, Mark; Hoge, Charles W

2013-08-07

Beginning in 2005, the incidence of suicide deaths in the US military began to sharply increase. Unique stressors, such as combat deployments, have been assumed to underlie the increasing incidence. Previous military suicide studies, however, have relied on case series and cross-sectional investigations and have not linked data during service with postservice periods. To prospectively identify and quantify risk factors associated with suicide in current and former US military personnel including demographic, military, mental health, behavioral, and deployment characteristics. Prospective longitudinal study with accrual and assessment of participants in 2001, 2004, and 2007. Questionnaire data were linked with the National Death Index and the Department of Defense Medical Mortality Registry through December 31, 2008. Participants were current and former US military personnel from all service branches, including active and Reserve/National Guard, who were included in the Millennium Cohort Study (N = 151,560). Death by suicide captured by the National Death Index and the Department of Defense Medical Mortality Registry. Through the end of 2008, findings were 83 suicides in 707,493 person-years of follow-up (11.73/100,000 person-years [95% CI, 9.21-14.26]). In Cox models adjusted for age and sex, factors significantly associated with increased risk of suicide included male sex, depression, manic-depressive disorder, heavy or binge drinking, and alcohol-related problems. None of the deployment-related factors (combat experience, cumulative days deployed, or number of deployments) were associated with increased suicide risk in any of the models. In multivariable Cox models, individuals with increased risk for suicide were men (hazard ratio [HR], 2.14; 95% CI, 1.17-3.92; P = .01; attributable risk [AR], 3.5 cases/10,000 persons), and those with depression (HR, 1.96; 95% CI, 1.05-3.64; P = .03; AR, 6.9/10,000 persons), manic-depressive disorder (HR, 4.35; 95% CI, 1.56-12.09; P = .005; AR, 35.6/10,000 persons), or alcohol-related problems (HR, 2.56; 95% CI, 1.56-4.18; P <.001; AR, 7.7/10,000 persons). A nested, matched case-control analysis using 20:1 control participants per case confirmed these findings. In this sample of current and former military personnel observed July 1, 2001-December 31, 2008, suicide risk was independently associated with male sex and mental disorders but not with military-specific variables. These findings may inform approaches to mitigating suicide risk in this population.

Advances in emerging drugs for the treatment of neuroblastoma.

PubMed

Berlanga, Pablo; Cañete, Adela; Castel, Victoria

2017-03-01

Neuroblastoma is the most common solid extracranial tumor of childhood. Outcome for children with high-risk neuroblastoma remains suboptimal. More than half of children diagnosed with high-risk neuroblastoma either do not respond to conventional therapies or relapse after treatment with dismal prognosis. Areas covered: This paper presents a short review of the state of the art in the current treatment of high-risk neuroblastoma. An updated review of new targeted therapies in this group of patients is also presented. Expert opinion: In order to improve prognosis for high-risk patients there is an urgent need to better understand spatial and temporal heterogeneity and obtain new predictive preclinical models in neuroblastoma. Combination strategies with conventional chemotherapy and/or other targeted therapies may overcome current ALK inhibitors resistance. Improvement of international and transatlantic cooperation to speed clinical trials accrual is needed.

Niche syndromes, species extinction risks, and management under climate change.

PubMed

Sax, Dov F; Early, Regan; Bellemare, Jesse

2013-09-01

The current distributions of species are often assumed to correspond with the total set of environmental conditions under which species can persist. When this assumption is incorrect, extinction risk estimated from species distribution models can be misleading. The degree to which species can tolerate or even thrive under conditions found beyond their current distributions alters extinction risks, time lags in realizing those risks, and the usefulness of alternative management strategies. To inform these issues, we propose a conceptual framework within which empirical data could be used to generate hypotheses regarding the realized, fundamental, and 'tolerance' niche of species. Although these niche components have rarely been characterized over geographic scales, we suggest that this could be done for many plant species by comparing native, naturalized, and horticultural distributions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Operational prediction of rip currents using numerical model and nearshore bathymetry from video images

NASA Astrophysics Data System (ADS)

Sembiring, L.; Van Ormondt, M.; Van Dongeren, A. R.; Roelvink, J. A.

2017-07-01

Rip currents are one of the most dangerous coastal hazards for swimmers. In order to minimize the risk, a coastal operational-process based-model system can be utilized in order to provide forecast of nearshore waves and currents that may endanger beach goers. In this paper, an operational model for rip current prediction by utilizing nearshore bathymetry obtained from video image technique is demonstrated. For the nearshore scale model, XBeach1 is used with which tidal currents, wave induced currents (including the effect of the wave groups) can be simulated simultaneously. Up-to-date bathymetry will be obtained using video images technique, cBathy 2. The system will be tested for the Egmond aan Zee beach, located in the northern part of the Dutch coastline. This paper will test the applicability of bathymetry obtained from video technique to be used as input for the numerical modelling system by comparing simulation results using surveyed bathymetry and model results using video bathymetry. Results show that the video technique is able to produce bathymetry converging towards the ground truth observations. This bathymetry validation will be followed by an example of operational forecasting type of simulation on predicting rip currents. Rip currents flow fields simulated over measured and modeled bathymetries are compared in order to assess the performance of the proposed forecast system.

Relative risk for HIV in India - An estimate using conditional auto-regressive models with Bayesian approach.

PubMed

Kandhasamy, Chandrasekaran; Ghosh, Kaushik

2017-02-01

Indian states are currently classified into HIV-risk categories based on the observed prevalence counts, percentage of infected attendees in antenatal clinics, and percentage of infected high-risk individuals. This method, however, does not account for the spatial dependence among the states nor does it provide any measure of statistical uncertainty. We provide an alternative model-based approach to address these issues. Our method uses Poisson log-normal models having various conditional autoregressive structures with neighborhood-based and distance-based weight matrices and incorporates all available covariate information. We use R and WinBugs software to fit these models to the 2011 HIV data. Based on the Deviance Information Criterion, the convolution model using distance-based weight matrix and covariate information on female sex workers, literacy rate and intravenous drug users is found to have the best fit. The relative risk of HIV for the various states is estimated using the best model and the states are then classified into the risk categories based on these estimated values. An HIV risk map of India is constructed based on these results. The choice of the final model suggests that an HIV control strategy which focuses on the female sex workers, intravenous drug users and literacy rate would be most effective. Copyright © 2017 Elsevier Ltd. All rights reserved.

RiskScape Volcano: Development of a risk assessment tool for volcanic hazards

NASA Astrophysics Data System (ADS)

Deligne, Natalia; King, Andrew; Jolly, Gill; Wilson, Grant; Wilson, Tom; Lindsay, Jan

2013-04-01

RiskScape is a multi-hazard risk assessment tool developed by GNS Science and the National Institute of Water and Atmospheric Research Ltd. (NIWA) in New Zealand that models the risk and impact of various natural hazards on a given built environment. RiskScape has a modular structure: the hazard module models hazard exposure (e.g., ash thickness at a given location), the asset module catalogues assets (built environment, infrastructure, and people) and their attributes exposed to the hazard, and the vulnerability module models the consequences of asset exposure to the hazard. Hazards presently included in RiskScape are earthquakes, river floods, tsunamis, windstorms, and ash from volcanic eruptions (specifically from Ruapehu). Here we present our framework for incorporating other volcanic hazards (e.g., pyroclastic density currents, lava flows, lahars, ground deformation) into RiskScape along with our approach for assessing asset vulnerability. We also will discuss the challenges of evaluating risk for 'point source' (e.g., stratovolcanoes) vs 'diffuse' (e.g., volcanic fields) volcanism using Ruapehu and the Auckland volcanic field as examples. Once operational, RiskScape Volcano will be a valuable resource both in New Zealand and internationally as a practical tool for evaluating risk and also as an example for how to predict the consequences of volcanic eruptions on both rural and urban environments.

The risks of innovation in health care.

PubMed

Enzmann, Dieter R

2015-04-01

Innovation in health care creates risks that are unevenly distributed. An evolutionary analogy using species to represent business models helps categorize innovation experiments and their risks. This classification reveals two qualitative categories: early and late diversification experiments. Early diversification has prolific innovations with high risk because they encounter a "decimation" stage, during which most experiments disappear. Participants face high risk. The few decimation survivors can be sustaining or disruptive according to Christensen's criteria. Survivors enter late diversification, during which they again expand, but within a design range limited to variations of the previous surviving designs. Late diversifications carry lower risk. The exception is when disruptive survivors "diversify," which amplifies their disruption. Health care and radiology will experience both early and late diversifications, often simultaneously. Although oversimplifying Christensen's concepts, early diversifications are likely to deliver disruptive innovation, whereas late diversifications tend to produce sustaining innovations. Current health care consolidation is a manifestation of late diversification. Early diversifications will appear outside traditional care models and physical health care sites, as well as with new science such as molecular diagnostics. They warrant attention because decimation survivors will present both disruptive and sustaining opportunities to radiology. Radiology must participate in late diversification by incorporating sustaining innovations to its value chain. Given the likelihood of disruptive survivors, radiology should seriously consider disrupting itself rather than waiting for others to do so. Disruption entails significant modifications of its value chain, hence, its business model, for which lessons may become available from the pharmaceutical industry's current simultaneous experience with early and late diversifications. Copyright © 2015. Published by Elsevier Inc.

[Risk, uncertainty and ignorance in medicine].

PubMed

Rørtveit, G; Strand, R

2001-04-30

Exploration of healthy patients' risk factors for disease has become a major medical activity. The rationale behind primary prevention through exploration and therapeutic risk reduction is not separated from the theoretical assumption that every form of uncertainty can be expressed as risk. Distinguishing "risk" (as quantitative probabilities in a known sample space), "strict uncertainty" (when the sample space is known, but probabilities of events cannot be quantified) and "ignorance" (when the sample space is not fully known), a typical clinical situation (primary risk of coronary disease) is analysed. It is shown how strict uncertainty and sometimes ignorance can be present, in which case the orthodox decision theoretical rationale for treatment breaks down. For use in such cases, a different ideal model of rationality is proposed, focusing on the patient's considered reasons. This model has profound implications for the current understanding of medical professionalism as well as for the design of clinical guidelines.

Common-Cause Failure Treatment in Event Assessment: Basis for a Proposed New Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dana Kelly; Song-Hua Shen; Gary DeMoss

2010-06-01

Event assessment is an application of probabilistic risk assessment in which observed equipment failures and outages are mapped into the risk model to obtain a numerical estimate of the event’s risk significance. In this paper, we focus on retrospective assessments to estimate the risk significance of degraded conditions such as equipment failure accompanied by a deficiency in a process such as maintenance practices. In modeling such events, the basic events in the risk model that are associated with observed failures and other off-normal situations are typically configured to be failed, while those associated with observed successes and unchallenged components aremore » assumed capable of failing, typically with their baseline probabilities. This is referred to as the failure memory approach to event assessment. The conditioning of common-cause failure probabilities for the common cause component group associated with the observed component failure is particularly important, as it is insufficient to simply leave these probabilities at their baseline values, and doing so may result in a significant underestimate of risk significance for the event. Past work in this area has focused on the mathematics of the adjustment. In this paper, we review the Basic Parameter Model for common-cause failure, which underlies most current risk modelling, discuss the limitations of this model with respect to event assessment, and introduce a proposed new framework for common-cause failure, which uses a Bayesian network to model underlying causes of failure, and which has the potential to overcome the limitations of the Basic Parameter Model with respect to event assessment.« less

Preliminary Shuttle Space Suit Shielding Model. Chapter 9

NASA Technical Reports Server (NTRS)

Anderson, Brooke M.; Nealy, J. E.; Qualls, G. D.; Staritz, P. J.; Wilson, J. W.; Kim, M.-H. Y.; Cucinotta, F. A.; Atwell, W.; DeAngelis, G.; Ware, J.;

Methods and Techniques for Risk Prediction of Space Shuttle Upgrades

NASA Technical Reports Server (NTRS)

Hoffman, Chad R.; Pugh, Rich; Safie, Fayssal

1998-01-01

Since the Space Shuttle Accident in 1986, NASA has been trying to incorporate probabilistic risk assessment (PRA) in decisions concerning the Space Shuttle and other NASA projects. One major study NASA is currently conducting is in the PRA area in establishing an overall risk model for the Space Shuttle System. The model is intended to provide a tool to predict the Shuttle risk and to perform sensitivity analyses and trade studies including evaluation of upgrades. Marshall Space Flight Center (MSFC) and its prime contractors including Pratt and Whitney (P&W) are part of the NASA team conducting the PRA study. MSFC responsibility involves modeling the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). A major challenge that faced the PRA team is modeling the shuttle upgrades. This mainly includes the P&W High Pressure Fuel Turbopump (HPFTP) and the High Pressure Oxidizer Turbopump (HPOTP). The purpose of this paper is to discuss the various methods and techniques used for predicting the risk of the P&W redesigned HPFTP and HPOTP.

[Psychosocial stress and disease risks in occupational life. Results of international studies on the demand-control and the effort-reward imbalance models].

PubMed

Siegrist, J; Dragano, N

2008-03-01

Given the far-reaching changes of modern working life, psychosocial stress at work has received increased attention. Its influence on stress-related disease risks is analysed with the help of standardised measurements based on theoretical models. Two such models have gained special prominence in recent years, the demand-control model and the effort-reward imbalance model. The former model places its emphasis on a distinct combination of job characteristics, whereas the latter model's focus is on the imbalance between efforts spent and rewards received in turn. The predictive power of these models with respect to coronary or cardiovascular disease and depression was tested in a number of prospective epidemiological investigations. In summary, twofold elevated disease risks are observed. Effects on cardiovascular disease are particularly pronounced among men, whereas no gender differences are observed for depression. Additional evidence derived from experimental and ambulatory monitoring studies supplements this body of findings. Current scientific evidence justifies an increased awareness and assessment of these newly discovered occupational risks, in particular by occupational health professionals. Moreover, structural and interpersonal measures of stress prevention and health promotion at work are warranted, with special emphasis on gender differences.

Ecological Determinants of Highly Pathogenic Avian Influenza (H5N1) Outbreaks in Bangladesh

PubMed Central

Ahmed, Syed S. U.; Ersbøll, Annette K.; Biswas, Paritosh K.; Christensen, Jens P.; Hannan, Abu S. M. A.; Toft, Nils

2012-01-01

Background The agro-ecology and poultry husbandry of the south Asian and south-east Asian countries share common features, however, with noticeable differences. Hence, the ecological determinants associated with risk of highly pathogenic avian influenza (HPAI-H5N1) outbreaks are expected to differ between Bangladesh and e.g., Thailand and Vietnam. The primary aim of the current study was to establish ecological determinants associated with the risk of HPAI-H5N1 outbreaks at subdistrict level in Bangladesh. The secondary aim was to explore the performance of two different statistical modeling approaches for unmeasured spatially correlated variation. Methodology/Principal Findings An ecological study at subdistrict level in Bangladesh was performed with 138 subdistricts with HPAI-H5N1 outbreaks during 2007–2008, and 326 subdistricts with no outbreaks. The association between ecological determinants and HPAI-H5N1 outbreaks was examined using a generalized linear mixed model. Spatial clustering of the ecological data was modeled using 1) an intrinsic conditional autoregressive (ICAR) model at subdistrict level considering their first order neighbors, and 2) a multilevel (ML) model with subdistricts nested within districts. Ecological determinants significantly associated with risk of HPAI-H5N1 outbreaks at subdistrict level were migratory birds' staging areas, river network, household density, literacy rate, poultry density, live bird markets, and highway network. Predictive risk maps were derived based on the resulting models. The resulting models indicate that the ML model absorbed some of the covariate effect of the ICAR model because of the neighbor structure implied in the two different models. Conclusions/Significance The study identified a new set of ecological determinants related to river networks, migratory birds' staging areas and literacy rate in addition to already known risk factors, and clarified that the generalized concept of free grazing duck and duck-rice cultivation interacted ecology are not significant determinants for Bangladesh. These findings will refine current understanding of the HPAI-H5N1 epidemiology in Bangladesh. PMID:22470496

Using incident response trees as a tool for risk management of online financial services.

PubMed

Gorton, Dan

2014-09-01

The article introduces the use of probabilistic risk assessment for modeling the incident response process of online financial services. The main contribution is the creation of incident response trees, using event tree analysis, which provides us with a visual tool and a systematic way to estimate the probability of a successful incident response process against the currently known risk landscape, making it possible to measure the balance between front-end and back-end security measures. The model is presented using an illustrative example, and is then applied to the incident response process of a Swedish bank. Access to relevant data is verified and the applicability and usability of the proposed model is verified using one year of historical data. Potential advantages and possible shortcomings are discussed, referring to both the design phase and the operational phase, and future work is presented. © 2014 Society for Risk Analysis.

Uncertainty quantification and validation of combined hydrological and macroeconomic analyses.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez, Jacquelynne; Parks, Mancel Jordan; Jennings, Barbara Joan

2010-09-01

Changes in climate can lead to instabilities in physical and economic systems, particularly in regions with marginal resources. Global climate models indicate increasing global mean temperatures over the decades to come and uncertainty in the local to national impacts means perceived risks will drive planning decisions. Agent-based models provide one of the few ways to evaluate the potential changes in behavior in coupled social-physical systems and to quantify and compare risks. The current generation of climate impact analyses provides estimates of the economic cost of climate change for a limited set of climate scenarios that account for a small subsetmore » of the dynamics and uncertainties. To better understand the risk to national security, the next generation of risk assessment models must represent global stresses, population vulnerability to those stresses, and the uncertainty in population responses and outcomes that could have a significant impact on U.S. national security.« less

Prediction Models for 30-Day Mortality and Complications After Total Knee and Hip Arthroplasties for Veteran Health Administration Patients With Osteoarthritis.

PubMed

Harris, Alex Hs; Kuo, Alfred C; Bowe, Thomas; Gupta, Shalini; Nordin, David; Giori, Nicholas J

2018-05-01

Statistical models to preoperatively predict patients' risk of death and major complications after total joint arthroplasty (TJA) could improve the quality of preoperative management and informed consent. Although risk models for TJA exist, they have limitations including poor transparency and/or unknown or poor performance. Thus, it is currently impossible to know how well currently available models predict short-term complications after TJA, or if newly developed models are more accurate. We sought to develop and conduct cross-validation of predictive risk models, and report details and performance metrics as benchmarks. Over 90 preoperative variables were used as candidate predictors of death and major complications within 30 days for Veterans Health Administration patients with osteoarthritis who underwent TJA. Data were split into 3 samples-for selection of model tuning parameters, model development, and cross-validation. C-indexes (discrimination) and calibration plots were produced. A total of 70,569 patients diagnosed with osteoarthritis who received primary TJA were included. C-statistics and bootstrapped confidence intervals for the cross-validation of the boosted regression models were highest for cardiac complications (0.75; 0.71-0.79) and 30-day mortality (0.73; 0.66-0.79) and lowest for deep vein thrombosis (0.59; 0.55-0.64) and return to the operating room (0.60; 0.57-0.63). Moderately accurate predictive models of 30-day mortality and cardiac complications after TJA in Veterans Health Administration patients were developed and internally cross-validated. By reporting model coefficients and performance metrics, other model developers can test these models on new samples and have a procedure and indication-specific benchmark to surpass. Published by Elsevier Inc.

Gut Microbiome Associates With Lifetime Cardiovascular Disease Risk Profile Among Bogalusa Heart Study Participants

PubMed Central

Kelly, Tanika N.; Bazzano, Lydia A.; Ajami, Nadim J.; He, Hua; Zhao, Jinying; Petrosino, Joseph F.; Correa, Adolfo; He, Jiang

2016-01-01

Rationale Few studies have systematically assessed the influence of gut microbiota on cardiovascular disease (CVD) risk. Objective To examine the association between gut microbiota and lifetime CVD risk profile among 55 Bogalusa Heart Study (BHS) participants with the highest and 57 with the lowest lifetime burdens of CVD risk factors. Methods and Results 16S rRNA sequencing was conducted on microbial DNA extracted from stool samples of the BHS participants. Alpha diversity, including measures of richness and evenness, and individual genera were tested for associations with lifetime CVD risk profile. Multivariable regression techniques were employed to adjust for age, gender, and race (Model 1), along with body mass index (BMI) (Model 2) and both BMI and diet (Model 3). In Model 1, odds ratios (95% confidence intervals) for each standard deviation increase in richness, measured by the number of observed operational taxonomic units, Chao 1 index, and abundance-based coverage estimator, were 0.62 (0.39, 0.99), 0.61 (0.38, 0.98), and 0.63 (0.39, 0.99), respectively. Associations were consistent in Models 2 and 3. Four genera were enriched among those with high versus low CVD risk profile in all models. Model 1 p-values were: 2.12×10−3, 7.95×10−5, 4.39×10−4, and 1.51×10−4 for Prevotella 2, Prevotella 7, Tyzzerella and Tyzzerella 4, respectively. Two genera were depleted among those with high versus low CVD risk profile in all models. Model 1 P-values were: 2.96×10−6 and 1.82×10−4 for Alloprevotella and Catenibacterium, respectively. Conclusions The current study identified associations of overall microbial richness and six microbial genera with lifetime CVD risk. PMID:27507222

Gut Microbiome Associates With Lifetime Cardiovascular Disease Risk Profile Among Bogalusa Heart Study Participants.

PubMed

Kelly, Tanika N; Bazzano, Lydia A; Ajami, Nadim J; He, Hua; Zhao, Jinying; Petrosino, Joseph F; Correa, Adolfo; He, Jiang

2016-09-30

Few studies have systematically assessed the influence of gut microbiota on cardiovascular disease (CVD) risk. To examine the association between gut microbiota and lifetime CVD risk profile among 55 Bogalusa Heart Study participants with the highest and 57 with the lowest lifetime burdens of CVD risk factors. 16S ribosomal RNA sequencing was conducted on microbial DNA extracted from stool samples of the Bogalusa Heart Study participants. α Diversity, including measures of richness and evenness, and individual genera were tested for associations with lifetime CVD risk profile. Multivariable regression techniques were used to adjust for age, sex, and race (model 1), along with body mass index (model 2) and both body mass index and diet (model 3). In model 1, odds ratios (95% confidence intervals) for each SD increase in richness, measured by the number of observed operational taxonomic units, Chao 1 index, and abundance-based coverage estimator, were 0.62 (0.39-0.99), 0.61 (0.38-0.98), and 0.63 (0.39-0.99), respectively. Associations were consistent in models 2 and 3. Four genera were enriched among those with high versus low CVD risk profile in all models. Model 1 P values were 2.12×10(-3), 7.95×10(-5), 4.39×10(-4), and 1.51×10(-4) for Prevotella 2, Prevotella 7, Tyzzerella, and Tyzzerella 4, respectively. Two genera were depleted among those with high versus low CVD risk profile in all models. Model 1 P values were 2.96×10(-6) and 1.82×10(-4) for Alloprevotella and Catenibacterium, respectively. The current study identified associations of overall microbial richness and 6 microbial genera with lifetime CVD risk. © 2016 American Heart Association, Inc.

Aporrectodea caliginosa, a relevant earthworm species for a posteriori pesticide risk assessment: current knowledge and recommendations for culture and experimental design.

PubMed

Bart, Sylvain; Amossé, Joël; Lowe, Christopher N; Mougin, Christian; Péry, Alexandre R R; Pelosi, Céline

2018-06-21

Ecotoxicological tests with earthworms are widely used and are mandatory for the risk assessment of pesticides prior to registration and commercial use. The current model species for standardized tests is Eisenia fetida or Eisenia andrei. However, these species are absent from agricultural soils and often less sensitive to pesticides than other earthworm species found in mineral soils. To move towards a better assessment of pesticide effects on non-target organisms, there is a need to perform a posteriori tests using relevant species. The endogeic species Aporrectodea caliginosa (Savigny, 1826) is representative of cultivated fields in temperate regions and is suggested as a relevant model test species. After providing information on its taxonomy, biology, and ecology, we reviewed current knowledge concerning its sensitivity towards pesticides. Moreover, we highlighted research gaps and promising perspectives. Finally, advice and recommendations are given for the establishment of laboratory cultures and experiments using this soil-dwelling earthworm species.

Near Earth Asteroid Characterization for Threat Assessment

NASA Technical Reports Server (NTRS)

Dotson, Jessie; Mathias, Donovan; Wheeler, Lorien; Wooden, Diane; Bryson, Kathryn; Ostrowski, Daniel

2017-01-01

Physical characteristics of NEAs are an essential input to modeling behavior during atmospheric entry and to assess the risk of impact but determining these properties requires a non-trivial investment of time and resources. The characteristics relevant to these models include size, density, strength and ablation coefficient. Some of these characteristics cannot be directly measured, but rather must be inferred from related measurements of asteroids and/or meteorites. Furthermore, for the majority of NEAs, only the basic measurements exist so often properties must be inferred from statistics of the population of more completely characterized objects. The Asteroid Threat Assessment Project at NASA Ames Research Center has developed a probabilistic asteroid impact risk (PAIR) model in order to assess the risk of asteroid impact. Our PAIR model and its use to develop probability distributions of impact risk are discussed in other contributions to PDC 2017 (e.g., Mathias et al.). Here we utilize PAIR to investigate which NEA characteristics are important for assessing the impact threat by investigating how changes in these characteristics alter the damage predicted by PAIR. We will also provide an assessment of the current state of knowledge of the NEA characteristics of importance for asteroid threat assessment. The relative importance of different properties as identified using PAIR will be combined with our assessment of the current state of knowledge to identify potential high impact investigations. In addition, we will discuss an ongoing effort to collate the existing measurements of NEA properties of interest to the planetary defense community into a readily accessible database.

Risk assessment of nitrate transport through subsurface layers and groundwater using experimental and modeling approach.

PubMed

Alslaibi, Tamer M; Abunada, Ziyad; Abu Amr, Salem S; Abustan, Ismail

2017-09-22

Landfills are one of the main point sources of groundwater pollution. This research mainly aims to assess the risk of nitrate [Formula: see text] transport from the unlined landfill to subsurface layers and groundwater using experimental results and the SESOIL model. Samples from 12 groundwater wells downstream of the landfill were collected and analyzed in 2008, 21 years after the landfill construction. The average [Formula: see text] concentration in the wells was 54 mg/L, slightly higher than the World Health Organization ([Formula: see text] 50 mg/L) standards. SESOIL model was used to predict the [Formula: see text] concentration at the bottom of the unsaturated zone. Results indicated that the current mean [Formula: see text] concentration at the bottom of the unsaturated zone is 75 mg/L. the model predicted that the level of NO 3 will increased up to 325 mg/L within 30 years. Accordingly, the [Formula: see text] concentration in groundwater wells near the landfill area is expected to gradually increase with time. Although the current risk associated with the [Formula: see text] level might not be harm to adults, however, it might pose severe risks to both adults and infants in the near future due to [Formula: see text] leaching. Urgent mitigation measures such as final cell cover (cap), lining system and vertical expansion should be considered at the landfill to protect the public health in the area.

Exogenous and endogenous hormones and breast cancer

PubMed Central

ChenMD, Wendy Y.

2008-01-01

Exposure to higher levels of both exogenous and endogenous hormone is associated with breast cancer risk. Because of the association between breast cancer and HRT, only the minimal duration of HRT use is recommended for symptom control, and it is not recommended for chronic disease management. Current research issues include the role of progestins, other types of HRT, duration of unopposed estrogen use, and characteristics of cancers that develop on HRT. Circulating sex steroid levels are associated with breast cancer risk, but multiple issues need to be addressed before they are used routinely in clinical practice. Current research issues include measurement of levels for routine clinical practice, integration with standard breast cancer risk models and genetic polymorphism data, and applicability to estrogen-receptor-negative cancers. PMID:18971119

Multimethod Prediction of Physical Parent-Child Aggression Risk in Expectant Mothers and Fathers with Social Information Processing Theory

PubMed Central

Rodriguez, Christina M.; Smith, Tamika L.; Silvia, Paul J.

2015-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants’ own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. PMID:26631420

A hybrid land-water-environment model for identification of ecological effect and risk under uncertain meteorological precipitation in an agroforestry ecosystem.

PubMed

Zeng, Xueting; Li, Tienan; Chen, Cong; Si, Zhenjiang; Huang, Guohe; Guo, Ping; Zhuang, Xiaowen

2018-08-15

In this study, a hybrid land-water-environment (LWE) model is developed for identifying ecological effect and risk under uncertain precipitation in an agroforestry ecosystem. A simulation-based fuzzy-stochastic programming with risk analysis (SFSR) method is used into LWE model to reflect the meteorological impacts; meanwhile, it also can quantify artificial fuzziness (e.g., risk attitude of policymaker) and natural vagueness (e.g., ecological function) in decision-making. The developed LWE model with SFSR method is applied to a practical agroforestry ecosystem in China. Results of optimized planting scale, irrigative water schedule, pollution mitigation scheme, and system benefit under changed rainfall, precise risk-adoption and vague ecological function are obtained; meanwhile their corresponding ecological effects and risks are analyzed. It found that current LWE plans could generate massive water deficits (e.g., 23.22×10 6 m 3 in crop irrigation and 26.32×10 6 m 3 in forest protection at highest) due to over-cultivation and excessive pollution discharges (e.g., the highest excessive TP and TN discharges would reach 460.64 and 15.30×10 3 ton) due to irrational fertilization, which would increase regional ecological risks. In addition, fifteen scenarios associated with withdrawing cultivation and recovering forest based on regional environment heterogeneity (such as soil types) have been discussed to adjust current agriculture-environment policies. It found that, the excessive pollution discharges (TN and TP) could be reduced 12.95% and 18.32% at highest through ecological expansions, which would generate higher system benefits than that without withdrawing farmland and recovering forest. All above can facilitate local policymakers to modulate a comprehensive LWE with more sustainable and robust manners, achieving regional harmony between socio-economy and eco-environment. Copyright © 2018 Elsevier B.V. All rights reserved.

Estimates of the Public Health Impact of a Pediatric Vaccination Program Using an Intranasal Tetravalent Live-Attenuated Influenza Vaccine in Belgium.

PubMed

Gerlier, Laetitia; Lamotte, Mark; Dos Santos Mendes, Sofia; Damm, Oliver; Schwehm, Markus; Eichner, Martin

2016-08-01

Our objectives were to estimate the public health outcomes of vaccinating Belgian children using an intranasal tetravalent live-attenuated influenza vaccine (QLAIV) combined with current coverage of high-risk/elderly individuals using the trivalent inactivated vaccine. We used a deterministic, age-structured, dynamic model to simulate seasonal influenza transmission in the Belgian population under the current coverage or after extending vaccination with QLAIV to healthy children aged 2-17 years. Differential equations describe demographic changes, exposure to infectious individuals, infection recovery, and immunity dynamics. The basic reproduction number (R 0) was calibrated to the observed number of influenza doctor visits/year. Vaccine efficacy was 80 % (live-attenuated) and 59-68 % (inactivated). The 10-year incidence of symptomatic influenza was calculated with different coverage scenarios (add-on to current coverage). Model calibration yielded R 0 = 1.1. QLAIV coverage of 75 % of those aged 2-17 years averted 374,000 symptomatic cases/year (57 % of the current number), 244,000 of which were among adults (indirect effect). Vaccinating 75 % of those aged 2-11 years and 50 % of those aged 12-17 years averted 333,200 cases/year (213,000 adult cases/year). Vaccinating only healthy children aged 2-5 years generated direct protection but limited indirect protection, even with 90 % coverage (40,800 averted adult cases/year; -8.4 %). Targeting all children averted twice as many high-risk cases as targeting high-risk children only (8485 vs. 4965/year with 75 % coverage). Sensitivity analyses showed the robustness of results. The model highlights the direct and indirect protection benefits when vaccinating healthy children with QLAIV in Belgium. Policies targeting only high-risk individuals or the youngest provide limited herd protection, as school-age children are important influenza vectors in the community.

Human Injury Criteria for Underwater Blasts

PubMed Central

Lance, Rachel M.; Capehart, Bruce; Kadro, Omar; Bass, Cameron R.

2015-01-01

Underwater blasts propagate further and injure more readily than equivalent air blasts. Development of effective personal protection and countermeasures, however, requires knowledge of the currently unknown human tolerance to underwater blast. Current guidelines for prevention of underwater blast injury are not based on any organized injury risk assessment, human data or experimental data. The goal of this study was to derive injury risk assessments for underwater blast using well-characterized human underwater blast exposures in the open literature. The human injury dataset was compiled using 34 case reports on underwater blast exposure to 475 personnel, dating as early as 1916. Using severity ratings, computational reconstructions of the blasts, and survival information from a final set of 262 human exposures, injury risk models were developed for both injury severity and risk of fatality as functions of blast impulse and blast peak overpressure. Based on these human data, we found that the 50% risk of fatality from underwater blast occurred at 302±16 kPa-ms impulse. Conservatively, there is a 20% risk of pulmonary injury at a kilometer from a 20 kg charge. From a clinical point of view, this new injury risk model emphasizes the large distances possible for potential pulmonary and gut injuries in water compared with air. This risk value is the first impulse-based fatality risk calculated from human data. The large-scale inconsistency between the blast exposures in the case reports and the guidelines available in the literature prior to this study further underscored the need for this new guideline derived from the unique dataset of actual injuries in this study. PMID:26606655

Linking adverse outcome pathways and population models: Current state of the science and future directions

EPA Science Inventory

Analysis of population impacts of chemical stressors through the use of modeling provides a linkage between endpoints observed in the individual and ecological risk to the population as a whole. In this presentation, we describe the evolution of an approach developed in our labor...

Temperament Pathways to Childhood Disruptive Behavior and Adolescent Substance Abuse: Testing a Cascade Model

ERIC Educational Resources Information Center

Martel, Michelle M.; Pierce, Laura; Nigg, Joel T.; Jester, Jennifer M.; Adams, Kenneth; Puttler, Leon I.; Buu, Anne; Fitzgerald, Hiram; Zucker, Robert A.

2009-01-01

Temperament traits may increase risk for developmental psychopathology like Attention-Deficit/Hyperactivity Disorder (ADHD) and disruptive behaviors during childhood, as well as predisposing to substance abuse during adolescence. In the current study, a cascade model of trait pathways to adolescent substance abuse was examined. Component…

DEVELOPMENT OF A MICROSCALE EMISSION FACTOR MODEL FOR PARTICULATE MATTER (MICROFACPM) FOR PREDICTING REAL TIME MOTOR VEHICLE EMISSIONS

EPA Science Inventory

Health risk evaluation needs precise measurement and modeling of human exposures in microenvironments to support review of current air quality standards. The particulate matter emissions from motor vehicles are a major component of human exposures in urban microenvironments. Cu...

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

NASA Technical Reports Server (NTRS)

Guarro, Sergio B.

2010-01-01

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.

Climate Change Could Increase the Geographic Extent of Hendra Virus Spillover Risk.

PubMed

Martin, Gerardo; Yanez-Arenas, Carlos; Chen, Carla; Plowright, Raina K; Webb, Rebecca J; Skerratt, Lee F

2018-03-19

Disease risk mapping is important for predicting and mitigating impacts of bat-borne viruses, including Hendra virus (Paramyxoviridae:Henipavirus), that can spillover to domestic animals and thence to humans. We produced two models to estimate areas at potential risk of HeV spillover explained by the climatic suitability for its flying fox reservoir hosts, Pteropus alecto and P. conspicillatus. We included additional climatic variables that might affect spillover risk through other biological processes (such as bat or horse behaviour, plant phenology and bat foraging habitat). Models were fit with a Poisson point process model and a log-Gaussian Cox process. In response to climate change, risk expanded southwards due to an expansion of P. alecto suitable habitat, which increased the number of horses at risk by 175-260% (110,000-165,000). In the northern limits of the current distribution, spillover risk was highly uncertain because of model extrapolation to novel climatic conditions. The extent of areas at risk of spillover from P. conspicillatus was predicted shrink. Due to a likely expansion of P. alecto into these areas, it could replace P. conspicillatus as the main HeV reservoir. We recommend: (1) HeV monitoring in bats, (2) enhancing HeV prevention in horses in areas predicted to be at risk, (3) investigate and develop mitigation strategies for areas that could experience reservoir host replacements.

Mapping risk of avian influenza transmission at the interface of domestic poultry and wild birds

USGS Publications Warehouse

Prosser, Diann J.; Hungerford, Laura L.; Erwin, R. Michael; Ottinger, Mary Ann; Takekawa, John Y.; Ellis, Erle C.

2013-01-01

Emergence of avian influenza viruses with high lethality to humans, such as the currently circulating highly pathogenic A(H5N1) (emerged in 1996) and A(H7N9) cause serious concern for the global economic and public health sectors. Understanding the spatial and temporal interface between wild and domestic populations, from which these viruses emerge, is fundamental to taking action. This information, however, is rarely considered in influenza risk models, partly due to a lack of data. We aim to identify areas of high transmission risk between domestic poultry and wild waterfowl in China, the epicenter of both viruses. Two levels of models were developed: one that predicts hotspots of novel virus emergence between domestic and wild birds, and one that incorporates H5N1 risk factors, for which input data exists. Models were produced at 1 and 30 km spatial resolution, and two temporal seasons. Patterns of risk varied between seasons with higher risk in the northeast, central-east, and western regions of China during spring and summer, and in the central and southeastern regions during winter. Monte-Carlo uncertainty analyses indicated varying levels of model confidence, with lowest errors in the densely populated regions of eastern and southern China. Applications and limitations of the models are discussed within.

An emerging epidemic: cancer and heart failure.

PubMed

Thavendiranathan, Paaladinesh; Nolan, Mark T

2017-01-01

Heart disease and cancer are the two leading causes of mortality globally. Cardiovascular complications of cancer therapy significantly contribute to the global burden of cardiovascular disease. Heart failure (HF) in particular is a relatively common and life-threatening complication. The increased risk is driven by the shared risk factors for cancer and HF, the direct impact of cancer therapy on the heart, an existing care gap in the cardiac care of patients with cancer and the increasing population of adult cancer survivors. The clear relationship between cancer treatment initiation and the potential for myocardial injury makes this population attractive for prevention strategies, targeted cardiovascular monitoring and treatment. However, there is currently no consensus on the optimal strategy for managing this at-risk population. Uniform treatment using cardioprotective medications may reduce the incidence of HF, but would impose frequently unnecessary and burdensome side effects. Ideally we could use validated risk-prediction models to target HF-preventive strategies, but currently no such models exist. In the present review, we focus on evidence and rationales for contemporary clinical decision-making in this novel field and discuss issues, including the burden of HF in patients with cancer, the reasons for the elevated risk and potential prevention strategies. © 2016 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.

Rates and Covariates of Recent Sexual and Physical Violence Against HIV-Infected Outpatient Drinkers in Western Kenya.

PubMed

Papas, Rebecca K; Gakinya, Benson N; Mwaniki, Michael M; Lee, Hana; Kiarie, Stella W; Martino, Steve; Loxley, Michelle P; Keter, Alfred K; Klein, Debra A; Sidle, John E; Baliddawa, Joyce B; Maisto, Stephen A

2017-08-01

Victimization from physical and sexual violence presents global health challenges. Partner violence is higher in Kenya than Africa. Violence against drinkers and HIV-infected individuals is typically elevated, so dual vulnerabilities may further augment risk. Understanding violence risks can improve interventions. Participants were 614 HIV-infected outpatient drinkers in western Kenya enrolled in a randomized trial to reduce alcohol use. At baseline, past 90-day partner physical and sexual violence were examined descriptively and in gender-stratified regression models. We hypothesized higher reported violence against women than men, and positive violence association with HIV stigma and alcohol use across gender. Women reported significantly more current sexual (26.3 vs. 5.7%) and physical (38.9 vs. 24.8%) victimization than men. Rates were generally higher than Kenyan lifetime national averages. In both regression models, HIV stigma and alcohol-related sexual expectations were significantly associated with violence while alcohol use was not. For women, higher violence risk was also conferred by childhood violence, past-year transactional sex, and younger age. HIV-infected Kenyan drinkers, particularly women, endorse high current violence due to multiple risk factors. Findings have implications for HIV interventions. Longitudinal research is needed to understand development of risk.

Evaluating nonindigenous species management in a Bayesian networks derived relative risk framework for Padilla Bay, WA, USA.

PubMed

Herring, Carlie E; Stinson, Jonah; Landis, Wayne G

2015-10-01

Many coastal regions are encountering issues with the spread of nonindigenous species (NIS). In this study, we conducted a regional risk assessment using a Bayesian network relative risk model (BN-RRM) to analyze multiple vectors of NIS introductions to Padilla Bay, Washington, a National Estuarine Research Reserve. We had 3 objectives in this study. The 1st objective was to determine whether the BN-RRM could be used to calculate risk from NIS introductions for Padilla Bay. Our 2nd objective was to determine which regions and endpoints were at greatest risk from NIS introductions. Our 3rd objective was to incorporate a management option into the model and predict endpoint risk if it were to be implemented. Eradication can occur at different stages of NIS invasions, such as the elimination of these species before being introduced to the habitat or removal of the species after settlement. We incorporated the ballast water treatment management scenario into the model, observed the risk to the endpoints, and compared this risk with the initial risk estimates. The model results indicated that the southern portion of the bay was at greatest risk because of NIS. Changes in community composition, Dungeness crab, and eelgrass were the endpoints most at risk from NIS introductions. The currents node, which controls the exposure of NIS to the bay from the surrounding marine environment, was the parameter that had the greatest influence on risk. The ballast water management scenario displayed an approximate 1% reduction in risk in this Padilla Bay case study. The models we developed provide an adaptable template for decision makers interested in managing NIS in other coastal regions and large bodies of water. © 2015 SETAC.

Potential Technologies for Assessing Risk Associated with a Mesoscale Forecast

DTIC Science & Technology

2015-10-01

American GFS models, and informally applied on the Weather Research and Forecasting ( WRF ) model. The current CI equation is as follows...Reen B, Penc R. Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) model using a Geographic Information System (GIS). J...Forecast model ( WRF -ARW) with extensions that might include finer terrain resolutions and more detailed representations of the underlying atmospheric

Personality and the Leading Behavioral Contributors of Mortality

PubMed Central

Turiano, Nicholas A.; Chapman, Benjamin P.; Gruenewald, Tara L.; Mroczek, Daniel K.

2014-01-01

Objective Personality traits predict both health behaviors and mortality risk across the life course. However, there are few investigations that have examined these effects in a single study. Thus, there are limitations in assessing if health behaviors explain why personality predicts health and longevity. Method Utilizing 14-year mortality data from a national sample of over 6,000 adults from the Midlife in the United States Study, we tested whether alcohol use, smoking behavior, and waist circumference mediated the personality–mortality association. Results After adjusting for demographic variables, higher levels of Conscientiousness predicted a 13% reduction in mortality risk over the follow-up. Structural equation models provided evidence that heavy drinking, smoking, and greater waist circumference significantly mediated the Conscientiousness–mortality association by 42%. Conclusion The current study provided empirical support for the health-behavior model of personality— Conscientiousness influences the behaviors persons engage in and these behaviors affect the likelihood of poor health outcomes. Findings highlight the usefulness of assessing mediation in a structural equation modeling framework when testing proportional hazards. In addition, the current findings add to the growing literature that personality traits can be used to identify those at risk for engaging in behaviors that deteriorate health and shorten the life span. PMID:24364374

Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

PubMed Central

Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

2016-01-01

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

Improving measurement of injection drug risk behavior using item response theory.

PubMed

Janulis, Patrick

2014-03-01

Recent research highlights the multiple steps to preparing and injecting drugs and the resultant viral threats faced by drug users. This research suggests that more sensitive measurement of injection drug HIV risk behavior is required. In addition, growing evidence suggests there are gender differences in injection risk behavior. However, the potential for differential item functioning between genders has not been explored. To explore item response theory as an improved measurement modeling technique that provides empirically justified scaling of injection risk behavior and to examine for potential gender-based differential item functioning. Data is used from three studies in the National Institute on Drug Abuse's Criminal Justice Drug Abuse Treatment Studies. A two-parameter item response theory model was used to scale injection risk behavior and logistic regression was used to examine for differential item functioning. Item fit statistics suggest that item response theory can be used to scale injection risk behavior and these models can provide more sensitive estimates of risk behavior. Additionally, gender-based differential item functioning is present in the current data. Improved measurement of injection risk behavior using item response theory should be encouraged as these models provide increased congruence between construct measurement and the complexity of injection-related HIV risk. Suggestions are made to further improve injection risk behavior measurement. Furthermore, results suggest direct comparisons of composite scores between males and females may be misleading and future work should account for differential item functioning before comparing levels of injection risk behavior.

Using the CAUSE Model to Understand Public Communication about Water Risks: Perspectives from Texas Groundwater District Officials on Drought and Availability.

PubMed

VanDyke, Matthew S; King, Andy J

2017-12-05

Public communication about drought and water availability risks poses challenges to a potentially disinterested public. Water management professionals, though, have a responsibility to work with the public to engage in communication about water and environmental risks. Because limited research in water management examines organizational communication practices and perceptions, insights into research and practice can be gained through investigation of current applications of these risk communication efforts. Guided by the CAUSE model, which explains common goals in communicating risk information to the public (e.g., creating Confidence, generating Awareness, enhancing Understanding, gaining Satisfaction, and motivating Enactment), semistructured interviews of professionals (N = 25) employed by Texas groundwater conservation districts were conducted. The interviews examined how CAUSE model considerations factor in to communication about drought and water availability risks. These data suggest that many work to build constituents' confidence in their districts. Although audiences and constituents living in drought-prone areas were reported as being engaged with water availability risks and solutions, many district officials noted constituents' lack of perceived risk and engagement. Some managers also indicated that public understanding was a secondary concern of their primary responsibilities and that the public often seemed apathetic about technical details related to water conservation risks. Overall, results suggest complicated dynamics between officials and the public regarding information access and motivation. The article also outlines extensions of the CAUSE model and implications for improving public communication about drought and water availability risks. © 2017 Society for Risk Analysis.

Bayesian Power Prior Analysis and Its Application to Operational Risk and Rasch Model

ERIC Educational Resources Information Center

Zhang, Honglian

2010-01-01

When sample size is small, informative priors can be valuable in increasing the precision of estimates. Pooling historical data and current data with equal weights under the assumption that both of them are from the same population may be misleading when heterogeneity exists between historical data and current data. This is particularly true when…

NASA Space Radiation Protection Strategies: Risk Assessment and Permissible Exposure Limits

NASA Technical Reports Server (NTRS)

Huff, J. L.; Patel, Z. S.; Simonsen, L. C.

2017-01-01

Permissible exposure limits (PELs) for short-term and career astronaut exposures to space radiation have been set and approved by NASA with the goal of protecting astronauts against health risks associated with ionizing radiation exposure. Short term PELs are intended to prevent clinically significant deterministic health effects, including performance decrements, which could threaten astronaut health and jeopardize mission success. Career PELs are implemented to control late occurring health effects, including a 3% risk of exposure induced death (REID) from cancer, and dose limits are used to prevent cardiovascular and central nervous system diseases. For radiation protection, meeting the cancer PEL is currently the design driver for galactic cosmic ray and solar particle event shielding, mission duration, and crew certification (e.g., 1-year ISS missions). The risk of cancer development is the largest known long-term health consequence following radiation exposure, and current estimates for long-term health risks due to cardiovascular diseases are approximately 30% to 40% of the cancer risk for exposures above an estimated threshold (Deep Space one-year and Mars missions). Large uncertainties currently exist in estimating the health risks of space radiation exposure. Improved understanding through radiobiology and physics research allows increased accuracy in risk estimation and is essential for ensuring astronaut health as well as for controlling mission costs, optimization of mission operations, vehicle design, and countermeasure assessment. We will review the Space Radiation Program Element's research strategies to increase accuracy in risk models and to inform development and validation of the permissible exposure limits.

Risk model for estimating the 1-year risk of deferred lesion intervention following deferred revascularization after fractional flow reserve assessment.

PubMed

Depta, Jeremiah P; Patel, Jayendrakumar S; Novak, Eric; Gage, Brian F; Masrani, Shriti K; Raymer, David; Facey, Gabrielle; Patel, Yogesh; Zajarias, Alan; Lasala, John M; Amin, Amit P; Kurz, Howard I; Singh, Jasvindar; Bach, Richard G

2015-02-21

Although lesions deferred revascularization following fractional flow reserve (FFR) assessment have a low risk of adverse cardiac events, variability in risk for deferred lesion intervention (DLI) has not been previously evaluated. The aim of this study was to develop a prediction model to estimate 1-year risk of DLI for coronary lesions where revascularization was not performed following FFR assessment. A prediction model for DLI was developed from a cohort of 721 patients with 882 coronary lesions where revascularization was deferred based on FFR between 10/2002 and 7/2010. Deferred lesion intervention was defined as any revascularization of a lesion previously deferred following FFR. The final DLI model was developed using stepwise Cox regression and validated using bootstrapping techniques. An algorithm was constructed to predict the 1-year risk of DLI. During a mean (±SD) follow-up period of 4.0 ± 2.3 years, 18% of lesions deferred after FFR underwent DLI; the 1-year incidence of DLI was 5.3%, while the predicted risk of DLI varied from 1 to 40%. The final Cox model included the FFR value, age, current or former smoking, history of coronary artery disease (CAD) or prior percutaneous coronary intervention, multi-vessel CAD, and serum creatinine. The c statistic for the DLI prediction model was 0.66 (95% confidence interval, CI: 0.61-0.70). Patients deferred revascularization based on FFR have variation in their risk for DLI. A clinical prediction model consisting of five clinical variables and the FFR value can help predict the risk of DLI in the first year following FFR assessment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2014. For permissions please email: journals.permissions@oup.com.

Predictive Modeling of Risk Factors and Complications of Cataract Surgery

PubMed Central

Gaskin, Gregory L; Pershing, Suzann; Cole, Tyler S; Shah, Nigam H

2016-01-01

Purpose To quantify the relationship between aggregated preoperative risk factors and cataract surgery complications, as well as to build a model predicting outcomes on an individual-level—given a constellation of demographic, baseline, preoperative, and intraoperative patient characteristics. Setting Stanford Hospital and Clinics between 1994 and 2013. Design Retrospective cohort study Methods Patients age 40 or older who received cataract surgery between 1994 and 2013. Risk factors, complications, and demographic information were extracted from the Electronic Health Record (EHR), based on International Classification of Diseases, 9th edition (ICD-9) codes, Current Procedural Terminology (CPT) codes, drug prescription information, and text data mining using natural language processing. We used a bootstrapped least absolute shrinkage and selection operator (LASSO) model to identify highly-predictive variables. We built random forest classifiers for each complication to create predictive models. Results Our data corroborated existing literature on postoperative complications—including the association of intraoperative complications, complex cataract surgery, black race, and/or prior eye surgery with an increased risk of any postoperative complications. We also found a number of other, less well-described risk factors, including systemic diabetes mellitus, young age (<60 years old), and hyperopia as risk factors for complex cataract surgery and intra- and post-operative complications. Our predictive models based on aggregated outperformed existing published models. Conclusions The constellations of risk factors and complications described here can guide new avenues of research and provide specific, personalized risk assessment for a patient considering cataract surgery. The predictive capacity of our models can enable risk stratification of patients, which has utility as a teaching tool as well as informing quality/value-based reimbursements. PMID:26692059

Personalized medicine in psychiatry.

PubMed

Wium-Andersen, Ida Kim; Vinberg, Maj; Kessing, Lars Vedel; McIntyre, Roger S

2017-01-01

Personalized medicine is a model in which a patient's unique clinical, genetic, and environmental characteristics are the basis for treatment and prevention. Aim, method, and results: This review aims to describe the current tools, phenomenological features, clinical risk factors, and biomarkers used to provide personalized medicine. Furthermore, this study describes the target areas in which they can be applied including diagnostics, treatment selection and response, assessment of risk of side-effects, and prevention. Personalized medicine in psychiatry is challenged by the current taxonomy, where the diagnostic categories are broad and great biological heterogeneity exists within each category. There is, thus, a gap between the current advanced research prospects and clinical practice, and the current taxonomy is, thus, a poor basis for biological research. The discussion proposes possible solutions to narrow this gap and to move psychiatric research forward towards personalized medicine.

Mapping for prevention: GIS models for directing childhood lead poisoning prevention programs.

PubMed Central

Miranda, Marie Lynn; Dolinoy, Dana C; Overstreet, M Alicia

2002-01-01

Environmental threats to children's health--especially low-level lead exposure--are complex and multifaceted; consequently, mitigation of these threats has proven costly and insufficient and has produced economic and racial disparities in exposure among populations. Policy makers, public health officials, child advocates, and others currently lack the appropriate infrastructure to evaluate children's risk and exposure potential across a broad range of risks. Unable to identify where the highest risk of exposure occurs, children's environmental health programs remain mitigative instead of preventive. In this article we use geographic information system spatial analysis of data from blood lead screening, county tax assessors, and the U.S. Census to predict statistically based lead exposure risk levels mapped at the individual tax parcel unit in six counties in North Carolina. The resulting model uses weighted risk factors to spatially locate modeled exposure zones, thus highlighting critical areas for targeted intervention. The methods presented here hold promise for application and extension to the other 94 North Carolina counties and nationally, as well as to other environmental health risks. PMID:12204831

Risk maps for navigation in liver surgery

NASA Astrophysics Data System (ADS)

Hansen, C.; Zidowitz, S.; Schenk, A.; Oldhafer, K.-J.; Lang, H.; Peitgen, H.-O.

2010-02-01

The optimal transfer of preoperative planning data and risk evaluations to the operative site is challenging. A common practice is to use preoperative 3D planning models as a printout or as a presentation on a display. One important aspect is that these models were not developed to provide information in complex workspaces like the operating room. Our aim is to reduce the visual complexity of 3D planning models by mapping surgically relevant information onto a risk map. Therefore, we present methods for the identification and classification of critical anatomical structures in the proximity of a preoperatively planned resection surface. Shadow-like distance indicators are introduced to encode the distance from the resection surface to these critical structures on the risk map. In addition, contour lines are used to accentuate shape and spatial depth. The resulting visualization is clear and intuitive, allowing for a fast mental mapping of the current resection surface to the risk map. Preliminary evaluations by liver surgeons indicate that damage to risk structures may be prevented and patient safety may be enhanced using the proposed methods.

Evaluation of potential risks from ash disposal site leachate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mills, W.B.; Loh, J.Y.; Bate, M.C.

1999-04-01

A risk-based approach is used to evaluate potential human health risks associated with a discharge from an ash disposal site into a small stream. The RIVRISK model was used to estimate downstream concentrations and corresponding risks. The modeling and risk analyses focus on boron, the constituent of greatest potential concern to public health at the site investigated, in Riddle Run, Pennsylvania. Prior to performing the risk assessment, the model is validated by comparing observed and predicted results. The comparison is good and an uncertainty analysis is provided to explain the comparison. The hazard quotient (HQ) for boron is predicted tomore » be greater than 1 at presently regulated compliance points over a range of flow rates. The reference dose (RfD) currently recommended by the United States Environmental Protection Agency (US EPA) was used for the analyses. However, the toxicity of boron as expressed by the RfD is now under review by both the U.S. EPA and the World Health Organization. Alternative reference doses being examined would produce predicted boron hazard quotients of less than 1 at nearly all flow conditions.« less

Integrated presentation of ecological risk from multiple stressors

NASA Astrophysics Data System (ADS)

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-10-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrated presentation of ecological risk from multiple stressors.

PubMed

Goussen, Benoit; Price, Oliver R; Rendal, Cecilie; Ashauer, Roman

2016-10-26

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic.

Integrating risk minimization planning throughout the clinical development and commercialization lifecycle: an opinion on how drug development could be improved

PubMed Central

Morrato, Elaine H; Smith, Meredith Y

2015-01-01

Pharmaceutical risk minimization programs are now an established requirement in the regulatory landscape. However, pharmaceutical companies have been slow to recognize and embrace the significant potential these programs offer in terms of enhancing trust with health care professionals and patients, and for providing a mechanism for bringing products to the market that might not otherwise have been approved. Pitfalls of the current drug development process include risk minimization programs that are not data driven; missed opportunities to incorporate pragmatic methods and market-based insights, outmoded tools and data sources, lack of rapid evaluative learning to support timely adaption, lack of systematic approaches for patient engagement, and questions on staffing and organizational infrastructure. We propose better integration of risk minimization with clinical drug development and commercialization work streams throughout the product lifecycle. We articulate a vision and propose broad adoption of organizational models for incorporating risk minimization expertise into the drug development process. Three organizational models are discussed and compared: outsource/external vendor, embedded risk management specialist model, and Center of Excellence. PMID:25750537

Managing occupational risk in creative practice: a new perspective for occupational health and safety.

PubMed

Oughton, Nicholas

2013-01-01

There has been little recognition of the fact that creative production operates in a somewhat different environment and timeframe to that associated with traditional industries. This has resulted in the application of an orthodox, generic or ``one size fits all'' framework of Occupational Health and Safety (OHS) systems across all industries. With the rapid growth of ``creative industry,'' certain challenges arise from the application of this "generic" strategy, mainly because the systems currently employed may not be entirely suitable for creative practice. Some OHS practitioners suggest that the current OHS paradigm is failing. This paper questions the appropriateness of applying a twentieth century OHS model in the present industrial context, and considers what framework will best provide for the well-being of creative workers and their enterprise in the twenty-first century. The paper questions the notion of "Risk" and the paradox associated with "Risk Management," particularly in the context of the creative process. Clearly, risk taking contributes to creative enterprise and effective risk management should accommodate both risk minimization and risk exploitation.

Modelling the current and potential future distributions of the sunn pest Eurygaster integriceps (Hemiptera: Scutelleridae) using CLIMEX.

PubMed

Aljaryian, Rasha; Kumar, Lalit; Taylor, Subhashni

2016-10-01

The sunn pest, Eurygaster integriceps (Hemiptera: Scutelleridae), is an economically significant pest throughout Western Asia and Eastern Europe. This study was conducted to examine the possible risk posed by the influence of climate change on its spread. CLIMEX software was used to model its current global distribution. Future invasion potential was investigated using two global climate models (GCMs), CSIRO-Mk3.0 (CS) and MIROC-H (MR), under A1B and A2 emission scenarios for 2030, 2070 and 2100. Dry to temperate climatic areas favour sunn pests. The potential global range for E. integriceps is expected to extend further polewards between latitudes 60° N and 70° N. Northern Europe and Canada will be at risk of sunn pest invasion as cold stress boundaries recede under the emission scenarios of these models. However, current highly suitable areas, such as South Africa and central Australia, will contract where precipitation is projected to decrease substantially with increased heat stress. Estimating the sunn pest's potential geographic distribution and detecting its climatic limits can provide useful information for management strategies and allow biosecurity authorities to plan ahead and reduce the expected harmful economic consequences by identifying the new areas for pest invasion. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Improving clinical models based on knowledge extracted from current datasets: a new approach.

PubMed

Mendes, D; Paredes, S; Rocha, T; Carvalho, P; Henriques, J; Morais, J

2016-08-01

The Cardiovascular Diseases (CVD) are the leading cause of death in the world, being prevention recognized to be a key intervention able to contradict this reality. In this context, although there are several models and scores currently used in clinical practice to assess the risk of a new cardiovascular event, they present some limitations. The goal of this paper is to improve the CVD risk prediction taking into account the current models as well as information extracted from real and recent datasets. This approach is based on a decision tree scheme in order to assure the clinical interpretability of the model. An innovative optimization strategy is developed in order to adjust the decision tree thresholds (rule structure is fixed) based on recent clinical datasets. A real dataset collected in the ambit of the National Registry on Acute Coronary Syndromes, Portuguese Society of Cardiology is applied to validate this work. In order to assess the performance of the new approach, the metrics sensitivity, specificity and accuracy are used. This new approach achieves sensitivity, a specificity and an accuracy values of, 80.52%, 74.19% and 77.27% respectively, which represents an improvement of about 26% in relation to the accuracy of the original score.

Maximization of the usage of coronary CTA derived plaque information using a machine learning based algorithm to improve risk stratification; insights from the CONFIRM registry.

PubMed

van Rosendael, Alexander R; Maliakal, Gabriel; Kolli, Kranthi K; Beecy, Ashley; Al'Aref, Subhi J; Dwivedi, Aeshita; Singh, Gurpreet; Panday, Mohit; Kumar, Amit; Ma, Xiaoyue; Achenbach, Stephan; Al-Mallah, Mouaz H; Andreini, Daniele; Bax, Jeroen J; Berman, Daniel S; Budoff, Matthew J; Cademartiri, Filippo; Callister, Tracy Q; Chang, Hyuk-Jae; Chinnaiyan, Kavitha; Chow, Benjamin J W; Cury, Ricardo C; DeLago, Augustin; Feuchtner, Gudrun; Hadamitzky, Martin; Hausleiter, Joerg; Kaufmann, Philipp A; Kim, Yong-Jin; Leipsic, Jonathon A; Maffei, Erica; Marques, Hugo; Pontone, Gianluca; Raff, Gilbert L; Rubinshtein, Ronen; Shaw, Leslee J; Villines, Todd C; Gransar, Heidi; Lu, Yao; Jones, Erica C; Peña, Jessica M; Lin, Fay Y; Min, James K

Machine learning (ML) is a field in computer science that demonstrated to effectively integrate clinical and imaging data for the creation of prognostic scores. The current study investigated whether a ML score, incorporating only the 16 segment coronary tree information derived from coronary computed tomography angiography (CCTA), provides enhanced risk stratification compared with current CCTA based risk scores. From the multi-center CONFIRM registry, patients were included with complete CCTA risk score information and ≥3 year follow-up for myocardial infarction and death (primary endpoint). Patients with prior coronary artery disease were excluded. Conventional CCTA risk scores (conventional CCTA approach, segment involvement score, duke prognostic index, segment stenosis score, and the Leaman risk score) and a score created using ML were compared for the area under the receiver operating characteristic curve (AUC). Only 16 segment based coronary stenosis (0%, 1-24%, 25-49%, 50-69%, 70-99% and 100%) and composition (calcified, mixed and non-calcified plaque) were provided to the ML model. A boosted ensemble algorithm (extreme gradient boosting; XGBoost) was used and the entire data was randomly split into a training set (80%) and testing set (20%). First, tuned hyperparameters were used to generate a trained model from the training data set (80% of data). Second, the performance of this trained model was independently tested on the unseen test set (20% of data). In total, 8844 patients (mean age 58.0 ± 11.5 years, 57.7% male) were included. During a mean follow-up time of 4.6 ± 1.5 years, 609 events occurred (6.9%). No CAD was observed in 48.7% (3.5% event), non-obstructive CAD in 31.8% (6.8% event), and obstructive CAD in 19.5% (15.6% event). Discrimination of events as expressed by AUC was significantly better for the ML based approach (0.771) vs the other scores (ranging from 0.685 to 0.701), P < 0.001. Net reclassification improvement analysis showed that the improved risk stratification was the result of down-classification of risk among patients that did not experience events (non-events). A risk score created by a ML based algorithm, that utilizes standard 16 coronary segment stenosis and composition information derived from detailed CCTA reading, has greater prognostic accuracy than current CCTA integrated risk scores. These findings indicate that a ML based algorithm can improve the integration of CCTA derived plaque information to improve risk stratification. Published by Elsevier Inc.

Population modeling for pesticide risk assessment of threatened species-A case study of a terrestrial plant, Boltonia decurrens.

PubMed

Schmolke, Amelie; Brain, Richard; Thorbek, Pernille; Perkins, Daniel; Forbes, Valery

2017-02-01

Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed, individual-based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species' population dynamics and were included in the model approach. The authors use the model to compare the population-level effects of 5 toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism-level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population-level risk assessments of listed species. Population-level effects of herbicides can be assessed in a realistic and species-specific context, and uncertainties can be addressed explicitly. The authors discuss how their approach can inform the future development and application of modeling for population-level risk assessments of listed species, and ecological risk assessment in general. Environ Toxicol Chem 2017;36:480-491. © 2016 SETAC. © 2016 SETAC.

Plasma Free Amino Acid Profiles Predict Four-Year Risk of Developing Diabetes, Metabolic Syndrome, Dyslipidemia, and Hypertension in Japanese Population

PubMed Central

Yamakado, Minoru; Nagao, Kenji; Imaizumi, Akira; Tani, Mizuki; Toda, Akiko; Tanaka, Takayuki; Jinzu, Hiroko; Miyano, Hiroshi; Yamamoto, Hiroshi; Daimon, Takashi; Horimoto, Katsuhisa; Ishizaka, Yuko

2015-01-01

Plasma free amino acid (PFAA) profile is highlighted in its association with visceral obesity and hyperinsulinemia, and future diabetes. Indeed PFAA profiling potentially can evaluate individuals’ future risks of developing lifestyle-related diseases, in addition to diabetes. However, few studies have been performed especially in Asian populations, about the optimal combination of PFAAs for evaluating health risks. We quantified PFAA levels in 3,701 Japanese subjects, and determined visceral fat area (VFA) and two-hour post-challenge insulin (Ins120 min) values in 865 and 1,160 subjects, respectively. Then, models between PFAA levels and the VFA or Ins120 min values were constructed by multiple linear regression analysis with variable selection. Finally, a cohort study of 2,984 subjects to examine capabilities of the obtained models for predicting four-year risk of developing new-onset lifestyle-related diseases was conducted. The correlation coefficients of the obtained PFAA models against VFA or Ins120 min were higher than single PFAA level. Our models work well for future risk prediction. Even after adjusting for commonly accepted multiple risk factors, these models can predict future development of diabetes, metabolic syndrome, and dyslipidemia. PFAA profiles confer independent and differing contributions to increasing the lifestyle-related disease risks in addition to the currently known factors in a general Japanese population. PMID:26156880

Estimates of Present and Future Flood Risk in the Conterminous United States

NASA Astrophysics Data System (ADS)

Wing, O.; Bates, P. D.; Smith, A.; Sampson, C. C.; Johnson, K.; Fargione, J.; Morefield, P.

2017-12-01

Past attempts to estimate flood risk across the USA either have incomplete coverage, coarse resolution or use overly simplified models of the flooding process. In this paper, we use a new 30m resolution model of the entire conterminous US (CONUS) with realistic flood physics to produce estimates of flood hazard which match to within 90% accuracy the skill of local models built with detailed data. Socio-economic data of commensurate resolution are combined with these flood depths to estimate current and future flood risk. Future population and land-use projections from the US Environmental Protection Agency (USEPA) are employed to indicate how flood risk might change through the 21st Century, while present-day estimates utilize the Federal Emergency Management Agency (FEMA) National Structure Inventory and a USEPA map of population distribution. Our data show that the total CONUS population currently exposed to serious flooding is 2.6 to 3.1 times higher than previous estimates; with nearly 41 million Americans living within the so-called 1 in 100-year (1% annual probability) floodplain, compared to only 13 million according to FEMA flood maps. Moreover, socio-economic change alone leads to significant future increases in flood exposure and risk, even before climate change impacts are accounted for. The share of the population living on the 1 in 100-year floodplain is projected to increase from 13.3% in the present-day to 15.6 - 15.8% in 2050 and 16.4 - 16.8% in 2100. The area of developed land within this floodplain, currently at 150,000 km2, is likely to increase by 37 - 72% in 2100 based on the scenarios selected. 5.5 trillion worth of assets currently lie on the 1% floodplain; we project that by 2100 this number will exceed 10 trillion. With this detailed spatial information on present-day flood risk, federal and state agencies can take appropriate action to mitigate losses. Use of USEPA population and land-use projections mean that particular attention can be paid to floodplains where development is projected. Steps to conserve such areas or ensure adequate defenses are in place could avoid the exposure of trillions of dollars of assets, not to mention the human suffering caused by loss of property and life.

Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

PubMed

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

The integrated effect of moderate exercise on coronary heart disease.

PubMed

Mathews, Marc J; Mathews, Edward H; Mathews, George E

Moderate exercise is associated with a lower risk for coronary heart disease (CHD). A suitable integrated model of the CHD pathogenetic pathways relevant to moderate exercise may help to elucidate this association. Such a model is currently not available in the literature. An integrated model of CHD was developed and used to investigate pathogenetic pathways of importance between exercise and CHD. Using biomarker relative-risk data, the pathogenetic effects are representable as measurable effects based on changes in biomarkers. The integrated model provides insight into higherorder interactions underlying the associations between CHD and moderate exercise. A novel 'connection graph' was developed, which simplifies these interactions. It quantitatively illustrates the relationship between moderate exercise and various serological biomarkers of CHD. The connection graph of moderate exercise elucidates all the possible integrated actions through which risk reduction may occur. An integrated model of CHD provides a summary of the effects of moderate exercise on CHD. It also shows the importance of each CHD pathway that moderate exercise influences. The CHD risk-reducing effects of exercise appear to be primarily driven by decreased inflammation and altered metabolism.

A review on the removal of antibiotics by carbon nanotubes.

PubMed

Cong, Qiao; Yuan, Xing; Qu, Jiao

2013-01-01

Increasing concerns have been raised regarding the potential risks of antibiotics to human and ecological health due to their extensive use. Carbon nanotubes (CNTs) have drawn special research attention because of their unique properties and potential applications as a kind of adsorbents. This review summarizes the currently available research on the adsorption of antibiotics on CNTs, and will provide useful information for CNT application and risk assessment. Four different models, the Freundlich model (FM), Langmuir model (LM), Polanyi-Mane model (PMM), and Dubinin-Ashtakhov model (DAM), are often used to fit the adsorption isotherms. Because different mechanisms may act simultaneously, including electrostatic interactions, hydrophobic interactions, π-π bonds, and hydrogen bonds, the prediction of organic chemical adsorption on CNTs is not straightforward. Properties of CNTs, such as specific surface area, adsorption sites, and oxygen content, may influence the adsorption of antibiotics on CNTs. Adsorption heterogeneity and hysteresis are two features of antibiotic-CNT interactions. In addition, CNTs with adsorbed antibiotics may have potential risks for human health. So, further research examining how to reduce such risks is needed.

Group Contingencies to Increase School and Project Attendance in At-Risk Adolescents: A Pilot Study

ERIC Educational Resources Information Center

Costello, Karen M.; Smyth, Sinéad

2017-01-01

The current study employed a group contingency in order to increase school and project attendance in a group of 10 at-risk male adolescents. The participants were already attending a youth diversion project designed to reduce criminal and antisocial behaviors. The group contingency was based on the fantasy football model (an interactive, virtual…

Establishing Preventive Services. Healthy Children 2010. Issues in Children's and Families' Lives, Vol. 9. The John & Kelly Hartman Series.

ERIC Educational Resources Information Center

Weissberg, Roger P., Ed.; Gullotta, Thomas P., Ed.; Hampton, Robert L., Ed.; Ryan, Bruce A., Ed.; Adams, Gerald R., Ed.

Young people are facing greater risks to their current and future health and social development, as shown by involvement of younger and younger children in risk-taking behaviors. This volume emphasizes developmentally and contextually appropriate prevention service delivery models and identifies state-of-the-art, empirically based strategies to…

Risk Factors for Running Away among a General Population Sample of Males and Females

ERIC Educational Resources Information Center

Tyler, Kimberly A.; Hagewen, Kellie J.; Melander, Lisa A.

2011-01-01

The present study examines risk factors for running away and homelessness among a sample of more than 7,000 currently housed youth using the National Longitudinal Study of Adolescent Health (Add Health). Structural equation modeling results revealed that those with greater levels of family instability and those who ran away at Wave 2 were…

Cumulative psychosocial risk, parental socialization, and child cognitive functioning: A longitudinal cascade model.

PubMed

Wade, Mark; Madigan, Sheri; Plamondon, Andre; Rodrigues, Michelle; Browne, Dillon; Jenkins, Jennifer M

2018-06-01

Previous studies have demonstrated that various psychosocial risks are associated with poor cognitive functioning in children, and these risks frequently cluster together. In the current longitudinal study, we tested a model in which it was hypothesized that cumulative psychosocial adversity of mothers would have deleterious effects on children's cognitive functioning by compromising socialization processes within families (i.e., parental competence). A prospective community birth cohort of 501 families was recruited when children were newborns. At this time, mothers reported on their current psychosocial circumstances (socioeconomic status, teen parenthood, depression, etc.), which were summed into a cumulative risk score. Families were followed up at 18 months and 3 years, at which point maternal reflective capacity and cognitive sensitivity were measured, respectively. Child cognition (executive functioning, theory of mind, and language ability) was assessed at age 4.5 using age-appropriate observational and standardized tasks. Analyses controlled for child age, gender, number of children in the home, number of years married, and mothers' history of adversity. The results revealed significant declines in child cognition as well as maternal reflective capacity and cognitive sensitivity as the number of psychosocial risks increased. Moreover, longitudinal path analysis showed significant indirect effects from cumulative risk to all three cognitive outcomes via reflective capacity and cognitive sensitivity. Findings suggest that cumulative risk of mothers may partially account for child cognitive difficulties in various domains by disrupting key parental socialization competencies. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A point-based prediction model for cardiovascular risk in orthotopic liver transplantation: The CAR-OLT score.

PubMed

VanWagner, Lisa B; Ning, Hongyan; Whitsett, Maureen; Levitsky, Josh; Uttal, Sarah; Wilkins, John T; Abecassis, Michael M; Ladner, Daniela P; Skaro, Anton I; Lloyd-Jones, Donald M

2017-12-01

Cardiovascular disease (CVD) complications are important causes of morbidity and mortality after orthotopic liver transplantation (OLT). There is currently no preoperative risk-assessment tool that allows physicians to estimate the risk for CVD events following OLT. We sought to develop a point-based prediction model (risk score) for CVD complications after OLT, the Cardiovascular Risk in Orthotopic Liver Transplantation risk score, among a cohort of 1,024 consecutive patients aged 18-75 years who underwent first OLT in a tertiary-care teaching hospital (2002-2011). The main outcome measures were major 1-year CVD complications, defined as death from a CVD cause or hospitalization for a major CVD event (myocardial infarction, revascularization, heart failure, atrial fibrillation, cardiac arrest, pulmonary embolism, and/or stroke). The bootstrap method yielded bias-corrected 95% confidence intervals for the regression coefficients of the final model. Among 1,024 first OLT recipients, major CVD complications occurred in 329 (32.1%). Variables selected for inclusion in the model (using model optimization strategies) included preoperative recipient age, sex, race, employment status, education status, history of hepatocellular carcinoma, diabetes, heart failure, atrial fibrillation, pulmonary or systemic hypertension, and respiratory failure. The discriminative performance of the point-based score (C statistic = 0.78, bias-corrected C statistic = 0.77) was superior to other published risk models for postoperative CVD morbidity and mortality, and it had appropriate calibration (Hosmer-Lemeshow P = 0.33). The point-based risk score can identify patients at risk for CVD complications after OLT surgery (available at www.carolt.us); this score may be useful for identification of candidates for further risk stratification or other management strategies to improve CVD outcomes after OLT. (Hepatology 2017;66:1968-1979). © 2017 by the American Association for the Study of Liver Diseases.

Water Stress on U.S. Power Production at Decadal Time Horizons

NASA Astrophysics Data System (ADS)

Ganguli, P.; Kumar, D.; Yun, J.; Short, G.; Klausner, J.; Ganguly, A. R.

2014-12-01

Thermoelectric power production at risk, owing to current and projected water scarcity and rising stream temperatures, is assessed for the continental United States (US) at decadal scales. Regional water scarcity is driven by climate variability and change, as well as by multi-sector water demand. While a planning horizon of zero to about thirty years is occasionally prescribed by stakeholders, the challenges to risk assessment at these scales include the difficulty in delineating decadal climate trends from intrinsic natural or multiple model variability. Current generation global climate or earth system models are not credible at the spatial resolutions of power plants, especially for surface water quantity and stream temperatures, which further exacerbates the assessment challenge. Population changes, which are anyway difficult to project, cannot serve as adequate proxies for changes in the water demand across sectors. The hypothesis that robust assessments of power production at risks are possible, despite the uncertainties, has been examined as a proof of concept. An approach is presented for delineating water scarcity and temperature from climate models, observations and population storylines, as well as for assessing power production at risk by examining geospatial correlations of power plant locations within regions where the usable water supply for energy production happens to be scarcer and warmer. Acknowledgment: Funding provided by US DOE's ARPA-E through Award DE-AR0000374.

Left ventricular ejection fraction to predict early mortality in patients with non-ST-segment elevation acute coronary syndromes.

PubMed

Bosch, Xavier; Théroux, Pierre

2005-08-01

Improvement in risk stratification of patients with non-ST-segment elevation acute coronary syndrome (ACS) is a gateway to a more judicious treatment. This study examines whether the routine determination of left ventricular ejection fraction (EF) adds significant prognostic information to currently recommended stratifiers. Several predictors of inhospital mortality were prospectively characterized in a registry study of 1104 consecutive patients, for whom an EF was determined, who were admitted for an ACS. Multiple regression models were constructed using currently recommended clinical, electrocardiographic, and blood marker stratifiers, and values of EF were incorporated into the models. Age, ST-segment shifts, elevation of cardiac markers, and the Thrombolysis in Myocardial Infarction (TIMI) risk score all predicted mortality (P < .0001). Adding EF into the model improved the prediction of mortality (C statistic 0.73 vs 0.67). The odds of death increased by a factor of 1.042 for each 1% decrement in EF. By receiver operating curves, an EF cutoff of 48% provided the best predictive value. Mortality rates were 3.3 times higher within each TIMI risk score stratum in patients with an EF of 48% or lower as compared with those with higher. The TIMI risk score predicts inhospital mortality in a broad population of patients with ACS. The further consideration of EF adds significant prognostic information.

The extreme risk of personal data breaches and the erosion of privacy

NASA Astrophysics Data System (ADS)

Wheatley, Spencer; Maillart, Thomas; Sornette, Didier

2016-01-01

Personal data breaches from organisations, enabling mass identity fraud, constitute an extreme risk. This risk worsens daily as an ever-growing amount of personal data are stored by organisations and on-line, and the attack surface surrounding this data becomes larger and harder to secure. Further, breached information is distributed and accumulates in the hands of cyber criminals, thus driving a cumulative erosion of privacy. Statistical modeling of breach data from 2000 through 2015 provides insights into this risk: A current maximum breach size of about 200 million is detected, and is expected to grow by fifty percent over the next five years. The breach sizes are found to be well modeled by an extremely heavy tailed truncated Pareto distribution, with tail exponent parameter decreasing linearly from 0.57 in 2007 to 0.37 in 2015. With this current model, given a breach contains above fifty thousand items, there is a ten percent probability of exceeding ten million. A size effect is unearthed where both the frequency and severity of breaches scale with organisation size like s0.6. Projections indicate that the total amount of breached information is expected to double from two to four billion items within the next five years, eclipsing the population of users of the Internet. This massive and uncontrolled dissemination of personal identities raises fundamental concerns about privacy.

Climate change and the emergence of vector-borne diseases in Europe: case study of dengue fever.

PubMed

Bouzid, Maha; Colón-González, Felipe J; Lung, Tobias; Lake, Iain R; Hunter, Paul R

2014-08-22

Dengue fever is the most prevalent mosquito-borne viral disease worldwide. Dengue transmission is critically dependent on climatic factors and there is much concern as to whether climate change would spread the disease to areas currently unaffected. The occurrence of autochthonous infections in Croatia and France in 2010 has raised concerns about a potential re-emergence of dengue in Europe. The objective of this study is to estimate dengue risk in Europe under climate change scenarios. We used a Generalized Additive Model (GAM) to estimate dengue fever risk as a function of climatic variables (maximum temperature, minimum temperature, precipitation, humidity) and socioeconomic factors (population density, urbanisation, GDP per capita and population size), under contemporary conditions (1985-2007) in Mexico. We then used our model estimates to project dengue incidence under baseline conditions (1961-1990) and three climate change scenarios: short-term 2011-2040, medium-term 2041-2070 and long-term 2071-2100 across Europe. The model was used to calculate average number of yearly dengue cases at a spatial resolution of 10 × 10 km grid covering all land surface of the currently 27 EU member states. To our knowledge, this is the first attempt to model dengue fever risk in Europe in terms of disease occurrence rather than mosquito presence. The results were presented using Geographical Information System (GIS) and allowed identification of areas at high risk. Dengue fever hot spots were clustered around the coastal areas of the Mediterranean and Adriatic seas and the Po Valley in northern Italy. This risk assessment study is likely to be a valuable tool assisting effective and targeted adaptation responses to reduce the likely increased burden of dengue fever in a warmer world.

Space Mission Human Reliability Analysis (HRA) Project

NASA Technical Reports Server (NTRS)

Boyer, Roger

2014-01-01

The purpose of the Space Mission Human Reliability Analysis (HRA) Project is to extend current ground-based HRA risk prediction techniques to a long-duration, space-based tool. Ground-based HRA methodology has been shown to be a reasonable tool for short-duration space missions, such as Space Shuttle and lunar fly-bys. However, longer-duration deep-space missions, such as asteroid and Mars missions, will require the crew to be in space for as long as 400 to 900 day missions with periods of extended autonomy and self-sufficiency. Current indications show higher risk due to fatigue, physiological effects due to extended low gravity environments, and others, may impact HRA predictions. For this project, Safety & Mission Assurance (S&MA) will work with Human Health & Performance (HH&P) to establish what is currently used to assess human reliabiilty for human space programs, identify human performance factors that may be sensitive to long duration space flight, collect available historical data, and update current tools to account for performance shaping factors believed to be important to such missions. This effort will also contribute data to the Human Performance Data Repository and influence the Space Human Factors Engineering research risks and gaps (part of the HRP Program). An accurate risk predictor mitigates Loss of Crew (LOC) and Loss of Mission (LOM).The end result will be an updated HRA model that can effectively predict risk on long-duration missions.

What is behind the priority heuristic? A mathematical analysis and comment on Brandstätter, Gigerenzer, and Hertwig (2006).

PubMed

Rieger, Marc Oliver; Wang, Mei

2008-01-01

Comments on the article by E. Brandstätter, G. Gigerenzer, and R. Hertwig. The authors discuss the priority heuristic, a recent model for decisions under risk. They reanalyze the experimental validity of this approach and discuss how these results compare with cumulative prospect theory, the currently most established model in behavioral economics. They also discuss how general models for decisions under risk based on a heuristic approach can be understood mathematically to gain some insight in their limitations. They finally consider whether the priority heuristic model can lead to some understanding of the decision process of individuals or whether it is better seen as an as-if model. (c) 2008 APA, all rights reserved

Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry.

PubMed

Nait Aicha, Ahmed; Englebienne, Gwenn; van Schooten, Kimberley S; Pijnappels, Mirjam; Kröse, Ben

2018-05-22

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Body-worn sensors such as accelerometers can provide valuable insight into fall risk. Currently, biomechanical features derived from accelerometer data are used for the assessment of fall risk. Here, we studied whether deep learning methods from machine learning are suited to automatically derive features from raw accelerometer data that assess fall risk. We used an existing dataset of 296 older adults. We compared the performance of three deep learning model architectures (convolutional neural network (CNN), long short-term memory (LSTM) and a combination of these two (ConvLSTM)) to each other and to a baseline model with biomechanical features on the same dataset. The results show that the deep learning models in a single-task learning mode are strong in recognition of identity of the subject, but that these models only slightly outperform the baseline method on fall risk assessment. When using multi-task learning, with gender and age as auxiliary tasks, deep learning models perform better. We also found that preprocessing of the data resulted in the best performance (AUC = 0.75). We conclude that deep learning models, and in particular multi-task learning, effectively assess fall risk on the basis of wearable sensor data.

Assessment of state measures of risk-appropriate care for very low birth weight infants and recommendations for enhancing regionalized state systems.

PubMed

Nowakowski, Lindsey; Barfield, Wanda D; Kroelinger, Charlan D; Lauver, Cassie B; Lawler, Michele H; White, Vanessa A; Ramos, Lauren Raskin

2012-01-01

The goal of this study was to examine state measurements and improvements in risk-appropriate care for very low birth weight (VLBW) infants. The authors reviewed state perinatal regionalization models and levels of care to compare varying definitions between states and assess mechanisms of measurement and areas for improvement. Seven states that presented at a 2009 Association of Maternal & Child Health Programs Perinatal Regionalization Meeting were included in the assessment. Information was gathered from meeting presentations, presenters, state representatives, and state websites. Comparison of state levels of care and forms of regulation were outlined. Review of state models revealed variability in the models themselves, as well as the various mechanisms for measuring and improving risk-appropriate care. Regulation of regionalization programs, data surveillance, review of adverse events, and consideration of geography and demographics were identified as mechanisms facilitating better measurement of risk-appropriate care. Antenatal or neonatal transfer arrangements, telemedicine networks, acquisition of funding, provision of financial incentives, and patient education comprised state actions for improving risk-appropriate care. The void of explicit and updated national standards led to the current variations in definitions and models among states. State regionalization models and measures of risk-appropriate care varied greatly. These variations arose from inconsistent definitions and models of perinatal regionalization. Guidelines should be collaboratively developed by healthcare providers and public health officials for consistent and suitable measures of perinatal risk-appropriate care.

Deep Learning to Predict Falls in Older Adults Based on Daily-Life Trunk Accelerometry

PubMed Central

Englebienne, Gwenn; Pijnappels, Mirjam

2018-01-01

Early detection of high fall risk is an essential component of fall prevention in older adults. Wearable sensors can provide valuable insight into daily-life activities; biomechanical features extracted from such inertial data have been shown to be of added value for the assessment of fall risk. Body-worn sensors such as accelerometers can provide valuable insight into fall risk. Currently, biomechanical features derived from accelerometer data are used for the assessment of fall risk. Here, we studied whether deep learning methods from machine learning are suited to automatically derive features from raw accelerometer data that assess fall risk. We used an existing dataset of 296 older adults. We compared the performance of three deep learning model architectures (convolutional neural network (CNN), long short-term memory (LSTM) and a combination of these two (ConvLSTM)) to each other and to a baseline model with biomechanical features on the same dataset. The results show that the deep learning models in a single-task learning mode are strong in recognition of identity of the subject, but that these models only slightly outperform the baseline method on fall risk assessment. When using multi-task learning, with gender and age as auxiliary tasks, deep learning models perform better. We also found that preprocessing of the data resulted in the best performance (AUC = 0.75). We conclude that deep learning models, and in particular multi-task learning, effectively assess fall risk on the basis of wearable sensor data. PMID:29786659

Risk of Suicidal Events With Atomoxetine Compared to Stimulant Treatment: A Cohort Study

PubMed Central

Bussing, Regina; Kubilis, Paul; Gerhard, Tobias; Segal, Richard; Shuster, Jonathan J; Winterstein, Almut G

2016-01-01

BACKGROUND: Antidepressant effects on increased suicidality in children have raised public concern in recent years. Approved in 2002 for attention-deficit/hyperactivity disorder treatment, the selective noradrenalin-reuptake-inhibitor atomoxetine was initially investigated for the treatment of depression. In post-hoc analyses of clinical trial data, atomoxetine has been associated with an increased risk of suicidal ideation in children and adolescents. We analyzed whether the observed increased risk of suicidal ideation in clinical trials translates into an increased risk of suicidal events in pediatric patients treated with atomoxetine compared with stimulants in 26 Medicaid programs. METHODS: Employing a retrospective cohort design, we used propensity score–adjusted Cox proportional hazard models to evaluate the risk of suicide and suicide attempt in pediatric patients initiating treatment with atomoxetine compared with stimulants from 2002 to 2006. RESULTS: The first-line treatment cohort included 279 315 patients. During the first year of follow-up, the adjusted hazard ratio for current atomoxetine use compared with current stimulant use was 0.95 (95% CI 0.47–1.92, P = .88). The second-line treatment cohort included 220 215 patients. During the first year of follow-up, the adjusted hazard ratio for current atomoxetine use compared with current stimulant use was 0.71 (95% CI 0.30–1.67, P = .43). CONCLUSIONS: First- and second-line treatment of youths age 5 to 18 with atomoxetine compared with stimulants was not significantly associated with an increased risk of suicidal events. The low incidence of suicide and suicide attempt resulted in wide confidence intervals and did not allow stratified analysis of high-risk groups or assessment of suicidal risk associated with long-term use of atomoxetine. PMID:27244795

Risk of Suicidal Events With Atomoxetine Compared to Stimulant Treatment: A Cohort Study.

PubMed

Linden, Stephan; Bussing, Regina; Kubilis, Paul; Gerhard, Tobias; Segal, Richard; Shuster, Jonathan J; Winterstein, Almut G

2016-05-01

Antidepressant effects on increased suicidality in children have raised public concern in recent years. Approved in 2002 for attention-deficit/hyperactivity disorder treatment, the selective noradrenalin-reuptake-inhibitor atomoxetine was initially investigated for the treatment of depression. In post-hoc analyses of clinical trial data, atomoxetine has been associated with an increased risk of suicidal ideation in children and adolescents. We analyzed whether the observed increased risk of suicidal ideation in clinical trials translates into an increased risk of suicidal events in pediatric patients treated with atomoxetine compared with stimulants in 26 Medicaid programs. Employing a retrospective cohort design, we used propensity score-adjusted Cox proportional hazard models to evaluate the risk of suicide and suicide attempt in pediatric patients initiating treatment with atomoxetine compared with stimulants from 2002 to 2006. The first-line treatment cohort included 279 315 patients. During the first year of follow-up, the adjusted hazard ratio for current atomoxetine use compared with current stimulant use was 0.95 (95% CI 0.47-1.92, P = .88). The second-line treatment cohort included 220 215 patients. During the first year of follow-up, the adjusted hazard ratio for current atomoxetine use compared with current stimulant use was 0.71 (95% CI 0.30-1.67, P = .43). First- and second-line treatment of youths age 5 to 18 with atomoxetine compared with stimulants was not significantly associated with an increased risk of suicidal events. The low incidence of suicide and suicide attempt resulted in wide confidence intervals and did not allow stratified analysis of high-risk groups or assessment of suicidal risk associated with long-term use of atomoxetine. Copyright © 2016 by the American Academy of Pediatrics.

A qualitative study of lung cancer risk perceptions and smoking beliefs among national lung screening trial participants.

PubMed

Park, Elyse R; Streck, Joanna M; Gareen, Ilana F; Ostroff, Jamie S; Hyland, Kelly A; Rigotti, Nancy A; Pajolek, Hannah; Nichter, Mark

2014-02-01

The National Comprehensive Cancer Network and the American Cancer Society recently released lung screening guidelines that include smoking cessation counseling for smokers undergoing screening. Previous work indicates that smoking behaviors and risk perceptions of the National Lung Screening Trial (NLST) participants were relatively unchanged. We explored American College of Radiology Imaging Network (ACRIN)/NLST former and current smokers' risk perceptions specifically to (a) determine whether lung screening is a cue for behavior change, (b) elucidate risk perceptions for lung cancer and smoking-related diseases, and (c) explore postscreening behavioral intentions and changes. A random sample of 35 participants from 4 ACRIN sites were qualitatively interviewed 1-2 years postscreen. We used a structured interview guide based on Health Belief Model and Self-Regulation Model constructs. Content analyses were conducted with NVivo 8. Most participants endorsed high-risk perceptions for lung cancer and smoking-related diseases, but heightened concern about these risks did not appear to motivate participants to seek screening. Risk perceptions were mostly attributed to participants' heavy smoking histories; former smokers expressed greatly reduced risk. Lung cancer and smoking-related diseases were perceived as very severe although participants endorsed low worry. Current smokers had low confidence in their ability to quit, and none reported quitting following their initial screen. Lung screening did not appear to be a behavior change cue to action, and high-risk perceptions did not translate into quitting behaviors. Cognitive and emotional dissonance and avoidance strategies may deter engagement in smoking behavior change. Smoking cessation and prevention interventions during lung screening should explore risk perceptions, emotions, and quit confidence.

A Qualitative Study of Lung Cancer Risk Perceptions and Smoking Beliefs Among National Lung Screening Trial Participants

PubMed Central

2014-01-01

Introduction: The National Comprehensive Cancer Network and the American Cancer Society recently released lung screening guidelines that include smoking cessation counseling for smokers undergoing screening. Previous work indicates that smoking behaviors and risk perceptions of the National Lung Screening Trial (NLST) participants were relatively unchanged. We explored American College of Radiology Imaging Network (ACRIN)/NLST former and current smokers’ risk perceptions specifically to (a) determine whether lung screening is a cue for behavior change, (b) elucidate risk perceptions for lung cancer and smoking-related diseases, and (c) explore postscreening behavioral intentions and changes. Methods: A random sample of 35 participants from 4 ACRIN sites were qualitatively interviewed 1–2 years postscreen. We used a structured interview guide based on Health Belief Model and Self-Regulation Model constructs. Content analyses were conducted with NVivo 8. Results: Most participants endorsed high-risk perceptions for lung cancer and smoking-related diseases, but heightened concern about these risks did not appear to motivate participants to seek screening. Risk perceptions were mostly attributed to participants’ heavy smoking histories; former smokers expressed greatly reduced risk. Lung cancer and smoking-related diseases were perceived as very severe although participants endorsed low worry. Current smokers had low confidence in their ability to quit, and none reported quitting following their initial screen. Conclusions: Lung screening did not appear to be a behavior change cue to action, and high-risk perceptions did not translate into quitting behaviors. Cognitive and emotional dissonance and avoidance strategies may deter engagement in smoking behavior change. Smoking cessation and prevention interventions during lung screening should explore risk perceptions, emotions, and quit confidence. PMID:23999653

OSHA's approach to risk assessment for setting a revised occupational exposure standard for 1,3-butadiene.

PubMed Central

Grossman, E A; Martonik, J

1990-01-01

In its 1980 benzene decision [Industrial Union Department, ALF-CIO v. American Petroleum Institute, 448 U.S. 607 (1980)], the Supreme Court ruled that "before he can promulgate any permanent health or safety standard, the Secretary [of Labor] is required to make a threshold finding that a place of employment is unsafe--in the sense that significant risks are present and can be lessened by a change in practices" (448 U.S. at 642). The Occupational Safety and Health Administration (OSHA) has interpreted this to mean that whenever possible, it must quantify the risk associated with occupational exposure to a toxic substance at the current permissible exposure limit (PEL). If OSHA determines that there is significant risk to workers' health at its current standard, then it must quantify the risk associated with a variety of alternative standards to determine at what level, if any, occupational exposure to a substance no longer poses a significant risk. For rulemaking on occupational exposure to 1,3-butadiene, there are two studies that are suitable for quantitative risk assessment. One is a mouse inhalation bioassay conducted by the National Toxicology Program (NTP), and the other is a rat inhalation bioassay conducted by Hazelton Laboratories Europe. Of the four risk assessments that have been submitted to OSHA, all four have used the mouse and/or rat data with a variety of models to quantify the risk associated with occupational exposure to 1,3-butadiene. In addition, OSHA has performed its own risk assessment using the female mouse and female rat data and the one-hit and multistage models.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:2401254

Using toxicokinetic-toxicodynamic modeling as an acute risk assessment refinement approach in vertebrate ecological risk assessment.

PubMed

Ducrot, Virginie; Ashauer, Roman; Bednarska, Agnieszka J; Hinarejos, Silvia; Thorbek, Pernille; Weyman, Gabriel

2016-01-01

Recent guidance identified toxicokinetic-toxicodynamic (TK-TD) modeling as a relevant approach for risk assessment refinement. Yet, its added value compared to other refinement options is not detailed, and how to conduct the modeling appropriately is not explained. This case study addresses these issues through 2 examples of individual-level risk assessment for 2 hypothetical plant protection products: 1) evaluating the risk for small granivorous birds and small omnivorous mammals of a single application, as a seed treatment in winter cereals, and 2) evaluating the risk for fish after a pulsed treatment in the edge-of-field zone. Using acute test data, we conducted the first tier risk assessment as defined in the European Food Safety Authority (EFSA) guidance. When first tier risk assessment highlighted a concern, refinement options were discussed. Cases where the use of models should be preferred over other existing refinement approaches were highlighted. We then practically conducted the risk assessment refinement by using 2 different models as examples. In example 1, a TK model accounting for toxicokinetics and relevant feeding patterns in the skylark and in the wood mouse was used to predict internal doses of the hypothetical active ingredient in individuals, based on relevant feeding patterns in an in-crop situation, and identify the residue levels leading to mortality. In example 2, a TK-TD model accounting for toxicokinetics, toxicodynamics, and relevant exposure patterns in the fathead minnow was used to predict the time-course of fish survival for relevant FOCUS SW exposure scenarios and identify which scenarios might lead to mortality. Models were calibrated using available standard data and implemented to simulate the time-course of internal dose of active ingredient or survival for different exposure scenarios. Simulation results were discussed and used to derive the risk assessment refinement endpoints used for decision. Finally, we compared the "classical" risk assessment approach with the model-based approach. These comparisons showed that TK and TK-TD models can bring more realism to the risk assessment through the possibility to study realistic exposure scenarios and to simulate relevant mechanisms of effects (including delayed toxicity and recovery). Noticeably, using TK-TD models is currently the most relevant way to directly connect realistic exposure patterns to effects. We conclude with recommendations on how to properly use TK and TK-TD model in acute risk assessment for vertebrates. © 2015 SETAC.

Customized oligonucleotide microarray gene expression-based classification of neuroblastoma patients outperforms current clinical risk stratification.

PubMed

Oberthuer, André; Berthold, Frank; Warnat, Patrick; Hero, Barbara; Kahlert, Yvonne; Spitz, Rüdiger; Ernestus, Karen; König, Rainer; Haas, Stefan; Eils, Roland; Schwab, Manfred; Brors, Benedikt; Westermann, Frank; Fischer, Matthias

2006-11-01

To develop a gene expression-based classifier for neuroblastoma patients that reliably predicts courses of the disease. Two hundred fifty-one neuroblastoma specimens were analyzed using a customized oligonucleotide microarray comprising 10,163 probes for transcripts with differential expression in clinical subgroups of the disease. Subsequently, the prediction analysis for microarrays (PAM) was applied to a first set of patients with maximally divergent clinical courses (n = 77). The classification accuracy was estimated by a complete 10-times-repeated 10-fold cross validation, and a 144-gene predictor was constructed from this set. This classifier's predictive power was evaluated in an independent second set (n = 174) by comparing results of the gene expression-based classification with those of risk stratification systems of current trials from Germany, Japan, and the United States. The first set of patients was accurately predicted by PAM (cross-validated accuracy, 99%). Within the second set, the PAM classifier significantly separated cohorts with distinct courses (3-year event-free survival [EFS] 0.86 +/- 0.03 [favorable; n = 115] v 0.52 +/- 0.07 [unfavorable; n = 59] and 3-year overall survival 0.99 +/- 0.01 v 0.84 +/- 0.05; both P < .0001) and separated risk groups of current neuroblastoma trials into subgroups with divergent outcome (NB2004: low-risk 3-year EFS 0.86 +/- 0.04 v 0.25 +/- 0.15, P < .0001; intermediate-risk 1.00 v 0.57 +/- 0.19, P = .018; high-risk 0.81 +/- 0.10 v 0.56 +/- 0.08, P = .06). In a multivariate Cox regression model, the PAM predictor classified patients of the second set more accurately than risk stratification of current trials from Germany, Japan, and the United States (P < .001; hazard ratio, 4.756 [95% CI, 2.544 to 8.893]). Integration of gene expression-based class prediction of neuroblastoma patients may improve risk estimation of current neuroblastoma trials.

Toward a cumulative ecological risk model for the etiology of child maltreatment

PubMed Central

MacKenzie, Michael J.; Kotch, Jonathan B.; Lee, Li-Ching

2011-01-01

The purpose of the current study was to further the integration of cumulative risk models with empirical research on the etiology of child maltreatment. Despite the well-established literature supporting the importance of the accumulation of ecological risk, this perspective has had difficulty infiltrating empirical maltreatment research and its tendency to focus on more limited risk factors. Utilizing a sample of 842 mother-infant dyads, we compared the capacity of individual risk factors and a cumulative index to predict maltreatment reports in a prospective longitudinal investigation over the first sixteen years of life. The total load of risk in early infancy was found to be related to maternal cognitions surrounding her new role, measures of social support and well-being, and indicators of child cognitive functioning. After controlling for total level of cumulative risk, most single factors failed to predict later maltreatment reports and no single variable provided odd-ratios as powerful as the predictive power of a cumulative index. Continuing the shift away from simplistic causal models toward an appreciation for the cumulative nature of risk would be an important step forward in the way we conceptualize intervention and support programs, concentrating them squarely on alleviating the substantial risk facing so many of society’s families. PMID:24817777

Neglected chronic disease: The WHO framework on non-communicable diseases and implications for the global poor.

PubMed

Nulu, Shanti

2017-04-01

The current global framework on noncommunicable disease (NCD), as exemplified by the WHO Action Plan of 2012, neglects the needs of the global poor. The current framework is rooted in an outdated pseudo-evolutionary theory of epidemiologic transition, which weds NCDs to modernity, and relies on global aggregate data. It is oriented around a simplistic causal model of behaviour, risk and disease, which implicitly locates 'risk' within individuals, conveniently drawing attention away from important global drivers of the NCD epidemic. In fact, the epidemiologic realities of the bottom billion reveal a burden of neglected chronic diseases that are associated with 'alternative' environmental and infectious risks that are largely structurally determined. In addition, the vertical orientation of the framework fails to centralise health systems and delivery issues that are essential to chronic disease prevention and treatment. A new framework oriented around a global health equity perspective would be able to correct some of the failures of the current model by bringing the needs of the global poor to the forefront, and centralising health systems and delivery. In addition, core social science concepts such as Bordieu's habitus may be useful to re-conceptualising strategies that may address both behavioural and structural determinants of health.

Anemia risk in relation to lead exposure in lead-related manufacturing.

PubMed

Hsieh, Nan-Hung; Chung, Shun-Hui; Chen, Szu-Chieh; Chen, Wei-Yu; Cheng, Yi-Hsien; Lin, Yi-Jun; You, Su-Han; Liao, Chung-Min

2017-05-05

Lead-exposed workers may suffer adverse health effects under the currently regulated blood lead (BPb) levels. However, a probabilistic assessment about lead exposure-associated anemia risk is lacking. The goal of this study was to examine the association between lead exposure and anemia risk among factory workers in Taiwan. We first collated BPb and indicators of hematopoietic function data via health examination records that included 533 male and 218 female lead-exposed workers between 2012 and 2014. We used benchmark dose (BMD) modeling to estimate the critical effect doses for detection of abnormal indicators. A risk-based probabilistic model was used to characterize the potential hazard of lead poisoning for job-specific workers by hazard index (HI). We applied Bayesian decision analysis to determine whether BMD could be implicated as a suitable BPb standard. Our results indicated that HI for total lead-exposed workers was 0.78 (95% confidence interval: 0.50-1.26) with risk occurrence probability of 11.1%. The abnormal risk of anemia indicators for male and female workers could be reduced, respectively, by 67-77% and 86-95% by adopting the suggested BPb standards of 25 and 15 μg/dL. We conclude that cumulative exposure to lead in the workplace was significantly associated with anemia risk. This study suggests that current BPb standard needs to be better understood for the application of lead-exposed population protection in different scenarios to provide a novel standard for health management. Low-level lead exposure risk is an occupational and public health problem that should be paid more attention.

An exploration of mortality risk factors in non-severe pneumonia in children using clinical data from Kenya.

PubMed

Tuti, Timothy; Agweyu, Ambrose; Mwaniki, Paul; Peek, Niels; English, Mike

2017-11-13

Childhood pneumonia is the leading infectious cause of mortality in children younger than 5 years old. Recent updates to World Health Organization pneumonia guidelines recommend outpatient care for a population of children previously classified as high risk. This revision has been challenged by policymakers in Africa, where mortality related to pneumonia is higher than in other regions and often complicated by comorbidities. This study aimed to identify factors that best discriminate inpatient mortality risk in non-severe pneumonia and explore whether these factors offer any added benefit over the current criteria used to identify children with pneumonia requiring inpatient care. We undertook a retrospective cohort study of children aged 2-59 months admitted with a clinical diagnosis of pneumonia at 14 public hospitals in Kenya between February 2014 and February 2016. Using machine learning techniques, we analysed whether clinical characteristics and common comorbidities increased the risk of inpatient mortality for non-severe pneumonia. The topmost risk factors were subjected to decision curve analysis to explore if using them as admission criteria had any net benefit above the current criteria. Out of 16,162 children admitted with pneumonia during the study period, 10,687 were eligible for subsequent analysis. Inpatient mortality within this non-severe group was 252/10,687 (2.36%). Models demonstrated moderately good performance; the partial least squares discriminant analysis model had higher sensitivity for predicting mortality in comparison to logistic regression. Elevated respiratory rate (≥70 bpm), age 2-11 months and weight-for-age Z-score (WAZ) < -3SD were highly discriminative of mortality. These factors ranked consistently across the different models. For a risk threshold probability of 7-14%, there is a net benefit to admitting the patient sub-populations with these features as additional criteria alongside those currently used to classify severe pneumonia. Of the population studied, 70.54% met at least one of these criteria. Sensitivity analyses indicated that the overall results were not significantly affected by variations in pneumonia severity classification criteria. Children with non-severe pneumonia aged 2-11 months or with respiratory rate ≥ 70 bpm or very low WAZ experience risks of inpatient mortality comparable to severe pneumonia. Inpatient care is warranted in these high-risk groups of children.

New Madrid Seismotectonic Program. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Buschbach, T.C.

1986-06-01

The New Madrid Seismotectonic Program was a large-scale multidisciplinary effort that was designed to define the structural setting and tectonic history of the New Madrid area in order to realistically evaluate earthquake risks in the siting of nuclear facilities. The tectonic model proposed to explain the New Madrid seismicity is the ''zone of weakness'' model, which suggests that an ancient rift complex formed a zone of weakness in the earth's crust along which regional stresses are relieved. The Reelfoot Rift portion of the proposed rift complex is currently seismically active, and it must be considered capable and likely to bemore » exposed to large-magnitude earthquakes in the future. Earthquakes that occur in the Wabash Valley area are less abundant and generally have deeper hypocenters than earthquakes in the New Madrid area. The area of the Southern Indiana Arm must be considered to have seismic risk, although a lesser extent than the Reelfoot Rift. The east-west trending Rough Creek Graben is practically aseismic, probably in large part due to its orientation in the current stress field. The northwest-trending St. Louis Arm of the proposed rift complex includes a pattern of seismicity that extends from southern Illinois along the Mississippi River. This arm must be considered to have seismic risk, but because of the lack of development of a graben associated with the arm and the orientation of the arm in the current stress field, the risk appears to be less than in the Reelfoot Rift portion of the rift complex.« less

Customer-Specific Transaction Risk Management in E-Commerce

NASA Astrophysics Data System (ADS)

Ruch, Markus; Sackmann, Stefan

Increasing potential for turnover in e-commerce is inextricably linked with an increase in risk. Online retailers (e-tailers), aiming for a company-wide value orientation should manage this risk. However, current approaches to risk management either use average retail prices elevated by an overall risk premium or restrict the payment methods offered to customers. Thus, they neglect customer-specific value and risk attributes and leave turnover potentials unconsidered. To close this gap, an innovative valuation model is proposed in this contribution that integrates customer-specific risk and potential turnover. The approach presented evaluates different payment methods using their risk-turnover characteristic, provides a risk-adjusted decision basis for selecting payment methods and allows e-tailers to derive automated risk management decisions per customer and transaction without reducing turnover potential.

Work stress and health risk behavior.

PubMed

Siegrist, Johannes; Rödel, Andreas

2006-12-01

This contribution discusses current knowledge of associations between psychosocial stress at work and health risk behavior, in particular cigarette smoking, alcohol consumption and overweight, by reviewing findings from major studies in the field published between 1989 and 2006. Psychosocial stress at work is measured by the demand-control model and the effort-reward imbalance model. Health risk behavior was analyzed in the broader context of a health-related Western lifestyle with socially and economically patterned practices of consumption. Overall, the review, based on 46 studies, only modestly supports the hypothesis of a consistent association between work stress and health risk behavior. The relatively strongest relationships have been found with regard to heavy alcohol consumption among men, overweight, and the co-manifestation of several risks. Suggestions for further research are given, and the need to reduce stressful experience in the framework of worksite health promotion programs is emphasized.

Empirically Based Composite Fracture Prediction Model From the Global Longitudinal Study of Osteoporosis in Postmenopausal Women (GLOW)

PubMed Central

Compston, Juliet E.; Chapurlat, Roland D.; Pfeilschifter, Johannes; Cooper, Cyrus; Hosmer, David W.; Adachi, Jonathan D.; Anderson, Frederick A.; Díez-Pérez, Adolfo; Greenspan, Susan L.; Netelenbos, J. Coen; Nieves, Jeri W.; Rossini, Maurizio; Watts, Nelson B.; Hooven, Frederick H.; LaCroix, Andrea Z.; March, Lyn; Roux, Christian; Saag, Kenneth G.; Siris, Ethel S.; Silverman, Stuart; Gehlbach, Stephen H.

2014-01-01

Context: Several fracture prediction models that combine fractures at different sites into a composite outcome are in current use. However, to the extent individual fracture sites have differing risk factor profiles, model discrimination is impaired. Objective: The objective of the study was to improve model discrimination by developing a 5-year composite fracture prediction model for fracture sites that display similar risk profiles. Design: This was a prospective, observational cohort study. Setting: The study was conducted at primary care practices in 10 countries. Patients: Women aged 55 years or older participated in the study. Intervention: Self-administered questionnaires collected data on patient characteristics, fracture risk factors, and previous fractures. Main Outcome Measure: The main outcome is time to first clinical fracture of hip, pelvis, upper leg, clavicle, or spine, each of which exhibits a strong association with advanced age. Results: Of four composite fracture models considered, model discrimination (c index) is highest for an age-related fracture model (c index of 0.75, 47 066 women), and lowest for Fracture Risk Assessment Tool (FRAX) major fracture and a 10-site model (c indices of 0.67 and 0.65). The unadjusted increase in fracture risk for an additional 10 years of age ranges from 80% to 180% for the individual bones in the age-associated model. Five other fracture sites not considered for the age-associated model (upper arm/shoulder, rib, wrist, lower leg, and ankle) have age associations for an additional 10 years of age from a 10% decrease to a 60% increase. Conclusions: After examining results for 10 different bone fracture sites, advanced age appeared the single best possibility for uniting several different sites, resulting in an empirically based composite fracture risk model. PMID:24423345

Scientific Foundations for an IUCN Red List of Ecosystems

PubMed Central

Keith, David A.; Rodríguez, Jon Paul; Rodríguez-Clark, Kathryn M.; Nicholson, Emily; Aapala, Kaisu; Alonso, Alfonso; Asmussen, Marianne; Bachman, Steven; Basset, Alberto; Barrow, Edmund G.; Benson, John S.; Bishop, Melanie J.; Bonifacio, Ronald; Brooks, Thomas M.; Burgman, Mark A.; Comer, Patrick; Comín, Francisco A.; Essl, Franz; Faber-Langendoen, Don; Fairweather, Peter G.; Holdaway, Robert J.; Jennings, Michael; Kingsford, Richard T.; Lester, Rebecca E.; Nally, Ralph Mac; McCarthy, Michael A.; Moat, Justin; Oliveira-Miranda, María A.; Pisanu, Phil; Poulin, Brigitte; Regan, Tracey J.; Riecken, Uwe; Spalding, Mark D.; Zambrano-Martínez, Sergio

2013-01-01

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world’s ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity PMID:23667454

Scientific foundations for an IUCN Red List of ecosystems.

PubMed

Keith, David A; Rodríguez, Jon Paul; Rodríguez-Clark, Kathryn M; Nicholson, Emily; Aapala, Kaisu; Alonso, Alfonso; Asmussen, Marianne; Bachman, Steven; Basset, Alberto; Barrow, Edmund G; Benson, John S; Bishop, Melanie J; Bonifacio, Ronald; Brooks, Thomas M; Burgman, Mark A; Comer, Patrick; Comín, Francisco A; Essl, Franz; Faber-Langendoen, Don; Fairweather, Peter G; Holdaway, Robert J; Jennings, Michael; Kingsford, Richard T; Lester, Rebecca E; Mac Nally, Ralph; McCarthy, Michael A; Moat, Justin; Oliveira-Miranda, María A; Pisanu, Phil; Poulin, Brigitte; Regan, Tracey J; Riecken, Uwe; Spalding, Mark D; Zambrano-Martínez, Sergio

2013-01-01

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world's ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity.

Modeling the risk of phosphorus runoff following single and split phosphorus fertilizer applications in two contrasting catchments.

PubMed

Burkitt, Lucy L; Dougherty, Warwick J; Corkrey, Ross; Broad, Shane T

2011-01-01

The potential loss of P in runoff is a function of the combined effects of fertilizer-soil interactions and climatic characteristics. In this study, we applied a Bayesian approach to experimental data to model the annualized long-term risk of P runoff following single and split P fertilizer applications using two example catchments with contrasting rainfall/runoff patterns. Split P fertilizer strategies are commonly used in intensive pasture production in Australia and our results showed that three applications of 13.3 kg P ha(-1) resulted in a greater risk of P runoff compared with a single application of 40 kg P ha(-1) when long-term surface runoff data were incorporated into a Bayesian P risk model. Splitting P fertilizer applications increased the likelihood of a coincidence of fertilizer application and runoff occurring. We found that the overall risk of P runoff is also increased in catchments where the rainfall/runoff pattern is less predictable, compared with catchments where rainfall/runoff is winter dominant. The findings of our study also question the effectiveness of current recommendations to avoid applying fertilizer if runoff is likely to occur in the next few days, as we found that total P concentrations at the half-life were still very high (18.2 and 8.2 mg P L(-1)) following single and split P treatments, respectively. Data from the current study also highlight that omitting P fertilizer on soils that already have adequate soil test P concentrations is an effective method of reducing P loss in surface runoff. If P fertilizer must be applied, we recommend less frequent applications and only during periods of the year when the risk of surface P runoff is low.

Space Radiation Cancer Risks

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.

2007-01-01

Space radiation presents major challenges to astronauts on the International Space Station and for future missions to the Earth s moon or Mars. Methods used to project risks on Earth need to be modified because of the large uncertainties in projecting cancer risks from space radiation, and thus impact safety factors. We describe NASA s unique approach to radiation safety that applies uncertainty based criteria within the occupational health program for astronauts: The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in the radiation cancer projection model. NASA s acceptable level of risk for ISS and their new lunar program have been set at the point-estimate of a 3-percent risk of exposure induced death (REID). Tissue-averaged organ dose-equivalents are combined with age at exposure and gender-dependent risk coefficients to project the cumulative occupational radiation risks incurred by astronauts. The 95% CL criteria in practice is a stronger criterion than ALARA, but not an absolute cut-off as is applied to a point projection of a 3% REID. We describe the most recent astronaut dose limits, and present a historical review of astronaut organ doses estimates from the Mercury through the current ISS program, and future projections for lunar and Mars missions. NASA s 95% CL criteria is linked to a vibrant ground based radiobiology program investigating the radiobiology of high-energy protons and heavy ions. The near-term goal of research is new knowledge leading to the reduction of uncertainties in projection models. Risk projections involve a product of many biological and physical factors, each of which has a differential range of uncertainty due to lack of data and knowledge. The current model for projecting space radiation cancer risk relies on the three assumptions of linearity, additivity, and scaling along with the use of population averages. We describe uncertainty estimates for this model, and new experimental data that sheds light on the accuracy of the underlying assumptions. These methods make it possible to express risk management objectives in terms of quantitative metrics, i.e., the number of days in space without exceeding a given risk level within well defined confidence limits. The resulting methodology is applied to several human space exploration mission scenarios including lunar station, deep space outpost, and a Mars mission. Factors that dominate risk projection uncertainties and application of this approach to assess candidate mitigation approaches are described.

Assessing the Risk of Crew Injury Due to Dynamic Loads During Spaceflight

NASA Technical Reports Server (NTRS)

Somers, J. T.; Gernhardt, M.; Newby, N.

2014-01-01

Spaceflight requires tremendous amounts of energy to achieve Earth orbit and to attain escape velocity for interplanetary missions. Although the majority of the energy is managed in such a way as to limit the accelerations on the crew, several mission phases may result in crew exposure to dynamic loads. In the automotive industry, risk of serious injury can be tolerated because the probability of a crash is remote each time a person enters a vehicle, resulting in a low total risk of injury. For spaceflight, the level of acceptable injury risk must be lower to achieve a low total risk of injury because the dynamic loads are expected on each flight. To mitigate the risk of injury due to dynamic loads, the NASA Human Research Program has developed a research plan to inform the knowledge gaps and develop relevant tools for assessing injury risk. The risk of injury due to dynamic loads can be further subdivided into extrinsic and intrinsic risk factors. Extrinsic risk factors include the vehicle dynamic profile, seat and restraint design, and spacesuit design. Human tolerance to loads varies considerably depending on the direction, amplitude, and rise-time of acceleration therefore the orientation of the body to the dynamic vector is critical to determining crew risk of injury. Although a particular vehicle dynamic profile may be safe for a particular design, the seat, restraint, and suit designs can affect the risk of injury due to localized effects. In addition, characteristics intrinsic to the crewmember may also contribute to the risk of injury, such as crewmember sex, age, anthropometry, and deconditioning due to spaceflight, and each astronaut may have a different risk profile because of these factors. The purpose of the research plan is to address any knowledge gaps in the risk factors to mitigate injury risk. Methods for assessing injury risk have been well documented in other analogous industries and include human volunteer testing, human exposure to dynamic environments, post-mortem human subject (PMHS) testing, animal testing, anthropomorphic test devices (ATD), dynamic models of the human, numerical models of ATDs, and numerical models of the human. Each has inherent strengths and limitations. For example, human volunteer testing is advantageous because a population can be selected that is similar to the astronaut corps; however, because of the inherent ethical limitations, only sub-injurious conditions can be tested. PMHSs can be tested in a variety of conditions including injurious levels, but the responses are not completely analogous to living human subjects. In addition, it is exceedingly difficult to select a PMHS population that is similar to the astronaut corps. ATDs are currently widely used in the automotive industry and military because they are highly repeatable and durable. Unfortunately, because they are mechanical models of the human body, the biofidelity of the responses are limited to dynamic conditions used to validate the ATD. Numerical models of the ATD, in addition to the strengths and limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional limitations for ATDs, are easy to use for a variety of designs before a design is fabricated, but also have additional uncertainty. Dynamic models are simple and easy to use, but do not account for localized effects of the seat and suit. Finally, numerical models of the human have the potential to have the most advantages; however, the current models are not validated for the conditions expected during spaceflight. To properly assess spaceflight conditions with numerical human models, human data would be needed to optimize the model responses for those conditions. Using the appropriate assessment method with the knowledge gained for each risk factor, an appropriate approach for mitigating the risk of injury due to dynamic loads can be developed ensuring crew safety in future NASA vehicles.

Health Risk Assessment of Dietary Cadmium Intake: Do Current Guidelines Indicate How Much is Safe?

PubMed

Satarug, Soisungwan; Vesey, David A; Gobe, Glenda C

2017-03-01

Cadmium (Cd), a food-chain contaminant, is a significant health hazard. The kidney is one of the primary sites of injury after chronic Cd exposure. Kidney-based risk assessment establishes the urinary Cd threshold at 5.24 μg/g creatinine, and tolerable dietary intake of Cd at 62 μg/day per 70-kg person. However, cohort studies show that dietary Cd intake below a threshold limit and that tolerable levels may increase the risk of death from cancer, cardiovascular disease, and Alzheimer's disease. We evaluated if the current tolerable dietary Cd intake guideline and urinary Cd threshold limit provide sufficient health protection. Staple foods constitute 40-60% of total dietary Cd intake by average consumers. Diets high in shellfish, crustaceans, mollusks, spinach, and offal add to dietary Cd sources. Modeling studies predict the current tolerable dietary intake corresponding to urinary Cd of 0.70-1.85 μg/g creatinine in men and 0.95-3.07 μg/g creatinine in women. Urinary Cd levels of < 1 μg/g creatinine were associated with progressive kidney dysfunction and peripheral vascular disease. A urinary Cd of 0.37 μg/g creatinine was associated with breast cancer, whereas dietary Cd of 16-31.5 μg/day was associated with 25-94% increase in risk of estrogen receptor-positive breast cancer. Modeling shows that dietary intake levels for Cd exceed the levels associated with kidney damage and many other adverse outcomes. Thus, the threshold level of urinary Cd should be re-evaluated. A more restrictive dietary intake guideline would afford enhanced health protection from this pervasive toxic metal. Citation: Satarug S, Vesey DA, Gobe GC. 2017. Health risk assessment of dietary cadmium intake: do current guidelines indicate how much is safe? Environ Health Perspect 125:284-288; http://dx.doi.org/10.1289/EHP108.

Risk assessment of bovine spongiform encephalopathy transmission through bone graft material derived from bovine bone used for dental applications.

PubMed

Sogal, A; Tofe, A J

1999-09-01

Several commercial products are currently available for clinical application as bone graft substitutes. These products can be broadly classified into two categories: synthetic and natural. Bovine bone is a popular source for several of the natural bone substitutes. The availability of bovine derived xenogenic bone substitutes has made it possible to avoid traumatic and expensive secondary surgery to obtain autogenous bone once thought essential for effective bone replacement. While autogenous bone still remains the undisputed "gold standard" in bone grafting, the realization that bone requirement in several clinical applications is as effectively met by xenografts has lead to their widespread use. But the convenience of using xenografts is tempered by the possibility of disease transmission from cattle to humans. The recent incidents of bovine spongiform encephalopathies (BSE) in humans have underscored this likelihood. In this paper, we report a risk analysis performed to assess the possibility of such disease transmission from a commercially available bone graft substitute (BGS) that is popularly used in clinical dentistry. An extensive review of current literature on the status of risk assessment of BSE transmission was conducted, and two risk assessment models were identified as applicable to the present study. Risk assessment models developed by the German Federal Ministry of Health and by the Pharmaceutical Research and Manufacturers Association of America were applied to BGS. Results from the analyses conducted using both models showed that the risk of disease (BSE) transmission from BGS was negligible and could be attributed to the stringent protocols followed in sourcing and processing of the raw bovine bone used in the commercial product. Based on the risk analysis, it is evident that the risk of BSE infection from BGS is several orders of magnitude less than that posed by the risk of death related to, lightning, tornadoes, or similar remote events. However, this low risk can only be maintained as long as an effective and active risk management program is implemented in operations that involve processing xenogenic tissue for human use.

Potential impacts of radon, terrestrial gamma and cosmic rays on childhood leukemia in France: a quantitative risk assessment.

PubMed

Laurent, Olivier; Ancelet, Sophie; Richardson, David B; Hémon, Denis; Ielsch, Géraldine; Demoury, Claire; Clavel, Jacqueline; Laurier, Dominique

2013-05-01

Previous epidemiological studies and quantitative risk assessments (QRA) have suggested that natural background radiation may be a cause of childhood leukemia. The present work uses a QRA approach to predict the excess risk of childhood leukemia in France related to three components of natural radiation: radon, cosmic rays and terrestrial gamma rays, using excess relative and absolute risk models proposed by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR). Both models were developed from the Life Span Study (LSS) of Japanese A-bomb survivors. Previous risk assessments were extended by considering uncertainties in radiation-related leukemia risk model parameters as part of this process, within a Bayesian framework. Estimated red bone marrow doses cumulated during childhood by the average French child due to radon, terrestrial gamma and cosmic rays are 4.4, 7.5 and 4.3 mSv, respectively. The excess fractions of cases (expressed as percentages) associated with these sources of natural radiation are 20 % [95 % credible interval (CI) 0-68 %] and 4 % (95 % CI 0-11 %) under the excess relative and excess absolute risk models, respectively. The large CIs, as well as the different point estimates obtained under these two models, highlight the uncertainties in predictions of radiation-related childhood leukemia risks. These results are only valid provided that models developed from the LSS can be transferred to the population of French children and to chronic natural radiation exposures, and must be considered in view of the currently limited knowledge concerning other potential risk factors for childhood leukemia. Last, they emphasize the need for further epidemiological investigations of the effects of natural radiation on childhood leukemia to reduce uncertainties and help refine radiation protection standards.

The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model.

PubMed

Binenbaum, Gil; Ying, Gui-Shuang; Quinn, Graham E; Huang, Jiayan; Dreiseitl, Stephan; Antigua, Jules; Foroughi, Negar; Abbasi, Soraya

2012-12-01

To develop a birth weight (BW), gestational age (GA), and postnatal-weight gain retinopathy of prematurity (ROP) prediction model in a cohort of infants meeting current screening guidelines. Multivariate logistic regression was applied retrospectively to data from infants born with BW less than 1501 g or GA of 30 weeks or less at a single Philadelphia hospital between January 1, 2004, and December 31, 2009. In the model, BW, GA, and daily weight gain rate were used repeatedly each week to predict risk of Early Treatment of Retinopathy of Prematurity type 1 or 2 ROP. If risk was above a cut-point level, examinations would be indicated. Of 524 infants, 20 (4%) had type 1 ROP and received laser treatment; 28 (5%) had type 2 ROP. The model (Children's Hospital of Philadelphia [CHOP]) accurately predicted all infants with type 1 ROP; missed 1 infant with type 2 ROP, who did not require laser treatment; and would have reduced the number of infants requiring examinations by 49%. Raising the cut point to miss one type 1 ROP case would have reduced the need for examinations by 79%. Using daily weight measurements to calculate weight gain rate resulted in slightly higher examination reduction than weekly measurements. The BW-GA-weight gain CHOP ROP model demonstrated accurate ROP risk assessment and a large reduction in the number of ROP examinations compared with current screening guidelines. As a simple logistic equation, it can be calculated by hand or represented as a nomogram for easy clinical use. However, larger studies are needed to achieve a highly precise estimate of sensitivity prior to clinical application.

Juvenile Offenders' Alcohol and Marijuana Trajectories: Risk and Protective Factor Effects in the Context of Time in a Supervised Facility

ERIC Educational Resources Information Center

Mauricio, Anne M.; Little, Michelle; Chassin, Laurie; Knight, George P.; Piquero, Alex R.; Losoya, Sandra H.; Vargas-Chanes, Delfino

2009-01-01

The current study modeled trajectories of substance use from ages 15 to 20 among 1,095 male serious juvenile offenders (M age = 16.54; 42% African-American, 34% Latino, 20% European-American, and 4% other ethnic/racial backgrounds) and prospectively predicted trajectories from risk and protective factors before and after controlling for time spent…

Preparing At-Risk Youth for a Changing World: Revisiting a Person-in-Context Model for Transition to Employment

ERIC Educational Resources Information Center

DeLuca, Christopher; Godden, Lorraine; Hutchinson, Nancy L.; Versnel, Joan

2015-01-01

Background: The current global cohort of youth has been called "a generation at-risk", marked by a dramatic rise in youth who are not in employment, education or training programmes. In 2010, youth were three times as likely as adults to be unemployed, with youth unemployment worsening in 2012 and 2013. Accordingly, there is an urgent…

Assessment of the Risk of Ebola Importation to Australia

PubMed Central

Cope, Robert C.; Cassey, Phillip; Hugo, Graeme J.; Ross, Joshua V.

2014-01-01

Objectives: To assess the risk of Ebola importation to Australia during the first six months of 2015, based upon the current outbreak in West Africa. Methodology: We assessed the risk under two distinct scenarios: (i) assuming that significant numbers of cases of Ebola remain confined to Guinea, Liberia and Sierra Leone, and using historic passenger arrival data into Australia; and, (ii) assuming potential secondary spread based upon international flight data. A model appropriate to each scenario is developed, and parameterised using passenger arrival card or international flight data, and World Health Organisation case data from West Africa. These models were constructed based on WHO Ebola outbreak data as at 17 October 2014 and 3 December 2014. An assessment of the risk under each scenario is reported. On 27 October 2014 the Australian Government announced a policy change, that visas from affected countries would be refused/cancelled, and the predicted effect of this policy change is reported. Results: The current probability of at least one case entering Australia by 1 July 2015, having travelled directly from West Africa with historic passenger arrival rates into Australia, is 0.34. Under the new Australian Government policy of restricting visas from affected countries (as of 27 October 2014), the probability of at least one case entering Australia by 1 July 2015 is reduced to 0.16. The probability of at least one case entering Australia by 1 July 2015 via an outbreak from a secondary source country is approximately 0.12. Conclusions: Our models suggest that if the transmission of Ebola remains unchanged, it is possible that a case will enter Australia within the first six months of 2015, either directly from West Africa (even when current visa restrictions are considered), or via secondary outbreaks elsewhere. Government and medical authorities should be prepared to respond to this eventuality. Control measures within West Africa over recent months have contributed to a reduction in projected risk of a case entering Australia. A significant further reduction of the rate at which Ebola is proliferating in West Africa, and control of the disease if and when it proliferates elsewhere, will continue to result in substantially lower risk of the disease entering Australia. PMID:25685627

Avian collision risk models for wind energy impact assessments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Masden, E.A., E-mail: elizabeth.masden@uhi.ac.uk; Cook, A.S.C.P.

2016-01-15

With the increasing global development of wind energy, collision risk models (CRMs) are routinely used to assess the potential impacts of wind turbines on birds. We reviewed and compared the avian collision risk models currently available in the scientific literature, exploring aspects such as the calculation of a collision probability, inclusion of stationary components e.g. the tower, angle of approach and uncertainty. 10 models were cited in the literature and of these, all included a probability of collision of a single bird colliding with a wind turbine during passage through the rotor swept area, and the majority included a measuremore » of the number of birds at risk. 7 out of the 10 models calculated the probability of birds colliding, whilst the remainder used a constant. We identified four approaches to calculate the probability of collision and these were used by others. 6 of the 10 models were deterministic and included the most frequently used models in the UK, with only 4 including variation or uncertainty in some way, the most recent using Bayesian methods. Despite their appeal, CRMs have their limitations and can be ‘data hungry’ as well as assuming much about bird movement and behaviour. As data become available, these assumptions should be tested to ensure that CRMs are functioning to adequately answer the questions posed by the wind energy sector. - Highlights: • We highlighted ten models available to assess avian collision risk. • Only 4 of the models included variability or uncertainty. • Collision risk models have limitations and can be ‘data hungry’. • It is vital that the most appropriate model is used for a given task.« less

Modeling and Quantification of Team Performance in Human Reliability Analysis for Probabilistic Risk Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jeffrey C. JOe; Ronald L. Boring

Probabilistic Risk Assessment (PRA) and Human Reliability Assessment (HRA) are important technical contributors to the United States (U.S.) Nuclear Regulatory Commission’s (NRC) risk-informed and performance based approach to regulating U.S. commercial nuclear activities. Furthermore, all currently operating commercial NPPs in the U.S. are required by federal regulation to be staffed with crews of operators. Yet, aspects of team performance are underspecified in most HRA methods that are widely used in the nuclear industry. There are a variety of "emergent" team cognition and teamwork errors (e.g., communication errors) that are 1) distinct from individual human errors, and 2) important to understandmore » from a PRA perspective. The lack of robust models or quantification of team performance is an issue that affects the accuracy and validity of HRA methods and models, leading to significant uncertainty in estimating HEPs. This paper describes research that has the objective to model and quantify team dynamics and teamwork within NPP control room crews for risk informed applications, thereby improving the technical basis of HRA, which improves the risk-informed approach the NRC uses to regulate the U.S. commercial nuclear industry.« less

Geographic risk modeling of childhood cancer relative to county-level crops, hazardous air pollutants and population density characteristics in Texas.

PubMed

Thompson, James A; Carozza, Susan E; Zhu, Li

2008-09-25

Childhood cancer has been linked to a variety of environmental factors, including agricultural activities, industrial pollutants and population mixing, but etiologic studies have often been inconclusive or inconsistent when considering specific cancer types. More specific exposure assessments are needed. It would be helpful to optimize future studies to incorporate knowledge of high-risk locations or geographic risk patterns. The objective of this study was to evaluate potential geographic risk patterns in Texas accounting for the possibility that multiple cancers may have similar geographic risks patterns. A spatio-temporal risk modeling approach was used, whereby 19 childhood cancer types were modeled as potentially correlated within county-years. The standard morbidity ratios were modeled as functions of intensive crop production, intensive release of hazardous air pollutants, population density, and rapid population growth. There was supportive evidence for elevated risks for germ cell tumors and "other" gliomas in areas of intense cropping and for hepatic tumors in areas of intense release of hazardous air pollutants. The risk for Hodgkin lymphoma appeared to be reduced in areas of rapidly growing population. Elevated spatial risks included four cancer histotypes, "other" leukemias, Central Nervous System (CNS) embryonal tumors, CNS other gliomas and hepatic tumors with greater than 95% likelihood of elevated risks in at least one county. The Bayesian implementation of the Multivariate Conditional Autoregressive model provided a flexible approach to the spatial modeling of multiple childhood cancer histotypes. The current study identified geographic factors supporting more focused studies of germ cell tumors and "other" gliomas in areas of intense cropping, hepatic cancer near Hazardous Air Pollutant (HAP) release facilities and specific locations with increased risks for CNS embryonal tumors and for "other" leukemias. Further study should be performed to evaluate potentially lower risk for Hodgkin lymphoma and malignant bone tumors in counties with rapidly growing population.

The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

PubMed

Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

2015-01-01

Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P < .001 and P = .001, respectively). Discrimination remained excellent when only elective procedures were considered. There was no evidence of miscalibration by Hosmer-Lemeshow analysis. We have developed accurate models to assess risk of in-hospital mortality after AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Climate change and health modeling: horses for courses.

PubMed

Ebi, Kristie L; Rocklöv, Joacim

2014-01-01

Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome ('horses for courses'). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

The relationship between the effect of pravastatin and risk factors for coronary heart disease in Japanese patients with hypercholesterolemia.

PubMed

Ishikawa, Toshitsugu; Mizuno, Kyoichi; Nakaya, Noriaki; Ohashi, Yasuo; Tajima, Naoko; Kushiro, Toshio; Teramoto, Tamio; Uchiyama, Shinichiro; Nakamura, Haruo

2008-10-01

Several epidemiologic studies in Japan have shown the risk factors for coronary heart disease (CHD) in the general population. The present analysis determined the risk factors for CHD in the MEGA Study, a large primary prevention trial with pravastatin in Japanese with hypercholesterolemia. The relationship between each baseline characteristic and the risk of CHD for the 5-year study period were evaluated using the Cox proportional hazard model. The multivariable predictors of CHD were sex, age, high-density lipoprotein-cholesterol (HDL-C), diabetes mellitus (DM), hypertension (HT), and history of smoking. Serum total and low-density lipoprotein-cholesterol were not independent risk factors for CHD in the current analysis. In addition, the effect of pravastatin was evaluated by subgroups in each risk factor using the interaction in a Cox model. Diet plus pravastatin treatment reduced CHD risk by 14-43% compared with diet alone, regardless of the presence or absence of risk factors. The risk factors for CHD were sex, age, DM, HT, smoking, and low HDL-C in the MEGA Study. The pravastatin treatment was effective for reducing the risk of CHD, regardless of the presence of risk factors.

Modeling risk for child abuse and harsh parenting in families with depressed and substance-abusing parents.

PubMed

Kelley, Michelle L; Lawrence, Hannah R; Milletich, Robert J; Hollis, Brittany F; Henson, James M

2015-05-01

Children with substance abusing parents are at considerable risk for child maltreatment. The current study applied an actor-partner interdependence model to examine how father only (n=52) and dual couple (n=33) substance use disorder, as well as their depressive symptomology influenced parents' own (actor effects) and the partner's (partner effects) overreactivity in disciplinary interactions with their children, as well as their risk for child maltreatment. Parents completed the Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977), the overreactivity subscale from the Parenting Scale (Arnold, O'Leary, Wolff, & Acker, 1993), and the Brief Child Abuse Potential Inventory (Ondersma, Chaffin, Mullins, & LeBreton, 2005). Results of multigroup structural equation models revealed that a parent's own report of depressive symptoms predicted their risk for child maltreatment in both father SUD and dual SUD couples. Similarly, a parent's report of their own depressive symptoms predicted their overreactivity in disciplinary encounters both in father SUD and dual SUD couples. In all models, partners' depressive symptoms did not predict their partner's risk for child maltreatment or overreactivity. Findings underscore the importance of a parent's own level of depressive symptoms in their risk for child maltreatment and for engaging in overreactivity during disciplinary episodes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modeling Risk for Child Abuse and Harsh Parenting in Families with Depressed and Substance-abusing Parents

PubMed Central

Kelley, Michelle L.; Lawrence, Hannah R.; Milletich, Robert R.; Hollis, Brittany F.; Henson, James M.

2015-01-01

Children with substance abusing parents are at considerable risk for child maltreatment. The current study applied an actor-partner interdependence model to examine how father only (n = 52) and dual couple (n = 33) substance use disorder, as well as their depressive symptomology influenced parents’ own (actor effects) and the partner's (partner effects) overreactivity in disciplinary interactions with their children, as well as their risk for child maltreatment. Parents completed the Center for Epidemiologic Studies Depression Scale (CES-D; Radloff, 1977), the overreactivity subscale from the Parenting Scale (Arnold, O'Leary, Wolff, & Acker, 1993), and the Brief Child Abuse Potential Inventory (Ondersma, Chaffin, Mullins, & LeBreton, 2005). Results of multigroup structural equation models revealed that a parent's own report of depressive symptoms predicted their risk for child maltreatment in both father SUD and dual SUD couples. Similarly, a parent's report of their own depressive symptoms predicted their overreactivity in disciplinary encounters both in father SUD and dual SUD couples. In all models, partners’ depressive symptoms did not predict their partner's risk for child maltreatment or overreactivity. Findings underscore the importance of a parent's own levels of depressive symptoms in their risk for child maltreatment and for engaging in overreactivity during disciplinary episodes. PMID:25724658

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland.

PubMed

Li, Sen; Gilbert, Lucy; Harrison, Paula A; Rounsevell, Mark D A

2016-03-01

Lyme disease is the most prevalent vector-borne disease in the temperate Northern Hemisphere. The abundance of infected nymphal ticks is commonly used as a Lyme disease risk indicator. Temperature can influence the dynamics of disease by shaping the activity and development of ticks and, hence, altering the contact pattern and pathogen transmission between ticks and their host animals. A mechanistic, agent-based model was developed to study the temperature-driven seasonality of Ixodes ricinus ticks and transmission of Borrelia burgdorferi sensu lato across mainland Scotland. Based on 12-year averaged temperature surfaces, our model predicted that Lyme disease risk currently peaks in autumn, approximately six weeks after the temperature peak. The risk was predicted to decrease with increasing altitude. Increases in temperature were predicted to prolong the duration of the tick questing season and expand the risk area to higher altitudinal and latitudinal regions. These predicted impacts on tick population ecology may be expected to lead to greater tick-host contacts under climate warming and, hence, greater risks of pathogen transmission. The model is useful in improving understanding of the spatial determinants and system mechanisms of Lyme disease pathogen transmission and its sensitivity to temperature changes. © 2016 The Author(s).

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

PubMed Central

Gilbert, Lucy; Harrison, Paula A.; Rounsevell, Mark D. A.

2016-01-01

Lyme disease is the most prevalent vector-borne disease in the temperate Northern Hemisphere. The abundance of infected nymphal ticks is commonly used as a Lyme disease risk indicator. Temperature can influence the dynamics of disease by shaping the activity and development of ticks and, hence, altering the contact pattern and pathogen transmission between ticks and their host animals. A mechanistic, agent-based model was developed to study the temperature-driven seasonality of Ixodes ricinus ticks and transmission of Borrelia burgdorferi sensu lato across mainland Scotland. Based on 12-year averaged temperature surfaces, our model predicted that Lyme disease risk currently peaks in autumn, approximately six weeks after the temperature peak. The risk was predicted to decrease with increasing altitude. Increases in temperature were predicted to prolong the duration of the tick questing season and expand the risk area to higher altitudinal and latitudinal regions. These predicted impacts on tick population ecology may be expected to lead to greater tick–host contacts under climate warming and, hence, greater risks of pathogen transmission. The model is useful in improving understanding of the spatial determinants and system mechanisms of Lyme disease pathogen transmission and its sensitivity to temperature changes. PMID:27030039

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes, These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

An improved approach for flight readiness certification: Methodology for failure risk assessment and application examples, volume 1

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with engineering analysis to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in engineering analyses of failure phenomena, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which engineering analysis models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. Conventional engineering analysis models currently employed for design of failure prediction are used in this methodology. The PFA methodology is described and examples of its application are presented. Conventional approaches to failure risk evaluation for spaceflight systems are discussed, and the rationale for the approach taken in the PFA methodology is presented. The statistical methods, engineering models, and computer software used in fatigue failure mode applications are thoroughly documented.

Multimethod prediction of physical parent-child aggression risk in expectant mothers and fathers with Social Information Processing theory.

PubMed

Rodriguez, Christina M; Smith, Tamika L; Silvia, Paul J

2016-01-01

The Social Information Processing (SIP) model postulates that parents undergo a series of stages in implementing physical discipline that can escalate into physical child abuse. The current study utilized a multimethod approach to investigate whether SIP factors can predict risk of parent-child aggression (PCA) in a diverse sample of expectant mothers and fathers. SIP factors of PCA attitudes, negative child attributions, reactivity, and empathy were considered as potential predictors of PCA risk; additionally, analyses considered whether personal history of PCA predicted participants' own PCA risk through its influence on their attitudes and attributions. Findings indicate that, for both mothers and fathers, history influenced attitudes but not attributions in predicting PCA risk, and attitudes and attributions predicted PCA risk; empathy and reactivity predicted negative child attributions for expectant mothers, but only reactivity significantly predicted attributions for expectant fathers. Path models for expectant mothers and fathers were remarkably similar. Overall, the findings provide support for major aspects of the SIP model. Continued work is needed in studying the progression of these factors across time for both mothers and fathers as well as the inclusion of other relevant ecological factors to the SIP model. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of local acceptance of a radioactive waste disposal facility.

PubMed

Chung, Ji Bum; Kim, Hong-Kew; Rho, Sam Kew

2008-08-01

Like many other countries in the world, Korea has struggled to site a facility for radioactive waste for almost 30 years because of the strong opposition from local residents. Finally, in 2005, Gyeongju was established as the first Korean site for a radioactive waste facility. The objectives of this research are to verify Gyeongju citizens' average level of risk perception of a radioactive waste disposal facility as compared to other risks, and to explore the best model for predicting respondents' acceptance level using variables related to cost-benefit, risk perception, and political process. For this purpose, a survey is conducted among Gyeongju residents, the results of which are as follows. First, the local residents' risk perception of an accident in a radioactive waste disposal facility is ranked seventh among a total of 13 risks, which implies that nuclear-related risk is not perceived very highly by Gyeongju residents; however, its characteristics are still somewhat negative. Second, the comparative regression analyses show that the cost-benefit and political process models are more suitable for explaining the respondents' level of acceptance than the risk perception model. This may be the result of the current economic depression in Gyeongju, residents' familiarity with the nuclear industry, or cultural characteristics of risk tolerance.

A Critique of Recent Epidemiologic Studies of Cancer Mortality Among Nuclear Workers.

PubMed

Scott, Bobby R

2018-01-01

Current justification by linear no-threshold (LNT) cancer risk model advocates for its use in low-dose radiation risk assessment is now mainly based on results from flawed and unreliable epidemiologic studies that manufacture small risk increases (ie, phantom risks). Four such studies of nuclear workers, essentially carried out by the same group of epidemiologists, are critiqued in this article. Three of the studies that forcibly applied the LNT model (inappropriate null hypothesis) to cancer mortality data and implicated increased mortality risk from any radiation exposure, no matter how small the dose, are demonstrated to manufacture risk increases for doses up to 100 mSv (or 100 mGy). In a study where risk reduction (hormetic effect/adaptive response) was implicated for nuclear workers, it was assumed by the researchers to relate to a "strong healthy worker effect" with no consideration of the possibility that low radiation doses may help prevent cancer mortality (which is consistent with findings from basic radiobiological research). It was found with basic research that while large radiation doses suppress our multiple natural defenses (barriers) against cancer, these barriers are enhanced by low radiation doses, thereby decreasing cancer risk, essentially rendering the LNT model to be inconsistent with the data.

Smoking and elevated blood pressure are the most important risk factors for subarachnoid hemorrhage in the Asia-Pacific region: an overview of 26 cohorts involving 306,620 participants.

PubMed

Feigin, Valery; Parag, Varsha; Lawes, Carlene M M; Rodgers, Anthony; Suh, Il; Woodward, Mark; Jamrozik, Konrad; Ueshima, Hirotsugu

2005-07-01

The cause of subarachnoid hemorrhage (SAH) is poorly understood and there are few large cohort studies of risk factors for SAH. We investigated the risk of SAH mortality and morbidity associated with common cardiovascular risk factors in the Asia-Pacific region and examined whether the strengths of these associations were different in Asian and Australasian (predominantly white) populations. Cohort studies were identified from Internet electronic databases, searches of proceedings of meetings, and personal communication. Hazard ratios (HRs) for systolic blood pressure (SBP), current smoking, total serum cholesterol, body mass index (BMI), and alcohol drinking were calculated from Cox models that were stratified by sex and cohort and adjusted for age at risk. Individual participant data from 26 prospective cohort studies (total number of participants 306,620) that reported incident cases of SAH (fatal and/or nonfatal) were available for analysis. During the median follow-up period of 8.2 years, a total of 236 incident cases of SAH were observed. Current smoking (HR, 2.4; 95% CI, 1.8 to 3.4) and SBP >140 mm Hg (HR, 2.0; 95% CI, 1.5 to 2.7) were significant and independent risk factors for SAH. Attributable risks of SAH associated with current smoking and elevated SBP (> or =140 mm Hg) were 29% and 19%, respectively. There were no significant associations between the risk of SAH and cholesterol, BMI, or drinking alcohol. The strength of the associations of the common cardiovascular risk factors with the risk of SAH did not differ much between Asian and Australasian regions. Cigarette smoking and SBP are the most important risk factors for SAH in the Asia-Pacific region.

Risk assessment of the introduction of porcine reproductive and respiratory syndrome virus via boar semen into Switzerland as an example of a PRRSV-free country.

PubMed

Nathues, C; Zimmerli, U; Hauser, R; Nathues, H; Grosse Beilage, E; Schüpbach-Regula, G

2014-12-01

Switzerland is currently porcine reproductive and respiratory syndrome virus (PRRSV) free, but semen imports from PRRSV-infected European countries are increasing. As the virus can be transmitted via semen, for example, when a free boar stud becomes infected, and the risk of its import in terms of PRRSV introduction is unknown, the annual probability to accidentally import the virus into Switzerland was estimated in a risk assessment. A quantitative stochastic model was set up with data comprised by import figures of 2010, interviews with boar stud owners and expert opinion. It resulted in an annual median number of 0.18 imported ejaculates (= imported semen doses from one collection from one donor) from PRRSV-infected boars. Hence, one infected ejaculate would be imported every 6 years and infect a mean of 10 sows. These results suggest that under current circumstances, there is a substantial risk of PRRSV introduction into Switzerland via imported boar semen and that measures to enhance safety of imports should be taken. The time from infection of a previously negative boar stud to its detection had the highest impact on the number of imported 'positive' ejaculates. Therefore, emphasis should be placed on PRRSV monitoring protocols in boar studs. Results indicated that a substantial increase in safety could only be achieved with much tighter sampling protocols than currently performed. Generally, the model could easily be customized for other applications like other countries or regions or even sow farms that want to estimate their risk when purchasing semen from a particular boar stud. © 2013 Blackwell Verlag GmbH.

Modelling the Geographical Range of a Species with Variable Life-History

PubMed Central

Macfadyen, Sarina; Kriticos, Darren J.

2012-01-01

We show how a climatic niche model can be used to describe the potential geographic distribution of a pest species with variable life-history, and illustrate how to estimate biogeographic pest threats that vary across space. The models were used to explore factors that affect pest risk (irrigation and presences of host plant). A combination of current distribution records and published experimental data were used to construct separate models for the asexual and sexual lineages of Rhopalosiphum padi (Linnaeus) (Hemiptera: Aphididae). The two models were combined with knowledge of host plant presence to classify the global pest risk posed by R. padi. Whilst R. padi has a relatively limited area in which sexual lineages can persist year round, a much larger area is suitable for transient sexual and asexual lineages to exist. The greatest risk of establishment of persistent sexual and asexual populations is in areas with warm temperate climates. At the global scale the models show very little difference in risk patterns between natural rainfall and irrigation scenarios, but in Australia, the amount of land suitable for persistent asexual and transient sexual populations decreases (by 20%) if drought stress is no longer alleviated by irrigation. This approach proved useful for modelling the potential distribution of a species that has a variable life-history. We were able to use the model outputs to examine factors such as irrigation practices and host plant presence that altered the nature (transient or permanent) and extent of pest risk. The composite niche maps indicate pest risk in terms that are useful to both biosecurity agencies and pest managers. PMID:22808133

An Expert Map of Gambling Risk Perception.

PubMed

Spurrier, Michael; Blaszczynski, Alexander; Rhodes, Paul

2015-12-01

The purpose of the current study was to investigate the moderating or mediating role played by risk perception in decision-making, gambling behaviour, and disordered gambling aetiology. Eleven gambling expert clinicians and researchers completed a semi-structured interview derived from mental models and grounded theory methodologies. Expert interview data was used to construct a comprehensive expert mental model 'map' detailing risk-perception related factors contributing to harmful or safe gambling. Systematic overlapping processes of data gathering and analysis were used to iteratively extend, saturate, test for exception, and verify concepts and emergent themes. Findings indicated that experts considered idiosyncratic beliefs among gamblers result in overall underestimates of risk and loss, insufficient prioritization of needs, and planning and implementation of risk management strategies. Additional contextual factors influencing use of risk information (reinforcement and learning; mental states, environmental cues, ambivalence; and socio-cultural and biological variables) acted to shape risk perceptions and increase vulnerabilities to harm or disordered gambling. It was concluded that understanding the nature, extent and processes by which risk perception predisposes an individual to maintain gambling despite adverse consequences can guide the content of preventative educational responsible gambling campaigns.

Stroke survivors' endorsement of a "stress belief model" of stroke prevention predicts control of risk factors for recurrent stroke.

PubMed

Phillips, L Alison; Tuhrim, Stanley; Kronish, Ian M; Horowitz, Carol R

2014-01-01

Perceptions that stress causes and stress-reduction controls hypertension have been associated with poorer blood pressure (BP) control in hypertension populations. The current study investigated these "stress-model perceptions" in stroke survivors regarding prevention of recurrent stroke and the influence of these perceptions on patients' stroke risk factor control. Stroke and transient ischemic attack survivors (N=600) participated in an in-person interview in which they were asked about their beliefs regarding control of future stroke; BP and cholesterol were measured directly after the interview. Counter to expectations, patients who endorsed a "stress-model" but not a "medication-model" of stroke prevention were in better control of their stroke risk factors (BP and cholesterol) than those who endorsed a medication-model but not a stress-model of stroke prevention (OR for poor control=.54, Wald statistic=6.07, p=.01). This result was not explained by between group differences in patients' reported medication adherence. The results have implications for theory and practice, regarding the role of stress belief models and acute cardiac events, compared to chronic hypertension.

Radiation Hormesis: Historical Perspective and Implications for Low-Dose Cancer Risk Assessment

PubMed Central

Vaiserman, Alexander M.

2010-01-01

Current guidelines for limiting exposure of humans to ionizing radiation are based on the linear-no-threshold (LNT) hypothesis for radiation carcinogenesis under which cancer risk increases linearly as the radiation dose increases. With the LNT model even a very small dose could cause cancer and the model is used in establishing guidelines for limiting radiation exposure of humans. A slope change at low doses and dose rates is implemented using an empirical dose and dose rate effectiveness factor (DDREF). This imposes usually unacknowledged nonlinearity but not a threshold in the dose-response curve for cancer induction. In contrast, with the hormetic model, low doses of radiation reduce the cancer incidence while it is elevated after high doses. Based on a review of epidemiological and other data for exposure to low radiation doses and dose rates, it was found that the LNT model fails badly. Cancer risk after ordinarily encountered radiation exposure (medical X-rays, natural background radiation, etc.) is much lower than projections based on the LNT model and is often less than the risk for spontaneous cancer (a hormetic response). Understanding the mechanistic basis for hormetic responses will provide new insights about both risks and benefits from low-dose radiation exposure. PMID:20585444

Integrating ecological risk assessments across levels of organization using the Franklin-Noss model of biodiversity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brugger, K.E.; Tiebout, H.M. III

1994-12-31

Wildlife toxicologists pioneered methodologies for assessing ecological risk to nontarget species. Historically, ecological risk assessments (ERAS) focused on a limited array of species and were based on a relatively few population-level endpoints (mortality, reproduction). Currently, risk assessment models are becoming increasingly complex that factor in multi-species interactions (across trophic levels) and utilize an increasingly diverse number of ecologically significant endpoints. This trend suggests the increasing importance of safeguarding not only populations of individual species, but also the overall integrity of the larger biotic systems that support them. In this sense, ERAs are in alignment with Conservation Biology, an applied sciencemore » of ecological knowledge used to conserve biodiversity. A theoretical conservation biology model could be incorporated in ERAs to quantify impacts to biodiversity (structure, function or composition across levels of biological organization). The authors suggest that the Franklin-Noss model for evaluating biodiversity, with its nested, hierarchical approach, may provide a suitable paradigm for assessing and integrating the ecological risk that chemical contaminants pose to biological systems from the simplest levels (genotypes, individual organisms) to the most complex levels of organization (communities and ecosystems). The Franklin-Noss model can accommodate the existing ecotoxicological database and, perhaps more importantly, indicate new areas in which critical endpoints should be identified and investigated.« less

Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems

PubMed Central

Garber, Kristina; Odenkirchen, Edward

2017-01-01

Insecticide usage in the United States is ubiquitous in urban, suburban, and rural environments. There is accumulating evidence that insecticides adversely affect non-target wildlife species, including birds, causing mortality, reproductive impairment, and indirect effects through loss of prey base, and the type and magnitude of such effects differs by chemical class, or mode of action. In evaluating data for an insecticide registration application and for registration review, scientists at the United States Environmental Protection Agency (USEPA) assess the fate of the insecticide and the risk the insecticide poses to the environment and non-target wildlife. Current USEPA risk assessments for pesticides generally rely on endpoints from laboratory based toxicity studies focused on groups of individuals and do not directly assess population-level endpoints. In this paper, we present a mechanistic model, which allows risk assessors to estimate the effects of insecticide exposure on the survival and seasonal productivity of birds known to forage in agricultural fields during their breeding season. This model relies on individual-based toxicity data and translates effects into endpoints meaningful at the population level (i.e., magnitude of mortality and reproductive impairment). The model was created from two existing USEPA avian risk assessment models, the Terrestrial Investigation Model (TIM v.3.0) and the Markov Chain Nest Productivity model (MCnest). The integrated TIM/MCnest model was used to assess the relative risk of 12 insecticides applied via aerial spray to control corn pests on a suite of 31 avian species known to forage in cornfields in agroecosystems of the Midwest, USA. We found extensive differences in risk to birds among insecticides, with chlorpyrifos and malathion (organophosphates) generally posing the greatest risk, and bifenthrin and λ-cyhalothrin (pyrethroids) posing the least risk. Comparative sensitivity analysis across the 31 species showed that ecological trait parameters related to the timing of breeding and reproductive output per nest attempt offered the greatest explanatory power for predicting the magnitude of risk. An important advantage of TIM/MCnest is that it allows risk assessors to rationally combine both acute (lethal) and chronic (reproductive) effects into a single unified measure of risk. PMID:28467479

Incorporating Stroke Severity Into Hospital Measures of 30-Day Mortality After Ischemic Stroke Hospitalization.

PubMed

Schwartz, Jennifer; Wang, Yongfei; Qin, Li; Schwamm, Lee H; Fonarow, Gregg C; Cormier, Nicole; Dorsey, Karen; McNamara, Robert L; Suter, Lisa G; Krumholz, Harlan M; Bernheim, Susannah M

2017-11-01

The Centers for Medicare & Medicaid Services publicly reports a hospital-level stroke mortality measure that lacks stroke severity risk adjustment. Our objective was to describe novel measures of stroke mortality suitable for public reporting that incorporate stroke severity into risk adjustment. We linked data from the American Heart Association/American Stroke Association Get With The Guidelines-Stroke registry with Medicare fee-for-service claims data to develop the measures. We used logistic regression for variable selection in risk model development. We developed 3 risk-standardized mortality models for patients with acute ischemic stroke, all of which include the National Institutes of Health Stroke Scale score: one that includes other risk variables derived only from claims data (claims model); one that includes other risk variables derived from claims and clinical variables that could be obtained from electronic health record data (hybrid model); and one that includes other risk variables that could be derived only from electronic health record data (electronic health record model). The cohort used to develop and validate the risk models consisted of 188 975 hospital admissions at 1511 hospitals. The claims, hybrid, and electronic health record risk models included 20, 21, and 9 risk-adjustment variables, respectively; the C statistics were 0.81, 0.82, and 0.79, respectively (as compared with the current publicly reported model C statistic of 0.75); the risk-standardized mortality rates ranged from 10.7% to 19.0%, 10.7% to 19.1%, and 10.8% to 20.3%, respectively; the median risk-standardized mortality rate was 14.5% for all measures; and the odds of mortality for a high-mortality hospital (+1 SD) were 1.51, 1.52, and 1.52 times those for a low-mortality hospital (-1 SD), respectively. We developed 3 quality measures that demonstrate better discrimination than the Centers for Medicare & Medicaid Services' existing stroke mortality measure, adjust for stroke severity, and could be implemented in a variety of settings. © 2017 American Heart Association, Inc.

Mechanistic modeling of insecticide risks to breeding birds in North American agroecosystems.

PubMed

Etterson, Matthew; Garber, Kristina; Odenkirchen, Edward

2017-01-01

Insecticide usage in the United States is ubiquitous in urban, suburban, and rural environments. There is accumulating evidence that insecticides adversely affect non-target wildlife species, including birds, causing mortality, reproductive impairment, and indirect effects through loss of prey base, and the type and magnitude of such effects differs by chemical class, or mode of action. In evaluating data for an insecticide registration application and for registration review, scientists at the United States Environmental Protection Agency (USEPA) assess the fate of the insecticide and the risk the insecticide poses to the environment and non-target wildlife. Current USEPA risk assessments for pesticides generally rely on endpoints from laboratory based toxicity studies focused on groups of individuals and do not directly assess population-level endpoints. In this paper, we present a mechanistic model, which allows risk assessors to estimate the effects of insecticide exposure on the survival and seasonal productivity of birds known to forage in agricultural fields during their breeding season. This model relies on individual-based toxicity data and translates effects into endpoints meaningful at the population level (i.e., magnitude of mortality and reproductive impairment). The model was created from two existing USEPA avian risk assessment models, the Terrestrial Investigation Model (TIM v.3.0) and the Markov Chain Nest Productivity model (MCnest). The integrated TIM/MCnest model was used to assess the relative risk of 12 insecticides applied via aerial spray to control corn pests on a suite of 31 avian species known to forage in cornfields in agroecosystems of the Midwest, USA. We found extensive differences in risk to birds among insecticides, with chlorpyrifos and malathion (organophosphates) generally posing the greatest risk, and bifenthrin and λ-cyhalothrin (pyrethroids) posing the least risk. Comparative sensitivity analysis across the 31 species showed that ecological trait parameters related to the timing of breeding and reproductive output per nest attempt offered the greatest explanatory power for predicting the magnitude of risk. An important advantage of TIM/MCnest is that it allows risk assessors to rationally combine both acute (lethal) and chronic (reproductive) effects into a single unified measure of risk.

Food Web Bioaccumulation Model for Resident Killer Whales from the Northeastern Pacific Ocean as a Tool for the Derivation of PBDE-Sediment Quality Guidelines.

PubMed

Alava, Juan José; Ross, Peter S; Gobas, Frank A P C

2016-01-01

Resident killer whale populations in the NE Pacific Ocean are at risk due to the accumulation of pollutants, including polybrominated diphenyl ethers (PBDEs). To assess the impact of PBDEs in water and sediments in killer whale critical habitat, we developed a food web bioaccumulation model. The model was designed to estimate PBDE concentrations in killer whales based on PBDE concentrations in sediments and the water column throughout a lifetime of exposure. Calculated and observed PBDE concentrations exceeded the only toxicity reference value available for PBDEs in marine mammals (1500 μg/kg lipid) in southern resident killer whales but not in northern resident killer whales. Temporal trends (1993-2006) for PBDEs observed in southern resident killer whales showed a doubling time of ≈5 years. If current sediment quality guidelines available in Canada for polychlorinated biphenyls are applied to PBDEs, it can be expected that PBDE concentrations in killer whales will exceed available toxicity reference values by a large margin. Model calculations suggest that a PBDE concentration in sediments of approximately 1.0 μg/kg dw produces PBDE concentrations in resident killer whales that are below the current toxicity reference value for 95 % of the population, with this value serving as a precautionary benchmark for a management-based approach to reducing PBDE health risks to killer whales. The food web bioaccumulation model may be a useful risk management tool in support of regulatory protection for killer whales.

Catastrophe risk data scoping for disaster risk finance in Asia

NASA Astrophysics Data System (ADS)

Millinship, Ian; Revilla-Romero, Beatriz

2017-04-01

Developing countries across Latin America, Africa, and Asia are some of the most exposed to natural catastrophes in the world. Over the last 20 years, Asia has borne almost half the estimated global economic cost of natural disasters - around 53billion annually. Losses from natural disasters can damage growth and hamper economic development and unlike in developed countries where risk is reallocated through re/insurance, typically these countries rely on budget reallocations and donor assistance in order to attempt to meet financing needs. There is currently an active international dialogue on the need to increase access to disaster risk financing solutions in Asia. The World Bank-GFDRR Disaster Risk Financing and Insurance Program with financial support from the Rockefeller Foundation, is currently working to develop regional options for disaster risk financing for developing countries in Asia. The first stage of this process has been to evaluate available catastrophe data suitable to support the design and implementation of disaster risk financing mechanisms in selected Asian countries. This project was carried out by a consortium of JBA Risk Management, JBA Consulting, ImageCat and Cat Risk Intelligence. The project focuses on investigating potential data sources for fourteen selected countries in Asia, for flood, tropical cyclone, earthquake and drought perils. The project was carried out under four stages. The first phase focused to identify and catalogue live/dynamic hazard data sources such as hazard gauging networks, or earth observations datasets which could be used to inform a parametric trigger. Live data sources were identified that provide credibility, transparency, independence, frequent reporting, consistency and stability. Data were catalogued at regional level, and prioritised at local level for five countries: Bangladesh, Indonesia, Pakistan, Sri Lanka and Viet Nam. The second phase was to identify, catalogue and evaluate catastrophe risk models that could quantify risk and provide a view of risk to support design and pricing of parametric disaster risk financing mechanisms. The third stage was to evaluate the usability of data sources and catastrophe models, and to develop index prototypes to outline how data and catastrophe models could be combined using local, regional and global data sources. Finally, the project identified priorities for investment to support the collection, analysis and evaluation of natural catastrophes in order to support disaster risk financing.

Breast Cancer Risk Prediction and Mammography Biopsy Decisions

PubMed Central

Armstrong, Katrina; Handorf, Elizabeth A.; Chen, Jinbo; Demeter, Mirar N. Bristol

2012-01-01

Background Controversy continues about screening mammography, in part because of the risk of false-negative and false-positive mammograms. Pre-test breast cancer risk factors may improve the positive and negative predictive value of screening. Purpose To create a model that estimates the potential impact of pre-test risk prediction using clinical and genomic information on the reclassification of women with abnormal mammograms (BI-RADS3 and BI-RADS4 [Breast Imaging-Reporting and Data System]) above and below the threshold for breast biopsy. Methods The current study modeled 1-year breast cancer risk in women with abnormal screening mammograms using existing data on breast cancer risk factors, 12 validated breast cancer single nucleotide polymorphisms (SNPs), and probability of cancer given the BI-RADS category. Examination was made of reclassification of women above and below biopsy thresholds of 1%, 2%, and 3% risk. The Breast Cancer Surveillance Consortium data were collected from 1996 to 2002. Data analysis was conducted in 2010 and 2011. Results Using a biopsy risk threshold of 2% and the standard risk factor model, 5% of women with a BI-RADS3 mammogram had a risk above the threshold, and 3% of women with BIRADS4A mammograms had a risk below the threshold. The addition of 12 SNPs in the model resulted in 8% of women with a BI-RADS3 mammogram above the threshold for biopsy and 7% of women with BI-RADS4A mammograms below the threshold. Conclusions The incorporation of pre-test breast cancer risk factors could change biopsy decisions for a small proportion of women with abnormal mammograms. The greatest impact comes from standard breast cancer risk factors. PMID:23253645

Electrical utilities model for determining electrical distribution capacity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, R. L.

1997-09-03

In its simplest form, this model was to obtain meaningful data on the current state of the Site`s electrical transmission and distribution assets, and turn this vast collection of data into useful information. The resulting product is an Electrical Utilities Model for Determining Electrical Distribution Capacity which provides: current state of the electrical transmission and distribution systems; critical Hanford Site needs based on outyear planning documents; decision factor model. This model will enable Electrical Utilities management to improve forecasting requirements for service levels, budget, schedule, scope, and staffing, and recommend the best path forward to satisfy customer demands at themore » minimum risk and least cost to the government. A dynamic document, the model will be updated annually to reflect changes in Hanford Site activities.« less

Risk adjustment alternatives in paying for behavioral health care under Medicaid.

PubMed Central

Ettner, S L; Frank, R G; McGuire, T G; Hermann, R C

2001-01-01

OBJECTIVE: To compare the performance of various risk adjustment models in behavioral health applications such as setting mental health and substance abuse (MH/SA) capitation payments or overall capitation payments for populations including MH/SA users. DATA SOURCES/STUDY DESIGN: The 1991-93 administrative data from the Michigan Medicaid program were used. We compared mean absolute prediction error for several risk adjustment models and simulated the profits and losses that behavioral health care carve outs and integrated health plans would experience under risk adjustment if they enrolled beneficiaries with a history of MH/SA problems. Models included basic demographic adjustment, Adjusted Diagnostic Groups, Hierarchical Condition Categories, and specifications designed for behavioral health. PRINCIPAL FINDINGS: Differences in predictive ability among risk adjustment models were small and generally insignificant. Specifications based on relatively few MH/SA diagnostic categories did as well as or better than models controlling for additional variables such as medical diagnoses at predicting MH/SA expenditures among adults. Simulation analyses revealed that among both adults and minors considerable scope remained for behavioral health care carve outs to make profits or losses after risk adjustment based on differential enrollment of severely ill patients. Similarly, integrated health plans have strong financial incentives to avoid MH/SA users even after adjustment. CONCLUSIONS: Current risk adjustment methodologies do not eliminate the financial incentives for integrated health plans and behavioral health care carve-out plans to avoid high-utilizing patients with psychiatric disorders. PMID:11508640

LinkIT: a ludic elicitation game for eliciting risk perceptions.

PubMed

Cao, Yan; McGill, William L

2013-06-01

The mental models approach, a leading strategy to develop risk communications, involves a time- and labor-intensive interview process and a lengthy questionnaire to elicit group-level risk perceptions. We propose that a similarity ratings approach for structural knowledge elicitation can be adopted to assist the risk mental models approach. The LinkIT game, inspired by games with a purpose (GWAP) technology, is a ludic elicitation tool designed to elicit group understanding of the relations between risk factors in a more enjoyable and productive manner when compared to traditional approaches. That is, consistent with the idea of ludic elicitation, LinkIT was designed to make the elicitation process fun and enjoyable in the hopes of increasing participation and data quality in risk studies. Like the mental models approach, the group mental model obtained via the LinkIT game can hence be generated and represented in a form of influence diagrams. In order to examine the external validity of LinkIT, we conducted a study to compare its performance with respect to a more conventional questionnaire-driven approach. Data analysis results conclude that the two group mental models elicited from the two approaches are similar to an extent. Yet, LinkIT was more productive and enjoyable than the questionnaire. However, participants commented that the current game has some usability concerns. This presentation summarizes the design and evaluation of the LinkIT game and suggests areas for future work. © 2012 Society for Risk Analysis.

Assessing the public health risk of microbial intrusion events in distribution systems: conceptual model, available data, and challenges.

PubMed

Besner, Marie-Claude; Prévost, Michèle; Regli, Stig

2011-01-01

Low and negative pressure events in drinking water distribution systems have the potential to result in intrusion of pathogenic microorganisms if an external source of contamination is present (e.g., nearby leaking sewer main) and there is a pathway for contaminant entry (e.g., leaks in drinking water main). While the public health risk associated with such events is not well understood, quantitative microbial risk assessment can be used to estimate such risk. A conceptual model is provided and the state of knowledge, current assumptions, and challenges associated with the conceptual model parameters are presented. This review provides a characterization of the causes, magnitudes, durations and frequencies of low/negative pressure events; pathways for pathogen entry; pathogen occurrence in external sources of contamination; volumes of water that may enter through the different pathways; fate and transport of pathogens from the pathways of entry to customer taps; pathogen exposure to populations consuming the drinking water; and risk associated with pathogen exposure. Copyright © 2010 Elsevier Ltd. All rights reserved.

Filling Terrorism Gaps: VEOs, Evaluating Databases, and Applying Risk Terrain Modeling to Terrorism

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagan, Ross F.

2016-08-29

This paper aims to address three issues: the lack of literature differentiating terrorism and violent extremist organizations (VEOs), terrorism incident databases, and the applicability of Risk Terrain Modeling (RTM) to terrorism. Current open source literature and publicly available government sources do not differentiate between terrorism and VEOs; furthermore, they fail to define them. Addressing the lack of a comprehensive comparison of existing terrorism data sources, a matrix comparing a dozen terrorism databases is constructed, providing insight toward the array of data available. RTM, a method for spatial risk analysis at a micro level, has some applicability to terrorism research, particularlymore » for studies looking at risk indicators of terrorism. Leveraging attack data from multiple databases, combined with RTM, offers one avenue for closing existing research gaps in terrorism literature.« less

Optimal control of an invasive species using a reaction-diffusion model and linear programming

USGS Publications Warehouse

Bonneau, Mathieu; Johnson, Fred A.; Smith, Brian J.; Romagosa, Christina M.; Martin, Julien; Mazzotti, Frank J.

2017-01-01

Managing an invasive species is particularly challenging as little is generally known about the species’ biological characteristics in its new habitat. In practice, removal of individuals often starts before the species is studied to provide the information that will later improve control. Therefore, the locations and the amount of control have to be determined in the face of great uncertainty about the species characteristics and with a limited amount of resources. We propose framing spatial control as a linear programming optimization problem. This formulation, paired with a discrete reaction-diffusion model, permits calculation of an optimal control strategy that minimizes the remaining number of invaders for a fixed cost or that minimizes the control cost for containment or protecting specific areas from invasion. We propose computing the optimal strategy for a range of possible model parameters, representing current uncertainty on the possible invasion scenarios. Then, a best strategy can be identified depending on the risk attitude of the decision-maker. We use this framework to study the spatial control of the Argentine black and white tegus (Salvator merianae) in South Florida. There is uncertainty about tegu demography and we considered several combinations of model parameters, exhibiting various dynamics of invasion. For a fixed one-year budget, we show that the risk-averse strategy, which optimizes the worst-case scenario of tegus’ dynamics, and the risk-neutral strategy, which optimizes the expected scenario, both concentrated control close to the point of introduction. A risk-seeking strategy, which optimizes the best-case scenario, focuses more on models where eradication of the species in a cell is possible and consists of spreading control as much as possible. For the establishment of a containment area, assuming an exponential growth we show that with current control methods it might not be possible to implement such a strategy for some of the models that we considered. Including different possible models allows an examination of how the strategy is expected to perform in different scenarios. Then, a strategy that accounts for the risk attitude of the decision-maker can be designed.

A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales.

PubMed

McAllister, Katherine S L; Ludman, Peter F; Hulme, William; de Belder, Mark A; Stables, Rodney; Chowdhary, Saqib; Mamas, Mamas A; Sperrin, Matthew; Buchan, Iain E

2016-05-01

The current risk model for percutaneous coronary intervention (PCI) in the UK is based on outcomes of patients treated in a different era of interventional cardiology. This study aimed to create a new model, based on a contemporary cohort of PCI treated patients, which would: predict 30 day mortality; provide good discrimination; and be well calibrated across a broad risk-spectrum. The model was derived from a training dataset of 336,433 PCI cases carried out between 2007 and 2011 in England and Wales, with 30 day mortality provided by record linkage. Candidate variables were selected on the basis of clinical consensus and data quality. Procedures in 2012 were used to perform temporal validation of the model. The strongest predictors of 30-day mortality were: cardiogenic shock; dialysis; and the indication for PCI and the degree of urgency with which it was performed. The model had an area under the receiver operator characteristic curve of 0.85 on the training data and 0.86 on validation. Calibration plots indicated a good model fit on development which was maintained on validation. We have created a contemporary model for PCI that encompasses a range of clinical risk, from stable elective PCI to emergency primary PCI and cardiogenic shock. The model is easy to apply and based on data reported in national registries. It has a high degree of discrimination and is well calibrated across the risk spectrum. The examination of key outcomes in PCI audit can be improved with this risk-adjusted model. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Transmission of Bacterial Zoonotic Pathogens between Pets and Humans: The Role of Pet Food.

PubMed

Lambertini, Elisabetta; Buchanan, Robert L; Narrod, Clare; Pradhan, Abani K

2016-01-01

Recent Salmonella outbreaks associated with dry pet food and treats raised the level of concern for these products as vehicle of pathogen exposure for both pets and their owners. The need to characterize the microbiological and risk profiles of this class of products is currently not supported by sufficient specific data. This systematic review summarizes existing data on the main variables needed to support an ingredients-to-consumer quantitative risk model to (1) describe the microbial ecology of bacterial pathogens in the dry pet food production chain, (2) estimate pet exposure to pathogens through dry food consumption, and (3) assess human exposure and illness incidence due to contact with pet food and pets in the household. Risk models populated with the data here summarized will provide a tool to quantitatively address the emerging public health concerns associated with pet food and the effectiveness of mitigation measures. Results of such models can provide a basis for improvements in production processes, risk communication to consumers, and regulatory action.

Forecasting the Future Risk of Barmah Forest Virus Disease under Climate Change Scenarios in Queensland, Australia

PubMed Central

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Background Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. Methods/Principal Findings We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. Conclusions/Significance We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland. PMID:23690959

Information risk and security modeling

NASA Astrophysics Data System (ADS)

Zivic, Predrag

2005-03-01

This research paper presentation will feature current frameworks to addressing risk and security modeling and metrics. The paper will analyze technical level risk and security metrics of Common Criteria/ISO15408, Centre for Internet Security guidelines, NSA configuration guidelines and metrics used at this level. Information IT operational standards view on security metrics such as GMITS/ISO13335, ITIL/ITMS and architectural guidelines such as ISO7498-2 will be explained. Business process level standards such as ISO17799, COSO and CobiT will be presented with their control approach to security metrics. Top level, the maturity standards such as SSE-CMM/ISO21827, NSA Infosec Assessment and CobiT will be explored and reviewed. For each defined level of security metrics the research presentation will explore the appropriate usage of these standards. The paper will discuss standards approaches to conducting the risk and security metrics. The research findings will demonstrate the need for common baseline for both risk and security metrics. This paper will show the relation between the attribute based common baseline and corporate assets and controls for risk and security metrics. IT will be shown that such approach spans over all mentioned standards. The proposed approach 3D visual presentation and development of the Information Security Model will be analyzed and postulated. Presentation will clearly demonstrate the benefits of proposed attributes based approach and defined risk and security space for modeling and measuring.

Affect, risk perception, and the use of cigarettes and e-cigarettes: a population study of U.S. adults.

PubMed

Popova, Lucy; Owusu, Daniel; Weaver, Scott R; Kemp, Catherine B; Mertz, C K; Pechacek, Terry F; Slovic, Paul

2018-03-22

Tobacco companies argue that the decision to smoke is made by well-informed rational adults who have considered all the risks and benefits of smoking. Yet in promoting their products, the tobacco industry frequently relies on affect, portraying their products as part of a desirable lifestyle. Research examining the roles of affect and perceived risks in smoking has been scant and non-existent for novel tobacco products, such as electronic cigarettes (e-cigarettes). We examined the relationship between affect, perceived risk, and current use for cigarettes and e-cigarettes in 2015 in a nationally representative sample of 5398 U.S. adults who were aware of e-cigarettes. Participants held various affective associations with tobacco products, and affect towards cigarettes was more negative than affect towards e-cigarettes. Using structural equation modeling (SEM), affect towards cigarettes and e-cigarettes was associated with cigarette smoking and e-cigarette use respectively, and these associations were both direct and partially mediated by risk perceptions towards smoking and e-cigarette use. More positive affect towards cigarettes or e-cigarettes was associated with lower perceived risks, which in turn was associated with higher odds of being a current cigarette or e-cigarette user. In developing models explaining tobacco use behavior, or in creating public communication campaigns aimed at curbing tobacco use, it is useful to focus not only on the reason based predictors, such as perceptions of risks and benefits, but also on affective predictors. Educational efforts aimed at further smoking reductions should highlight and reinforce negative images and associations with cigarettes.

Prospective Study of Maternal Alcohol Intake During Pregnancy or Lactation and Risk of Childhood Asthma: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; DeRoo, Lisa A.; Håberg, Siri E.; Magnus, Per; Nafstad, Per; Nystad, Wenche; London, Stephanie J.

2014-01-01

Background Many women drink during pregnancy and lactation despite recommendations to abstain. In animals, alcohol exposure during pregnancy and lactation influences lung and immune development, plausibly increasing risk of asthma and lower respiratory tract infections (LRTIs). Studies in humans are few. Methods In the Norwegian Mother and Child Cohort Study, we examined maternal alcohol intake during pregnancy and lactation in relation to risk of current asthma at 36 months (49,138 children), recurrent LRTIs by 36 months (39,791 children) and current asthma at seven years (13,253 children). Mothers reported frequency and amount of alcohol intake each trimester and the first three months following delivery. We calculated adjusted relative risks (aRR), comparing children of drinkers to non-drinkers, using Generalized Linear Models. Results A total of 31.8% of mothers consumed alcohol during first trimester, 9.7% during second trimester and 15.6% during third trimester. Infrequent and low-dose prenatal alcohol exposure showed a modest statistically significant inverse association with current asthma at 36 months (aRRs ~0.85). No association was seen with the highest alcohol intakes during the first trimester when alcohol consumption was most common. Relative risks of maternal alcohol intake during pregnancy with recurrent LRTIs were ~1, with sporadic differences in risk for some metrics of intake, but without any consistent pattern. For current asthma at seven years, similar inverse associations were seen as with current asthma at 36 month but were not statistically significant. Among children breastfed throughout the first three months of life, maternal alcohol intake during this time was not significantly associated with any of the three outcomes. Conclusion The low levels of alcohol exposure during pregnancy or lactation observed in this cohort were not associated with increased risk of asthma or recurrent LRTIs. The slight inverse associations of infrequent or low-dose prenatal alcohol exposure with asthma may not be causal. PMID:24460824

Allostasis and the human brain: Integrating models of stress from the social and life sciences

PubMed Central

Ganzel, Barbara L.; Morris, Pamela A.; Wethington, Elaine

2009-01-01

We draw on the theory of allostasis to develop an integrative model of the current stress process that highlights the brain as a dynamically adapting interface between the changing environment and the biological self. We review evidence that the core emotional regions of the brain constitute the primary mediator of the well-established association between stress and health, as well as the neural focus of “wear and tear” due to ongoing adaptation. This mediation, in turn, allows us to model the interplay over time between context, current stressor exposure, internal regulation of bodily processes, and health outcomes. We illustrate how this approach facilitates the integration of current findings in human neuroscience and genetics with key constructs from stress models from the social and life sciences, with implications for future research and the design of interventions targeting individuals at risk. PMID:20063966

The credibility challenge for global fluvial flood risk analysis

NASA Astrophysics Data System (ADS)

Trigg, M. A.; Birch, C. E.; Neal, J. C.; Bates, P. D.; Smith, A.; Sampson, C. C.; Yamazaki, D.; Hirabayashi, Y.; Pappenberger, F.; Dutra, E.; Ward, P. J.; Winsemius, H. C.; Salamon, P.; Dottori, F.; Rudari, R.; Kappes, M. S.; Simpson, A. L.; Hadzilacos, G.; Fewtrell, T. J.

2016-09-01

Quantifying flood hazard is an essential component of resilience planning, emergency response, and mitigation, including insurance. Traditionally undertaken at catchment and national scales, recently, efforts have intensified to estimate flood risk globally to better allow consistent and equitable decision making. Global flood hazard models are now a practical reality, thanks to improvements in numerical algorithms, global datasets, computing power, and coupled modelling frameworks. Outputs of these models are vital for consistent quantification of global flood risk and in projecting the impacts of climate change. However, the urgency of these tasks means that outputs are being used as soon as they are made available and before such methods have been adequately tested. To address this, we compare multi-probability flood hazard maps for Africa from six global models and show wide variation in their flood hazard, economic loss and exposed population estimates, which has serious implications for model credibility. While there is around 30%-40% agreement in flood extent, our results show that even at continental scales, there are significant differences in hazard magnitude and spatial pattern between models, notably in deltas, arid/semi-arid zones and wetlands. This study is an important step towards a better understanding of modelling global flood hazard, which is urgently required for both current risk and climate change projections.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 1: Methodology and applications

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflight systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for designs failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

An improved approach for flight readiness certification: Probabilistic models for flaw propagation and turbine blade failure. Volume 2: Software documentation

NASA Technical Reports Server (NTRS)

Moore, N. R.; Ebbeler, D. H.; Newlin, L. E.; Sutharshana, S.; Creager, M.

1992-01-01

An improved methodology for quantitatively evaluating failure risk of spaceflights systems to assess flight readiness and identify risk control measures is presented. This methodology, called Probabilistic Failure Assessment (PFA), combines operating experience from tests and flights with analytical modeling of failure phenomena to estimate failure risk. The PFA methodology is of particular value when information on which to base an assessment of failure risk, including test experience and knowledge of parameters used in analytical modeling, is expensive or difficult to acquire. The PFA methodology is a prescribed statistical structure in which analytical models that characterize failure phenomena are used conjointly with uncertainties about analysis parameters and/or modeling accuracy to estimate failure probability distributions for specific failure modes. These distributions can then be modified, by means of statistical procedures of the PFA methodology, to reflect any test or flight experience. State-of-the-art analytical models currently employed for design, failure prediction, or performance analysis are used in this methodology. The rationale for the statistical approach taken in the PFA methodology is discussed, the PFA methodology is described, and examples of its application to structural failure modes are presented. The engineering models and computer software used in fatigue crack growth and fatigue crack initiation applications are thoroughly documented.

An Overview of Quantitative Risk Assessment of Space Shuttle Propulsion Elements

NASA Technical Reports Server (NTRS)

Safie, Fayssal M.

1998-01-01

Since the Space Shuttle Challenger accident in 1986, NASA has been working to incorporate quantitative risk assessment (QRA) in decisions concerning the Space Shuttle and other NASA projects. One current major NASA QRA study is the creation of a risk model for the overall Space Shuttle system. The model is intended to provide a tool to estimate Space Shuttle risk and to perform sensitivity analyses/trade studies, including the evaluation of upgrades. Marshall Space Flight Center (MSFC) is a part of the NASA team conducting the QRA study; MSFC responsibility involves modeling the propulsion elements of the Space Shuttle, namely: the External Tank (ET), the Solid Rocket Booster (SRB), the Reusable Solid Rocket Motor (RSRM), and the Space Shuttle Main Engine (SSME). This paper discusses the approach that MSFC has used to model its Space Shuttle elements, including insights obtained from this experience in modeling large scale, highly complex systems with a varying availability of success/failure data. Insights, which are applicable to any QRA study, pertain to organizing the modeling effort, obtaining customer buy-in, preparing documentation, and using varied modeling methods and data sources. Also provided is an overall evaluation of the study results, including the strengths and the limitations of the MSFC QRA approach and of qRA technology in general.

The Global Earthquake Model and Disaster Risk Reduction

NASA Astrophysics Data System (ADS)

Smolka, A. J.

2015-12-01

Advanced, reliable and transparent tools and data to assess earthquake risk are inaccessible to most, especially in less developed regions of the world while few, if any, globally accepted standards currently allow a meaningful comparison of risk between places. The Global Earthquake Model (GEM) is a collaborative effort that aims to provide models, datasets and state-of-the-art tools for transparent assessment of earthquake hazard and risk. As part of this goal, GEM and its global network of collaborators have developed the OpenQuake engine (an open-source software for hazard and risk calculations), the OpenQuake platform (a web-based portal making GEM's resources and datasets freely available to all potential users), and a suite of tools to support modelers and other experts in the development of hazard, exposure and vulnerability models. These resources are being used extensively across the world in hazard and risk assessment, from individual practitioners to local and national institutions, and in regional projects to inform disaster risk reduction. Practical examples for how GEM is bridging the gap between science and disaster risk reduction are: - Several countries including Switzerland, Turkey, Italy, Ecuador, Papua-New Guinea and Taiwan (with more to follow) are computing national seismic hazard using the OpenQuake-engine. In some cases these results are used for the definition of actions in building codes. - Technical support, tools and data for the development of hazard, exposure, vulnerability and risk models for regional projects in South America and Sub-Saharan Africa. - Going beyond physical risk, GEM's scorecard approach evaluates local resilience by bringing together neighborhood/community leaders and the risk reduction community as a basis for designing risk reduction programs at various levels of geography. Actual case studies are Lalitpur in the Kathmandu Valley in Nepal and Quito/Ecuador. In agreement with GEM's collaborative approach, all projects are undertaken with strong involvement of local scientific and risk reduction communities. Open-source software and careful documentation of the methodologies create full transparency of the modelling process, so that results can be reproduced any time by third parties.

Estimating Radiation Dose Metrics for Patients Undergoing Tube Current Modulation CT Scans

NASA Astrophysics Data System (ADS)

McMillan, Kyle Lorin

Computed tomography (CT) has long been a powerful tool in the diagnosis of disease, identification of tumors and guidance of interventional procedures. With CT examinations comes the concern of radiation exposure and the associated risks. In order to properly understand those risks on a patient-specific level, organ dose must be quantified for each CT scan. Some of the most widely used organ dose estimates are derived from fixed tube current (FTC) scans of a standard sized idealized patient model. However, in current clinical practice, patient size varies from neonates weighing just a few kg to morbidly obese patients weighing over 200 kg, and nearly all CT exams are performed with tube current modulation (TCM), a scanning technique that adjusts scanner output according to changes in patient attenuation. Methods to account for TCM in CT organ dose estimates have been previously demonstrated, but these methods are limited in scope and/or restricted to idealized TCM profiles that are not based on physical observations and not scanner specific (e.g. don't account for tube limits, scanner-specific effects, etc.). The goal of this work was to develop methods to estimate organ doses to patients undergoing CT scans that take into account both the patient size as well as the effects of TCM. This work started with the development and validation of methods to estimate scanner-specific TCM schemes for any voxelized patient model. An approach was developed to generate estimated TCM schemes that match actual TCM schemes that would have been acquired on the scanner for any patient model. Using this approach, TCM schemes were then generated for a variety of body CT protocols for a set of reference voxelized phantoms for which TCM information does not currently exist. These are whole body patient models representing a variety of sizes, ages and genders that have all radiosensitive organs identified. TCM schemes for these models facilitated Monte Carlo-based estimates of fully-, partially- and indirectly-irradiated organ dose from TCM CT exams. By accounting for the effects of patient size in the organ dose estimates, a comprehensive set of patient-specific dose estimates from TCM CT exams was developed. These patient-specific organ dose estimates from TCM CT exams will provide a more complete understanding of the dose impact and risks associated with modern body CT scanning protocols.

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

A prediction model for colon cancer surveillance data.

PubMed

Good, Norm M; Suresh, Krithika; Young, Graeme P; Lockett, Trevor J; Macrae, Finlay A; Taylor, Jeremy M G

2015-08-15

Dynamic prediction models make use of patient-specific longitudinal data to update individualized survival probability predictions based on current and past information. Colonoscopy (COL) and fecal occult blood test (FOBT) results were collected from two Australian surveillance studies on individuals characterized as high-risk based on a personal or family history of colorectal cancer. Motivated by a Poisson process, this paper proposes a generalized nonlinear model with a complementary log-log link as a dynamic prediction tool that produces individualized probabilities for the risk of developing advanced adenoma or colorectal cancer (AAC). This model allows predicted risk to depend on a patient's baseline characteristics and time-dependent covariates. Information on the dates and results of COLs and FOBTs were incorporated using time-dependent covariates that contributed to patient risk of AAC for a specified period following the test result. These covariates serve to update a person's risk as additional COL, and FOBT test information becomes available. Model selection was conducted systematically through the comparison of Akaike information criterion. Goodness-of-fit was assessed with the use of calibration plots to compare the predicted probability of event occurrence with the proportion of events observed. Abnormal COL results were found to significantly increase risk of AAC for 1 year following the test. Positive FOBTs were found to significantly increase the risk of AAC for 3 months following the result. The covariates that incorporated the updated test results were of greater significance and had a larger effect on risk than the baseline variables. Copyright © 2015 John Wiley & Sons, Ltd.

Integrated presentation of ecological risk from multiple stressors

PubMed Central

Goussen, Benoit; Price, Oliver R.; Rendal, Cecilie; Ashauer, Roman

2016-01-01

Current environmental risk assessments (ERA) do not account explicitly for ecological factors (e.g. species composition, temperature or food availability) and multiple stressors. Assessing mixtures of chemical and ecological stressors is needed as well as accounting for variability in environmental conditions and uncertainty of data and models. Here we propose a novel probabilistic ERA framework to overcome these limitations, which focusses on visualising assessment outcomes by construct-ing and interpreting prevalence plots as a quantitative prediction of risk. Key components include environmental scenarios that integrate exposure and ecology, and ecological modelling of relevant endpoints to assess the effect of a combination of stressors. Our illustrative results demonstrate the importance of regional differences in environmental conditions and the confounding interactions of stressors. Using this framework and prevalence plots provides a risk-based approach that combines risk assessment and risk management in a meaningful way and presents a truly mechanistic alternative to the threshold approach. Even whilst research continues to improve the underlying models and data, regulators and decision makers can already use the framework and prevalence plots. The integration of multiple stressors, environmental conditions and variability makes ERA more relevant and realistic. PMID:27782171

Risk prediction models for major adverse cardiac event (MACE) following percutaneous coronary intervention (PCI): A review

NASA Astrophysics Data System (ADS)

Manan, Norhafizah A.; Abidin, Basir

2015-02-01

Five percent of patients who went through Percutaneous Coronary Intervention (PCI) experienced Major Adverse Cardiac Events (MACE) after PCI procedure. Risk prediction of MACE following a PCI procedure therefore is helpful. This work describes a review of such prediction models currently in use. Literature search was done on PubMed and SCOPUS database. Thirty literatures were found but only 4 studies were chosen based on the data used, design, and outcome of the study. Particular emphasis was given and commented on the study design, population, sample size, modeling method, predictors, outcomes, discrimination and calibration of the model. All the models had acceptable discrimination ability (C-statistics >0.7) and good calibration (Hosmer-Lameshow P-value >0.05). Most common model used was multivariate logistic regression and most popular predictor was age.

Measuring the effect of fuel treatments on forest carbon using landscape risk analysis

Treesearch

A.A. Ager; M.A. Finney; A. McMahan; J. Carthcart

2010-01-01

Wildfire simulation modelling was used to examine whether fuel reduction treatments can potentially reduce future wildfire emissions and provide carbon benefits. In contrast to previous reports, the current study modelled landscape scale effects of fuel treatments on fire spread and intensity, and used a probabilistic framework to quantify wildfire effects on carbon...

Hostile Intent Attributions and Relational Aggression: The Moderating Roles of Emotional Sensitivity, Gender, and Victimization

ERIC Educational Resources Information Center

Mathieson, Lindsay C.; Murray-Close, Dianna; Crick, Nicki R.; Woods, Kathleen E.; Zimmer-Gembeck, Melanie; Geiger, Tasha C.; Morales, Julie R.

2011-01-01

The current study adopts a relational vulnerability model to examine the association between hostile attribution bias and relational aggression. Specifically, the relational vulnerability model implicates the interactive effects of a number of relational risk factors in the development of relational aggression. A sample of 635 3rd, 4th, and 5th…

77 FR 48192 - Self-Regulatory Organizations; Chicago Mercantile Exchange, Inc.; Notice of Filing of Proposed...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-13

... Liquidity Factor of Its Credit Default Swap Margin Methodology August 7, 2012. Pursuant to Section 19(b)(1... model. The liquidity margin component of the CME CDS margin model is designed to capture the risk... CDS Clearing Member. The current methodology for the liquidity factor is a function of a portfolio's...

Body Image as a Mediator of Non-Suicidal Self-Injury in Adolescents

ERIC Educational Resources Information Center

Muehlenkamp, Jennifer J.; Brausch, Amy M.

2012-01-01

Attitudes towards the body have been largely overlooked as a potential risk factor for adolescent non-suicidal self-injury (NSSI) despite theorizing that a negative body image may play a critical role in the development of this behavior. The current study used structural equation modeling to evaluate the fit of a theoretical model specifying body…

Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California

NASA Astrophysics Data System (ADS)

Delaney, C.; Hartman, R. K.; Mendoza, J.; Evans, K. M.; Evett, S.

2016-12-01

Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation or flow forecasts to inform the flood operations of reservoirs. Previous research and modeling for flood control reservoirs has shown that FIRO can reduce flood risk and increase water supply for many reservoirs. The risk-based method of FIRO presents a unique approach that incorporates flow forecasts made by NOAA's California-Nevada River Forecast Center (CNRFC) to model and assess risk of meeting or exceeding identified management targets or thresholds. Forecasted risk is evaluated against set risk tolerances to set reservoir flood releases. A water management model was developed for Lake Mendocino, a 116,500 acre-foot reservoir located near Ukiah, California. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United State Army Corps of Engineers and is operated by the Sonoma County Water Agency for water supply. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has been plagued with water supply reliability issues since 2007. FIRO is applied to Lake Mendocino by simulating daily hydrologic conditions from 1985 to 2010 in the Upper Russian River from Lake Mendocino to the City of Healdsburg approximately 50 miles downstream. The risk-based method is simulated using a 15-day, 61 member streamflow hindcast by the CNRFC. Model simulation results of risk-based flood operations demonstrate a 23% increase in average end of water year (September 30) storage levels over current operations. Model results show no increase in occurrence of flood damages for points downstream of Lake Mendocino. This investigation demonstrates that FIRO may be a viable flood control operations approach for Lake Mendocino and warrants further investigation through additional modeling and analysis.

Predictions of space radiation fatality risk for exploration missions

NASA Astrophysics Data System (ADS)

Cucinotta, Francis A.; To, Khiet; Cacao, Eliedonna

2017-05-01

In this paper we describe revisions to the NASA Space Cancer Risk (NSCR) model focusing on updates to probability distribution functions (PDF) representing the uncertainties in the radiation quality factor (QF) model parameters and the dose and dose-rate reduction effectiveness factor (DDREF). We integrate recent heavy ion data on liver, colorectal, intestinal, lung, and Harderian gland tumors with other data from fission neutron experiments into the model analysis. In an earlier work we introduced distinct QFs for leukemia and solid cancer risk predictions, and here we consider liver cancer risks separately because of the higher RBE's reported in mouse experiments compared to other tumors types, and distinct risk factors for liver cancer for astronauts compared to the U.S. population. The revised model is used to make predictions of fatal cancer and circulatory disease risks for 1-year deep space and International Space Station (ISS) missions, and a 940 day Mars mission. We analyzed the contribution of the various model parameter uncertainties to the overall uncertainty, which shows that the uncertainties in relative biological effectiveness (RBE) factors at high LET due to statistical uncertainties and differences across tissue types and mouse strains are the dominant uncertainty. NASA's exposure limits are approached or exceeded for each mission scenario considered. Two main conclusions are made: 1) Reducing the current estimate of about a 3-fold uncertainty to a 2-fold or lower uncertainty will require much more expansive animal carcinogenesis studies in order to reduce statistical uncertainties and understand tissue, sex and genetic variations. 2) Alternative model assumptions such as non-targeted effects, increased tumor lethality and decreased latency at high LET, and non-cancer mortality risks from circulatory diseases could significantly increase risk estimates to several times higher than the NASA limits.

Preconception healthcare delivery at a population level: construction of public health models of preconception care.

PubMed

Shannon, Geordan D; Alberg, Corinna; Nacul, Luis; Pashayan, Nora

2014-08-01

A key challenge of preconception healthcare is identifying how it can best be delivered at a population level. To review current strategies of preconception healthcare, explore methods of preconception healthcare delivery, and develop public health models which reflect different preconception healthcare pathways. Preconception care strategies, programmes and evaluations were identified through a review of Medline and Embase databases. Search terms included: preconception, pre-pregnancy, intervention, primary care, healthcare, model, delivery, program, prevention, trial, effectiveness, congenital disorders OR abnormalities, evaluation, assessment, impact. Inclusion criteria for review articles were: (1) English, (2) human subjects, (3) women of childbearing age, (4) 1980–current data, (5) all countries, (6) both high risk and universal approaches, (7) guidelines or recommendations, (8) opinion articles, (9) experimental studies. Exclusion criteria were: (1) non-human subjects, (2) non-English, (3) outside of the specified timeframe, (4) articles on male healthcare. The results of the literature review were synthesised into public health models of care: (1) primary care; (2) hospital-based and inter-conception care; (3) specific preconception care clinics; and, (4) community outreach. Fifteen evaluations of preconception care were identified. Community programmes demonstrated a significant impact on substance use, folic acid supplementation, diabetes optimization, and hyperphenylalaninemia. An ideal preconception visits entail risk screening, education, and intervention if indicated. Subsequently, four public health models were developed synthesizing preconception care delivery at a population level. Heterogeneity of risk factors, health systems and strategies of care reflect the lack of consensus about the best way to deliver preconception care. The proposed models aim to reflect differing aspects of preconception healthcare delivery.

Current Status and Future Challenges in Risk-Based Radiation Engineering

NASA Technical Reports Server (NTRS)

Pellish, Jonathan A.

2017-01-01

This presentation covers the basis and challenges for radiation effects in electronic systems. The three main types of radiation effects in electronics are: 1) total ionizing dose (TID), 2) total non-ionizing dose (TNID) / displacement damage dose (DDD), and 3) single-event effect (SEE). Some content on relevant examples of effects, current concerns, and possible environmental model-driven solutions are also included.

Solar Energetic Proton Nowcast for Low Earth Orbits

NASA Astrophysics Data System (ADS)

Winter, L. M.; Quinn, R. A.

2013-12-01

Solar energetic proton flux levels above > 10 pfu can damage spacecraft and pose a hazard to astronauts as well as passengers and crew on polar commercial flights. While the GOES satellites provide real-time data of SEP levels in geosynchronous orbit, it is also important to determine the risk to objects in lower altitude orbits. To assess this risk in real-time, we created a web-based nowcast of SEP flux. The tool determines the current solar energetic proton flux level given input position (latitude, longitude, and altitude) and energy of the protons (e.g., > 10 MeV). The effective cutoff energy is calculated for the location and current geomagnetic storm level (i.e., the Kp value from SWPC) using the Shea & Smart (e.g., Smart et al. 1999abc, 2000) geomagnetic cutoff model, which uses a trajectory tracing technique through the Tsyganenko magnetospheric model for the geomagnetic field. With the cutoff energy and GOES proton flux measurements, a map of the current predicted proton flux level at the input energy is displayed along with the calculated integral spectrum for the input position. This operational tool is a powerful new diagnostic for assessing the risk to spacecraft from current solar proton levels, with easy to read color-coded maps generated for all GOES integral proton flux energies and a range of altitudes (1000 - 35000 km). The figures show example maps over a ';'quiet'' (03-26-13) and active (10-30-03) time, with high proton levels easily distinguishable at or above the NOAA warning level (yellow-orange-red). The tool also displays the current GOES integral spectrum and fit, and the estimated spectrum at a user-defined location and altitude.

Simulation Assisted Risk Assessment: Blast Overpressure Modeling

NASA Technical Reports Server (NTRS)

Lawrence, Scott L.; Gee, Ken; Mathias, Donovan; Olsen, Michael

2006-01-01

A probabilistic risk assessment (PRA) approach has been developed and applied to the risk analysis of capsule abort during ascent. The PRA is used to assist in the identification of modeling and simulation applications that can significantly impact the understanding of crew risk during this potentially dangerous maneuver. The PRA approach is also being used to identify the appropriate level of fidelity for the modeling of those critical failure modes. The Apollo launch escape system (LES) was chosen as a test problem for application of this approach. Failure modes that have been modeled and/or simulated to date include explosive overpressure-based failure, explosive fragment-based failure, land landing failures (range limits exceeded either near launch or Mode III trajectories ending on the African continent), capsule-booster re-contact during separation, and failure due to plume-induced instability. These failure modes have been investigated using analysis tools in a variety of technical disciplines at various levels of fidelity. The current paper focuses on the development and application of a blast overpressure model for the prediction of structural failure due to overpressure, including the application of high-fidelity analysis to predict near-field and headwinds effects.

Reconsidering Clinical Staging Model: A Case of Genetic High Risk for Schizophrenia.

PubMed

Lee, Tae Young; Kim, Minah; Kim, Sung Nyun; Kwon, Jun Soo

2017-01-01

The clinical staging model is considered a useful and practical method not only in dealing with the early stage of psychosis overcoming the debate about diagnostic boundaries but also in emerging mood disorder. However, its one limitation is that it cannot discriminate the heterogeneity of individuals at clinical high risk for psychosis, but lumps them all together. Even a healthy offspring of schizophrenia can eventually show clinical symptoms and progress to schizophrenia under the influence of genetic vulnerability and environmental stress even after the peak age of onset of schizophrenia. Therefore, individuals with genetic liability of schizophrenia may require a more intensive intervention than recommended by the staging model based on current clinical status.

Software risk management through independent verification and validation

NASA Technical Reports Server (NTRS)

Callahan, John R.; Zhou, Tong C.; Wood, Ralph

1995-01-01

Software project managers need tools to estimate and track project goals in a continuous fashion before, during, and after development of a system. In addition, they need an ability to compare the current project status with past project profiles to validate management intuition, identify problems, and then direct appropriate resources to the sources of problems. This paper describes a measurement-based approach to calculating the risk inherent in meeting project goals that leverages past project metrics and existing estimation and tracking models. We introduce the IV&V Goal/Questions/Metrics model, explain its use in the software development life cycle, and describe our attempts to validate the model through the reverse engineering of existing projects.

Modeling the habitat suitability for the arbovirus vector Aedes albopictus (Diptera: Culicidae) in Germany.

PubMed

Koch, Lisa K; Cunze, Sarah; Werblow, Antje; Kochmann, Judith; Dörge, Dorian D; Mehlhorn, Heinz; Klimpel, Sven

2016-03-01

Climatic changes raise the risk of re-emergence of arthropod-borne virus outbreaks globally. These viruses are transmitted by arthropod vectors, often mosquitoes. Due to increasing worldwide trade and tourism, these vector species are often accidentally introduced into many countries beyond their former distribution range. Aedes albopictus, a well-known disease vector, was detected for the first time in Germany in 2007, but seems to have failed establishment until today. However, the species is known to occur in other temperate regions and a risk for establishment in Germany remains, especially in the face of predicted climate change. Thus, the goal of the study was to estimate the potential distribution of Ae. albopictus in Germany. We used ecological niche modeling in order to estimate the potential habitat suitability for this species under current and projected future climatic conditions. According to our model, there are already two areas in western and southern Germany that appear suitable for Ae. albopictus under current climatic conditions. One of these areas lies in Baden-Wuerttemberg, the other in North-Rhine Westphalia in the Ruhr region. Furthermore, projections under future climatic conditions show an increase of the modeled habitat suitability throughout Germany. Ae. albopictus is supposed to be better acclimated to colder temperatures than other tropical vectors and thus, might become, triggered by climate change, a serious threat to public health in Germany. Our modeling results can help optimizing the design of monitoring programs currently in place in Germany.

Patient-specific radiation dose and cancer risk for pediatric chest CT.

PubMed

Li, Xiang; Samei, Ehsan; Segars, W Paul; Sturgeon, Gregory M; Colsher, James G; Frush, Donald P

2011-06-01

To estimate patient-specific radiation dose and cancer risk for pediatric chest computed tomography (CT) and to evaluate factors affecting dose and risk, including patient size, patient age, and scanning parameters. The institutional review board approved this study and waived informed consent. This study was HIPAA compliant. The study included 30 patients (0-16 years old), for whom full-body computer models were recently created from clinical CT data. A validated Monte Carlo program was used to estimate organ dose from eight chest protocols, representing clinically relevant combinations of bow tie filter, collimation, pitch, and tube potential. Organ dose was used to calculate effective dose and risk index (an index of total cancer incidence risk). The dose and risk estimates before and after normalization by volume-weighted CT dose index (CTDI(vol)) or dose-length product (DLP) were correlated with patient size and age. The effect of each scanning parameter was studied. Organ dose normalized by tube current-time product or CTDI(vol) decreased exponentially with increasing average chest diameter. Effective dose normalized by tube current-time product or DLP decreased exponentially with increasing chest diameter. Chest diameter was a stronger predictor of dose than weight and total scan length. Risk index normalized by tube current-time product or DLP decreased exponentially with both chest diameter and age. When normalized by DLP, effective dose and risk index were independent of collimation, pitch, and tube potential (<10% variation). The correlations of dose and risk with patient size and age can be used to estimate patient-specific dose and risk. They can further guide the design and optimization of pediatric chest CT protocols. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101900/-/DC1. RSNA, 2011

Technical Evaluation of the NASA Model for Cancer Risk to Astronauts Due to Space Radiation

NASA Technical Reports Server (NTRS)

2012-01-01

At the request of NASA, the National Research Council's (NRC's) Committee for Evaluation of Space Radiation Cancer Risk Model reviewed a number of changes that NASA proposes to make to its model for estimating the risk of radiation-induced cancer in astronauts. The NASA model in current use was last updated in 2005, and the proposed model would incorporate recent research directed at improving the quantification and understanding of the health risks posed by the space radiation environment. NASA's proposed model is defined by the 2011 NASA report Space Radiation Cancer Risk Projections and Uncertainties 2010 (Cucinotta et al., 2011). The committee's evaluation is based primarily on this source, which is referred to hereafter as the 2011 NASA report, with mention of specific sections or tables cited more formally as Cucinotta et al. (2011). The overall process for estimating cancer risks due to low linear energy transfer (LET) radiation exposure has been fully described in reports by a number of organizations. They include, more recently: (1) The "BEIR VII Phase 2" report from the NRC's Committee on Biological Effects of Ionizing Radiation (BEIR) (NRC, 2006); (2) Studies of Radiation and Cancer from the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR, 2006), (3) The 2007 Recommendations of the International Commission on Radiological Protection (ICRP), ICRP Publication 103 (ICRP, 2007); and (4) The Environmental Protection Agency s (EPA s) report EPA Radiogenic Cancer Risk Models and Projections for the U.S. Population (EPA, 2011). The approaches described in the reports from all of these expert groups are quite similar. NASA's proposed space radiation cancer risk assessment model calculates, as its main output, age- and gender-specific risk of exposure-induced death (REID) for use in the estimation of mission and astronaut-specific cancer risk. The model also calculates the associated uncertainties in REID. The general approach for estimating risk and uncertainty in the proposed model is broadly similar to that used for the current (2005) NASA model and is based on recommendations by the National Council on Radiation Protection and Measurements (NCRP, 2000, 2006). However, NASA's proposed model has significant changes with respect to the following: the integration of new findings and methods into its components by taking into account newer epidemiological data and analyses, new radiobiological data indicating that quality factors differ for leukemia and solid cancers, an improved method for specifying quality factors in terms of radiation track structure concepts as opposed to the previous approach based on linear energy transfer, the development of a new solar particle event (SPE) model, and the updates to galactic cosmic ray (GCR) and shielding transport models. The newer epidemiological information includes updates to the cancer incidence rates from the life span study (LSS) of the Japanese atomic bomb survivors (Preston et al., 2007), transferred to the U.S. population and converted to cancer mortality rates from U.S. population statistics. In addition, the proposed model provides an alternative analysis applicable to lifetime never-smokers (NSs). Details of the uncertainty analysis in the model have also been updated and revised. NASA's proposed model and associated uncertainties are complex in their formulation and as such require a very clear and precise set of descriptions. The committee found the 2011 NASA report challenging to review largely because of the lack of clarity in the model descriptions and derivation of the various parameters used. The committee requested some clarifications from NASA throughout its review and was able to resolve many, but not all, of the ambiguities in the written description.

Testing Current and Developing Novel Therapies for NF1-Mutant Sarcomas in a Genetically Engineered Mouse Model

DTIC Science & Technology

2015-04-01

Patients with Neurofibromatosis type 1 (NF1) are at increased risk for developing malignant tumors of the connective tissue called soft-tissue sarcomas...mouse model, MPNST, Neurofibromatosis , NF1 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE...9 9. Appendices……………………………………………………………9 4   1. INTRODUCTION: Patients with Neurofibromatosis type 1 (NF1) are at increased risk for

Mixture models for undiagnosed prevalent disease and interval-censored incident disease: applications to a cohort assembled from electronic health records.

PubMed

Cheung, Li C; Pan, Qing; Hyun, Noorie; Schiffman, Mark; Fetterman, Barbara; Castle, Philip E; Lorey, Thomas; Katki, Hormuzd A

2017-09-30

For cost-effectiveness and efficiency, many large-scale general-purpose cohort studies are being assembled within large health-care providers who use electronic health records. Two key features of such data are that incident disease is interval-censored between irregular visits and there can be pre-existing (prevalent) disease. Because prevalent disease is not always immediately diagnosed, some disease diagnosed at later visits are actually undiagnosed prevalent disease. We consider prevalent disease as a point mass at time zero for clinical applications where there is no interest in time of prevalent disease onset. We demonstrate that the naive Kaplan-Meier cumulative risk estimator underestimates risks at early time points and overestimates later risks. We propose a general family of mixture models for undiagnosed prevalent disease and interval-censored incident disease that we call prevalence-incidence models. Parameters for parametric prevalence-incidence models, such as the logistic regression and Weibull survival (logistic-Weibull) model, are estimated by direct likelihood maximization or by EM algorithm. Non-parametric methods are proposed to calculate cumulative risks for cases without covariates. We compare naive Kaplan-Meier, logistic-Weibull, and non-parametric estimates of cumulative risk in the cervical cancer screening program at Kaiser Permanente Northern California. Kaplan-Meier provided poor estimates while the logistic-Weibull model was a close fit to the non-parametric. Our findings support our use of logistic-Weibull models to develop the risk estimates that underlie current US risk-based cervical cancer screening guidelines. Published 2017. This article has been contributed to by US Government employees and their work is in the public domain in the USA. Published 2017. This article has been contributed to by US Government employees and their work is in the public domain in the USA.