Estimation of survival rate and extinction probability for stage-structured populations with overlapping life stages

The development of methods providing reliable estimates of demographic parameters (e. g., survival rates, fecundity) for wild populations is essential to better understand the ecology and conservation requirements of individual species. A number of methods exist for estimating the demographics of stage-structured populations, but inherent mathematical complexity often limits their uptake by conservation practitioners. Estimating survival rates for pond-breeding amphibians is further complicated by their complex migratory and reproductive behaviours, often resulting in nonobservable states and successive cohorts of eggs and tadpoles. Here we used comprehensive data on 11 distinct breeding toad populations (Bufo calamita) to clarify and assess the suitability of a relatively simple method [the Kiritani-Nakasuji-Manly (KNM) method] to estimate the survival rates of stage-structured populations with overlapping life stages. The study shows that the KNM method is robust and provides realistic estimates of amphibian egg and larval survival rates for species in which breeding can occur as a single pulse or over a period of several weeks. The study also provides estimates of fecundity for seven distinct toad populations and indicates that it is essential to use reliable estimates of fecundity to limit the risk of under- or overestimating the survival rates when using the KNM method. Survival and fecundity rates for B. calamita populations were then used to define population matrices and make a limited exploration of their growth and viability. The findings of the study recently led to the implementation of practical conservation measures at the sites where populations were most vulnerable to extinction. © 2010 The Society of Population Ecology and Springer.

Why is housing tenure associated with a lower risk of admission to a nursing or residential home? Wealth, health and the incentive to keep 'my home'

Background Previous research has shown that home ownership is associated with a reduced risk of admission to institutional care. The extent to which this reflects associations between wealth and health, between wealth and ability to buy in care or increased motivation to avoid admission related to policies on charging is unclear. Taking account of the value of the home, as well as housing tenure, may provide some clarification as to the relative importance of these factors.
Aims To analyse the probability of admission to residential and nursing home care according to housing tenure and house value.
Methods Cox regression was used to examine the association between home ownership, house value and risk of care home admissions over 6 years of follow-up among a cohort of 51 619 people aged 65 years or older drawn from the Northern Ireland Longitudinal Study, a representative sample of approximate to 28% of the population of Northern Ireland.
Results 4% of the cohort (2138) was admitted during follow-up. Homeowners were less likely than those who rented to be admitted to care homes (HR 0.77, 95% CI 0.70 to 0.85, after adjusting for age, sex, health, living arrangement and urban/rural differences). There was a strong association between house value/tenure and health with those in the highest valued houses having the lowest odds of less than good health or limiting long-term illness. However, there was no difference in probability of admission according to house value; HRs of 0.78 (95% CI 0.67 to 0.90) and 0.81 (95% CI 0.70 to 0.95), respectively, for the lowest and highest value houses compared with renters.
Conclusions The requirement for people in the UK with capital resources to contribute to their care is a significant disincentive to institutional admission. This may place an additional burden on carers.

Animal group forces resulting from predator avoidance and competition minimization

A new model to explain animal spacing, based on a trade-off between foraging efficiency and predation risk, is derived from biological principles. The model is able to explain not only the general tendency for animal groups to form, but some of the attributes of real groups. These include the independence of mean animal spacing from group population, the observed variation of animal spacing with resource availability and also with the probability of predation, and the decline in group stability with group size. The appearance of "neutral zones" within which animals are not motivated to adjust their relative positions is also explained. The model assumes that animals try to minimize a cost potential combining the loss of intake rate due to foraging interference and the risk from exposure to predators. The cost potential describes a hypothetical field giving rise to apparent attractive and repulsive forces between animals. Biologically based functions are given for the decline in interference cost and increase in the cost of predation risk with increasing animal separation. Predation risk is calculated from the probabilities of predator attack and predator detection as they vary with distance. Using example functions for these probabilities and foraging interference, we calculate the minimum cost potential for regular lattice arrangements of animals before generalizing to finite-sized groups and random arrangements of animals, showing optimal geometries in each case and describing how potentials vary with animal spacing. (C) 1999 Academic Press.</p>

Risk-informed decision-making in the presence of epistemic uncertainty

An important issue in risk analysis is the distinction between epistemic and aleatory uncertainties. In this paper, the use of distinct representation formats for aleatory and epistemic uncertainties is advocated, the latter being modelled by sets of possible values. Modern uncertainty theories based on convex sets of probabilities are known to be instrumental for hybrid representations where aleatory and epistemic components of uncertainty remain distinct. Simple uncertainty representation techniques based on fuzzy intervals and p-boxes are used in practice. This paper outlines a risk analysis methodology from elicitation of knowledge about parameters to decision. It proposes an elicitation methodology where the chosen representation format depends on the nature and the amount of available information. Uncertainty propagation methods then blend Monte Carlo simulation and interval analysis techniques. Nevertheless, results provided by these techniques, often in terms of probability intervals, may be too complex to interpret for a decision-maker and we, therefore, propose to compute a unique indicator of the likelihood of risk, called confidence index. It explicitly accounts for the decisionmaker’s attitude in the face of ambiguity. This step takes place at the end of the risk analysis process, when no further collection of evidence is possible that might reduce the ambiguity due to epistemic uncertainty. This last feature stands in contrast with the Bayesian methodology, where epistemic uncertainties on input parameters are modelled by single subjective probabilities at the beginning of the risk analysis process.

Welfare risk assessment:The benefits and common pitfalls

Risk is defined as a situation involving exposure to danger. Risk assessment by nature characterises the probability of a negative event occurring and quantifies the consequences of such an event. Risk assessment is increasingly being used in the field of animal welfare as a means of drawing comparisons between multiple welfare problems within and between species and identifying those that should be prioritised by policy-makers, either because they affect a large proportion of the population or because they have particularly severe consequences for those affected. The assessment of risk is typically based on three fundamental factors: intensity of consequences, duration affected by consequences and prevalence. However, it has been recognised that these factors alone do not give a complete picture of a hazard and its associated consequences. Rather, to get a complete picture, it is important to also consider information about the hazard itself: probability of exposure to the hazard and duration of exposure to the hazard. The method has been applied to a variety of farmed species (eg poultry, dairy cows, farmed fish), investigating housing, husbandry and slaughter procedures, as well as companion animals, where it has been used to compare inherited defects in pedigree dogs and horses. To what extent can we trust current risk assessment methods to get the priorities straight? How should we interpret the results produced by such assessments? Here, the potential difficulties and pitfalls of the welfare risk assessment method will be discussed: (i) the assumption that welfare hazards are independent; (ii) the problem of quantifying the model parameters; and (iii) assessing and incorporating variability and uncertainty into welfare risk assessments. © 2012 Universities Federation for Animal Welfare.

Serial chimerism analyses indicate that mixed haemopoietic chimerism influences the probability of graft rejection and disease recurrence following allogeneic stem cell transplantation (SCT) for severe aplastic anaemia (SAA): indication for routine assessment of chimerism post SCT for SAA

Ninety-one patients were studied serially for chimeric status following allogeneic stem cell transplantation (SCT) for severe aplastic anaemia (SAA) or Fanconi Anaemia (FA). Short tandem repeat polymerase chain reaction (STR-PCR) was used to stratify patients into five groups: (A) complete donor chimeras (n = 39), (B) transient mixed chimeras (n = 15) (C) stable mixed chimeras (n = 18), (D) progressive mixed chimeras (n = 14) (E) recipient chimeras with early graft rejection (n = 5). As serial sampling was not possible in Group E, serial chimerism results for 86 patients were available for analysis. The following factors were analysed for association with chimeric status: age, sex match, donor type, aetiology of aplasia, source of stem cells, number of cells engrafted, conditioning regimen, graft-versus-host disease (GvHD) prophylaxis, occurrence of acute and chronic GvHD and survival. Progressive mixed chimeras (PMCs) were at high risk of late graft rejection (n = 10, P <0.0001). Seven of these patients lost their graft during withdrawal of immunosuppressive therapy. STR-PCR indicated an inverse correlation between detection of recipient cells post-SCT and occurrence of acute GvHD (P = 0.008). PMC was a bad prognostic indicator of survival (P = 0.003). Monitoring of chimeric status during cyclosporin withdrawal may facilitate therapeutic intervention to prevent late graft rejection in patients transplanted for SAA.

How much risk ought we to take? Exploring the possibilities of risk-sensitive consequentialism in the context of climate engineering

When it comes to assessing the deontic status of acts and policies in the context of risk and uncertainty, moral theories are often at a loss. In this paper we hope to show that employing a multi-dimensional consequentialist framework provides ethical guidance for decision-making in complex situations. The paper starts by briefly rehearsing consequentialist responses to the issue of risk, as well as their shortcomings. We then go on to present our own proposal based on three dimensions: wellbeing, fairness and probability. In the last section we apply our approach to a comparison of different climate policy options, including stratospheric solar-radiation management.

Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms

Rationale, aims and objectives: This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. 

Methods: Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. 

Results: Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). 

Conclusions: Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized.

Risk Modelling Framework for Emergency Hospital Readmission, Using Hospital Episode Statistics Inpatient Data

The objective of this study was to develop, test and benchmark a framework and a predictive risk model for hospital emergency readmission within 12 months. We performed the development using routinely collected Hospital Episode Statistics data covering inpatient hospital admissions in England. Three different timeframes were used for training, testing and benchmarking: 1999 to 2004, 2000 to 2005 and 2004 to 2009 financial years. Each timeframe includes 20% of all inpatients admitted within the trigger year. The comparisons were made using positive predictive value, sensitivity and specificity for different risk cut-offs, risk bands and top risk segments, together with the receiver operating characteristic curve. The constructed Bayes Point Machine using this feature selection framework produces a risk probability for each admitted patient, and it was validated for different timeframes, sub-populations and cut-off points. At risk cut-off of 50%, the positive predictive value was 69.3% to 73.7%, the specificity was 88.0% to 88.9% and sensitivity was 44.5% to 46.3% across different timeframes. Also, the area under the receiver operating characteristic curve was 73.0% to 74.3%. The developed framework and model performed considerably better than existing modelling approaches with high precision and moderate sensitivity.

A risk-averse optimization model for trading wind energy in a market environment under uncertainty

In this paper, a stochastic programming approach is proposed for trading wind energy in a market environment under uncertainty. Uncertainty in the energy market prices is the main cause of high volatility of profits achieved by power producers. The volatile and intermittent nature of wind energy represents another source of uncertainty. Hence, each uncertain parameter is modeled by scenarios, where each scenario represents a plausible realization of the uncertain parameters with an associated occurrence probability. Also, an appropriate risk measurement is considered. The proposed approach is applied on a realistic case study, based on a wind farm in Portugal. Finally, conclusions are duly drawn. (C) 2011 Elsevier Ltd. All rights reserved.

The simple economics of risk-sharing agreements between the NHS and the pharmaceutical industry

The Janssen-Cilag proposal for a risk-sharing agreement regarding bortezomib received a welcome signal from NICE. The Office of Fair Trading report included risk-sharing agreements as an available tool for the National Health Service. Nonetheless, recent discussions have somewhat neglected the economic fundamentals underlying risk-sharing agreements. We argue here that risk-sharing agreements, although attractive due to the principle of paying by results, also entail risks. Too many patients may be put under treatment even with a low success probability. Prices are likely to be adjusted upward, in anticipation of future risk-sharing agreements between the pharmaceutical company and the third-party payer. An available instrument is a verification cost per patient treated, which allows obtaining the first-best allocation of patients to the new treatment, under the risk sharing agreement. Overall, the welfare effects of risk-sharing agreements are ambiguous, and care must be taken with their use.

Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees : the PredictAL study

Background: Little is known about the risk of progression to hazardous alcohol use in people currently drinking at safe limits. We aimed to develop a prediction model (predictAL) for the development of hazardous drinking in safe drinkers. Methods: A prospective cohort study of adult general practice attendees in six European countries and Chile followed up over 6 months. We recruited 10,045 attendees between April 2003 to February 2005. 6193 European and 2462 Chilean attendees recorded AUDIT scores below 8 in men and 5 in women at recruitment and were used in modelling risk. 38 risk factors were measured to construct a risk model for the development of hazardous drinking using stepwise logistic regression. The model was corrected for over fitting and tested in an external population. The main outcome was hazardous drinking defined by an AUDIT score >= 8 in men and >= 5 in women. Results: 69.0% of attendees were recruited, of whom 89.5% participated again after six months. The risk factors in the final predictAL model were sex, age, country, baseline AUDIT score, panic syndrome and lifetime alcohol problem. The predictAL model's average c-index across all six European countries was 0.839 (95% CI 0.805, 0.873). The Hedge's g effect size for the difference in log odds of predicted probability between safe drinkers in Europe who subsequently developed hazardous alcohol use and those who did not was 1.38 (95% CI 1.25, 1.51). External validation of the algorithm in Chilean safe drinkers resulted in a c-index of 0.781 (95% CI 0.717, 0.846) and Hedge's g of 0.68 (95% CI 0.57, 0.78). Conclusions: The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.

Introducing risk parity on momentum and carry portfolios

The momentum and carry anomalies have been extensively documented in the literature. However, there are still many issues relating to the risks associated to them that are left unexplained. One is the fact that an investor holds for too long the most volatile assets, both under momentum and carry strategies. Therefore, they present a level of risk and a probability of extreme events to happen inconsistent. This work project hypothesizes and proves the introduction of risk parity rules on the weights of the portfolios do increase risk rewarding of carry strategies. However, it fails under momentum strategies.

Properties of a risk measure derived from ruin theory

This paper studies a risk measure inherited from ruin theory and investigates some of its properties. Specifically, we consider a value-at-risk (VaR)-type risk measure defined as the smallest initial capital needed to ensure that the ultimate ruin probability is less than a given level. This VaR-type risk measure turns out to be equivalent to the VaR of the maximal deficit of the ruin process in infinite time. A related Tail-VaR-type risk measure is also discussed.

Genetic variants influencing circulating lipid levels and risk of coronary artery disease.

OBJECTIVE: Genetic studies might provide new insights into the biological mechanisms underlying lipid metabolism and risk of CAD. We therefore conducted a genome-wide association study to identify novel genetic determinants of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides. METHODS AND RESULTS: We combined genome-wide association data from 8 studies, comprising up to 17 723 participants with information on circulating lipid concentrations. We did independent replication studies in up to 37 774 participants from 8 populations and also in a population of Indian Asian descent. We also assessed the association between single-nucleotide polymorphisms (SNPs) at lipid loci and risk of CAD in up to 9 633 cases and 38 684 controls. We identified 4 novel genetic loci that showed reproducible associations with lipids (probability values, 1.6×10(-8) to 3.1×10(-10)). These include a potentially functional SNP in the SLC39A8 gene for HDL-C, an SNP near the MYLIP/GMPR and PPP1R3B genes for LDL-C, and at the AFF1 gene for triglycerides. SNPs showing strong statistical association with 1 or more lipid traits at the CELSR2, APOB, APOE-C1-C4-C2 cluster, LPL, ZNF259-APOA5-A4-C3-A1 cluster and TRIB1 loci were also associated with CAD risk (probability values, 1.1×10(-3) to 1.2×10(-9)). CONCLUSIONS: We have identified 4 novel loci associated with circulating lipids. We also show that in addition to those that are largely associated with LDL-C, genetic loci mainly associated with circulating triglycerides and HDL-C are also associated with risk of CAD. These findings potentially provide new insights into the biological mechanisms underlying lipid metabolism and CAD risk.