Making robust policy decision using global biodiversity indicators

In order to influence global policy effectively, conservation scientists need to be able to provide robust predictions of the impact of alternative policies on biodiversity and measure progress towards goals using reliable indicators. We present a framework for using biodiversity indicators predictively to inform policy choices at a global level. The approach is illustrated with two case studies in which we project forwards the impacts of feasible policies on trends in biodiversity and in relevant indicators. The policies are based on targets agreed at the Convention on Biological Diversity (CBD) meeting in Nagoya in October 2010. The first case study compares protected area policies for African mammals, assessed using the Red List Index; the second example uses the Living Planet Index to assess the impact of a complete halt, versus a reduction, in bottom trawling. In the protected areas example, we find that the indicator can aid in decision-making because it is able to differentiate between the impacts of the different policies. In the bottom trawling example, the indicator exhibits some counter-intuitive behaviour, due to over-representation of some taxonomic and functional groups in the indicator, and contrasting impacts of the policies on different groups caused by trophic interactions. Our results support the need for further research on how to use predictive models and indicators to credibly track trends and inform policy. To be useful and relevant, scientists must make testable predictions about the impact of global policy on biodiversity to ensure that targets such as those set at Nagoya catalyse effective and measurable change

A regional Bayesian POT model for flood frequency analysis

Flood frequency analysis is usually based on the fitting of an extreme value distribution to the local streamflow series. However, when the local data series is short, frequency analysis results become unreliable. Regional frequency analysis is a convenient way to reduce the estimation uncertainty. In this work, we propose a regional Bayesian model for short record length sites. This model is less restrictive than the index flood model while preserving the formalism of "homogeneous regions". The performance of the proposed model is assessed on a set of gauging stations in France. The accuracy of quantile estimates as a function of the degree of homogeneity of the pooling group is also analysed. The results indicate that the regional Bayesian model outperforms the index flood model and local estimators. Furthermore, it seems that working with relatively large and homogeneous regions may lead to more accurate results than working with smaller and highly homogeneous regions

Climate change and the long-term viability of the World’s busiest heavy haul ice road

Climate models project that the northern high latitudes will warm at a rate in excess of the global mean. This will pose severe problems for Arctic and sub-Arctic infrastructure dependent on maintaining low temperatures for structural integrity. This is the case for the economically important Tibbitt to Contwoyto Winter Road (TCWR)—the world’s busiest heavy haul ice road, spanning 400 km across mostly frozen lakes within the Northwest Territories of Canada. In this study, future climate scenarios are developed for the region using statistical downscaling methods. In addition, changes in lake ice thickness are projected based on historical relationships between measured ice thickness and air temperatures. These projections are used to infer the theoretical operational dates of the TCWR based on weight limits for trucks on the ice. Results across three climate models driven by four RCPs reveal a considerable warming trend over the coming decades. Projected changes in ice thickness reveal a trend towards thinner lake ice and a reduced time window when lake ice is at sufficient thickness to support trucks on the ice road, driven by increasing future temperatures. Given the uncertainties inherent in climate modelling and the resultant projections, caution should be exercised in interpreting the magnitude of these scenarios. More certain is the direction of change, with a clear trend towards winter warming that will reduce the operation time window of the TCWR. This illustrates the need for planners and policymakers to consider future changes in climate when planning annual haulage along the TCWR

The social nature of serial murder: The intersection of gender and modernity

The literature on the aetiology of serial killing has benefited from analyses which offer an alternative perspective to individual/psychological approaches and consider serial murder as a sociological phenomenon. The main argument brought to bear within this body of work identifies the socio-economic and cultural conditions of modernity as enabling and legitimating the motivations and actions of the serial killer. This article interrogates this work from the standpoint of a gendered reading of modernity. Using the Yorkshire Ripper case, it emphasizes how in addition to the political economy, gender relations and masculinity shape the dynamics of serial murder and its representation

First integrative trend analysis for a great ape species in Borneo

For many threatened species the rate and drivers of population decline are difficult to assess accurately: species’ surveys are typically restricted to small geographic areas, are conducted over short time periods, and employ a wide range of survey protocols. We addressed methodological challenges for assessing change in the abundance of an endangered species. We applied novel methods for integrating field and interview survey data for the critically endangered Bornean orangutan (Pongo pygmaeus), allowing a deeper understanding of the species’ persistence through time. Our analysis revealed that Bornean orangutan populations have declined at a rate of 25% over the last 10 years. Survival rates of the species are lowest in areas with intermediate rainfall, where complex interrelations between soil fertility, agricultural productivity, and human settlement patterns influence persistence. These areas also have highest threats from human-wildlife conflict. Survival rates are further positively associated with forest extent, but are lower in areas where surrounding forest has been recently converted to industrial agriculture. Our study highlights the urgency of determining specific management interventions needed in different locations to counter the trend of decline and its associated drivers

Using a smartphone-based self-management platform to support medication adherence and clinical consultation in Parkinson's disease.

The progressive nature of Parkinson's disease, its complex treatment regimens and the high rates of comorbid conditions make self-management and treatment adherence a challenge. Clinicians have limited face-to-face consultation time with Parkinson's disease patients, making it difficult to comprehensively address non-adherence. Here we share the results from a multi-centre (seven centres) randomised controlled trial conducted in England and Scotland to assess the impact of using a smartphone-based Parkinson's tracker app to promote patient self-management, enhance treatment adherence and quality of clinical consultation. Eligible Parkinson's disease patients were randomised using a 1:1 ratio according to a computer-generated random sequence, stratified by centre and using blocks of variable size, to intervention Parkinson's Tracker App or control (Treatment as Usual). Primary outcome was the self-reported score of adherence to treatment (Morisky medication adherence scale -8) at 16 weeks. Secondary outcomes were Quality of Life (Parkinson's disease questionnaire -39), quality of consultation for Parkinson's disease patients (Patient-centred questionnaire for Parkinson's disease), impact on non-motor symptoms (Non-motor symptoms questionnaire), depression and anxiety (Hospital anxiety and depression scale) and beliefs about medication (Beliefs about Medication Questionnaire) at 16 weeks. Primary and secondary endpoints were analysed using a generalised linear model with treatment as the fixed effect and baseline measurement as the covariate. 158 patients completed the study (Parkinson's tracker app = 68 and TAU = 90). At 16 weeks Parkinson's tracker app significantly improved adherence, compared to treatment as usual (mean difference: 0.39, 95%CI 0.04-0.74; p = 0.0304) with no confounding effects of gender, number of comorbidities and age. Among secondary outcomes, Parkinson's tracker app significantly improved patients' perception of quality of consultation (0.15, 95% CI 0.03 to 0.27; p = 0.0110). The change in non-motor symptoms was -0.82 (95% CI -1.75 to 0.10; p = 0.0822). 72% of participants in the Parkinson's tracker app group continued to use and engage with the application throughout the 16-week trial period. The Parkinson's tracker app can be an effective and novel way of enhancing self-reported medication adherence and quality of clinical consultation by supporting self-management in Parkinson's disease in patients owning smartphones. Further work is recommended to determine whether the benefits of the intervention are maintained beyond the 16 week study period

Mortality by age, gene and gender in carriers of pathogenic mismatch repair gene variants receiving surveillance for early cancer diagnosis and treatment: a report from the prospective Lynch syndrome database

BACKGROUND: The Prospective Lynch Syndrome Database (PLSD) collates information on carriers of pathogenic or likely pathogenic MMR variants (path_MMR) who are receiving medical follow-up, including colonoscopy surveillance, which aims to the achieve early diagnosis and treatment of cancers. Here we use the most recent PLSD cohort that is larger and has wider geographical representation than previous versions, allowing us to present mortality as an outcome, and median ages at cancer diagnoses for the first time. METHODS: The PLSD is a prospective observational study without a control group that was designed in 2012 and updated up to October 2022. Data for 8500 carriers of path_MMR variants from 25 countries were included, providing 71,713 years of follow up. Cumulative cancer incidences at 65 years of age were combined with 10-year crude survival following cancer, to derive estimates of mortality up to 75 years of age by organ, gene, and gender. FINDINGS: Gynaecological cancers were more frequent than colorectal cancers in path_MSH2, path_MSH6 and path_PMS2 carriers [cumulative incidence: 53.3%, 49.6% and 23.3% at 75 years, respectively]. Endometrial, colon and ovarian cancer had low mortality [8%, 13% and 15%, respectively] and prostate cancers were frequent in male path_MSH2 carriers [cumulative incidence: 39.7% at 75 years]. Pancreatic, brain, biliary tract and ureter and kidney and urinary bladder cancers were associated with high mortality [83%, 66%, 58%, 27%, and 29%, respectively]. Among path_MMR carriers undergoing colonoscopy surveillance, particularly path_MSH2 carriers, more deaths followed non-colorectal Lynch syndrome cancers than colorectal cancers. INTERPRETATION: In path_MMR carriers undergoing colonoscopy surveillance, non-colorectal Lynch syndrome cancers were associated with more deaths than were colorectal cancers. Reducing deaths from non-colorectal cancers presents a key challenge in contemporary medical care in Lynch syndrome. FUNDING: We acknowledge funding from the Norwegian Cancer Society, contract 194751-2017

An economic model of long-term use of celecoxib in patients with osteoarthritis

<p>Abstract</p> <p>Background</p> <p>Previous evaluations of the cost-effectiveness of the cyclooxygenase-2 selective inhibitor celecoxib (Celebrex, Pfizer Inc, USA) have produced conflicting results. The recent controversy over the cardiovascular (CV) risks of rofecoxib and other coxibs has renewed interest in the economic profile of celecoxib, the only coxib now available in the United States. The objective of our study was to evaluate the long-term cost-effectiveness of celecoxib compared with nonselective nonsteroidal anti-inflammatory drugs (nsNSAIDs) in a population of 60-year-old osteoarthritis (OA) patients with average risks of upper gastrointestinal (UGI) complications who require chronic daily NSAID therapy.</p> <p>Methods</p> <p>We used decision analysis based on data from the literature to evaluate cost-effectiveness from a modified societal perspective over patients' lifetimes, with outcomes expressed as incremental costs per quality-adjusted life-year (QALY) gained. Sensitivity tests were performed to evaluate the impacts of advancing age, CV thromboembolic event risk, different analytic horizons and alternate treatment strategies after UGI adverse events.</p> <p>Results</p> <p>Our main findings were: 1) the base model incremental cost-effectiveness ratio (ICER) for celecoxib versus nsNSAIDs was $31,097 per QALY; 2) the ICER per QALY was$19,309 for a model in which UGI ulcer and ulcer complication event risks increased with advancing age; 3) the ICER per QALY was $17,120 in sensitivity analyses combining serious CV thromboembolic event (myocardial infarction, stroke, CV death) risks with base model assumptions.</p> <p>Conclusion</p> <p>Our model suggests that chronic celecoxib is cost-effective versus nsNSAIDs in a population of 60-year-old OA patients with average risks of UGI events.</p

100,000 Genomes Pilot on Rare-Disease Diagnosis in Health Care — Preliminary Report

BACKGROUND: The U.K. 100,000 Genomes Project is in the process of investigating the role of genome sequencing in patients with undiagnosed rare diseases after usual care and the alignment of this research with health care implementation in the U.K. National Health Service. Other parts of this project focus on patients with cancer and infection. METHODS: We conducted a pilot study involving 4660 participants from 2183 families, among whom 161 disorders covering a broad spectrum of rare diseases were present. We collected data on clinical features with the use of Human Phenotype Ontology terms, undertook genome sequencing, applied automated variant prioritization on the basis of applied virtual gene panels and phenotypes, and identified novel pathogenic variants through research analysis. RESULTS: Diagnostic yields varied among family structures and were highest in family trios (both parents and a proband) and families with larger pedigrees. Diagnostic yields were much higher for disorders likely to have a monogenic cause (35%) than for disorders likely to have a complex cause (11%). Diagnostic yields for intellectual disability, hearing disorders, and vision disorders ranged from 40 to 55%. We made genetic diagnoses in 25% of the probands. A total of 14% of the diagnoses were made by means of the combination of research and automated approaches, which was critical for cases in which we found etiologic noncoding, structural, and mitochondrial genome variants and coding variants poorly covered by exome sequencing. Cohortwide burden testing across 57,000 genomes enabled the discovery of three new disease genes and 19 new associations. Of the genetic diagnoses that we made, 25% had immediate ramifications for clinical decision making for the patients or their relatives. CONCLUSIONS: Our pilot study of genome sequencing in a national health care system showed an increase in diagnostic yield across a range of rare diseases. (Funded by the National Institute for Health Research and others.)