Managing structural uncertainty in health economic decision models: a discrepancy approach

Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for quantifying uncertainty due to inadequacies in model structure are less well developed. We introduce an example of a model that aims to predict the costs and health effects of a physical activity promoting intervention. Our goal is to develop a framework in which we can manage our uncertainty about the costs and health effects due to deficiencies in the model structure. We describe the concept of `model discrepancy': the difference between the model evaluated at its true inputs, and the true costs and health effects. We then propose a method for quantifying discrepancy based on decomposing the cost-effectiveness model into a series of sub-functions, and considering potential error at each sub-function. We use a variance based sensitivity analysis to locate important sources of discrepancy within the model in order to guide model refinement. The resulting improved model is judged to contain less structural error, and the distribution on the model output better reflects our true uncertainty about the costs and effects of the intervention

Gray plumage color is more cryptic than brown in snowy landscapes in a resident color polymorphic bird

Camouflage may promote fitness of given phenotypes in different environments. The tawny owl (Strix aluco) is a color polymorphic species with a gray and brown morph resident in the Western Palearctic. A strong selection pressure against the brown morph during snowy and cold winters has been documented earlier, but the selection mechanisms remain unresolved. Here, we hypothesize that selection favors the gray morph because it is better camouflaged against predators and mobbers in snowy conditions compared to the brown one. We conducted an online citizen science experiment where volunteers were asked to locate a gray or a brown tawny owl specimen from pictures taken in snowy and snowless landscapes. Our results show that the gray morph in snowy landscapes is the hardest to detect whereas the brown morph in snowy landscapes is the easiest to detect. With an avian vision model, we show that, similar to human perceivers, the brown morph is more conspicuous than the gray against coniferous tree trunks for a mobbing passerine. We suggest that with better camouflage, the gray morph may avoid mobbers and predators more efficiently than the brown morph and thus survive better in snowy environments. As winters are getting milder and shorter in the species range, the selection periods against brown coloration may eventually disappear or shift poleward.Peer reviewe

Retrospective evaluation of foot-and-mouth disease vaccineeffectiveness in Turkey

AbstractFoot-and-mouth disease (FMD) is present in much of Turkey and its control is largely based on vaccination. The arrival of the FMD Asia-1 serotype in Turkey in 2011 caused particular concern, spreading rapidly westwards across the country towards the FMD free European Union. With no prior natural immunity, control of spread would rely heavily on vaccination.Unlike human vaccines, field protection is rarely evaluated directly for FMD vaccines. Between September 2011 and July 2012 we performed four retrospective outbreak investigations to assess the vaccine effectiveness (VE) of FMD Asia-1 vaccines in Turkey. Vaccine effectiveness is defined as the reduction in risk in vaccinated compared to unvaccinated individuals with similar virus exposure in the field.The four investigations included 12 villages and 1230 cattle >4 months of age. One investigation assessed the FMD Asia-1 Shamir vaccine, the other three evaluated the recently introduced FMD Asia-1 TUR 11 vaccine made using a field isolate of the FMD Asia-1 Sindh-08 lineage that had recently entered Turkey.After adjustment for confounding, the TUR 11 vaccine provided moderate protection against both clinical disease VE=69% [95% CI: 50%–81%] and infection VE=63% [95% CI: 29%–81%]. However, protection was variable with some herds with high vaccine coverage still experiencing high disease incidence. Some of this variability will be the result of the variation in virus challenge and immunity that occurs under field conditions.In the outbreak investigated there was no evidence that the Asia-1 Shamir vaccine provided adequate protection against clinical FMD with an incidence of 89% in single vaccinated cattle and 69% in those vaccinated two to five times.Based on these effectiveness estimates, vaccination alone is unlikely to produce the high levels of herd immunity needed to control FMD without additional control measures

Implementing Monte Carlo tests with P-value buckets

Software packages usually report the results of statistical tests using p-values. Users often interpret these by comparing them to standard thresholds, e.g. 0.1%, 1% and 5%, which is sometimes reinforced by a star rating (***, **, *). We consider an arbitrary statistical test whose p-value p is not available explicitly, but can be approximated by Monte Carlo samples, e.g. by bootstrap or permutation tests. The standard implementation of such tests usually draws a fixed number of samples to approximate p. However, the probability that the exact and the approximated p-value lie on different sides of a threshold (the resampling risk) can be high, particularly for p-values close to a threshold. We present a method to overcome this. We consider a finite set of user-specified intervals which cover [0,1] and which can be overlapping. We call these p-value buckets. We present algorithms that, with arbitrarily high probability, return a p-value bucket containing p. We prove that for both a bounded resampling risk and a finite runtime, overlapping buckets need to be employed, and that our methods both bound the resampling risk and guarantee a finite runtime for such overlapping buckets. To interpret decisions with overlapping buckets, we propose an extension of the star rating system. We demonstrate that our methods are suitable for use in standard software, including for low p-value thresholds occurring in multiple testing settings, and that they can be computationally more efficient than standard implementations

Research review: the relationship between social anxiety and social cognition in children and adolescents: a systematic review and meta‐analysis

Childhood Social Anxiety Disorder (SAD) is common and impairing. The recommended treatment is a disorder specific form of cognitive behavioural therapy (CBT) that includes social skills training and, whilst they appear to be more effective than more general treatments, it is not clear whether social skills training is the critical component involved in improved outcomes, particularly given that evidence for the relationship between social anxiety and social skills deficits in children is inconsistent. This may be partly due to an overlap in their observable features, and because the nature of the association may vary in different contexts (e.g. according to child age). An alternative approach is to examine the association between social anxiety and the social cognitive capacities that underpin social skills. This paper aims to examine the association between social anxiety and social cognition in children and adolescents, and examine conceptual and methodological moderators of this relationship. Methods Papers published between 1980 and 2019 were screened systematically. Fifty studies were identified from which an effect size could be calculated for the relationship between social anxiety and social cognition, including 15,411 children and adolescents. Results An overall significant, but moderate effect (r = −.15) was identified, where increased social anxiety was associated with lower social cognitive ability. Moderation analyses revealed specific associations within studies examining social anxiety among participants with and without ASD who were older than 7 years old, and studies assessing the relationship between social anxiety and specific aspects of Theory of Mind (ToM). No significant association was identified between social anxiety and emotion recognition. Conclusions Significant associations between social anxiety and social cognitive abilities appear to be accounted for by elevated social anxiety among children with ASD, and those with difficulties in specific aspects of ToM but not broader social skills, such as emotion recognition. This reinforces the importance of accurately identifying and treating social anxiety within ASD populations. In addition, treatments for social anxiety among neurotypical populations may benefit from targeting particular aspects of ToM rather than emotion recognition and other broad social skills

Genome-wide Association Study for Beta-glucan Concentration in Elite North American Oat

Genome-wide association studies (GWAS) can be a useful approach to detect quantitative trait loci (QTL) controlling complex traits in crop plants. Oat (Avena sativa L.) β-glucan is a soluble dietary fiber and has been shown to have positive health benefits. We report a GWAS involving 446 elite oat breeding lines from North America genotyped with 1005 diversity arrays technology (DArT) markers and with phenotypic data from both historical and balanced 2-yr data. Association analyses accounting for pair-wise relationships and population structure were conducted using single-marker tests and least absolute shrinkage and selection operator (LASSO). Single-marker tests yielded six and 15 significant markers for the historical and balanced data sets, respectively. The LASSO method selected 24 and 37 markers as the most important in explaining β-glucan concentration for the historical and balanced data sets, respectively. Comparisons of genetic location showed that 15 of the markers in our study were found on the same linkage groups as QTL identified in previous studies. Four of the markers colocalized to within 4 cM of three previously detected QTL, suggesting concordance between QTL detected in our study and previous studies. Two of the significant markers were also adjacent to a β-glucan candidate gene in the rice (Oryza sativa L.) genome. Our findings suggest that GWAS can be used for QTL detection for the purpose of gene discovery and for marker-assisted selection to improve β-glucan concentration in elite oat

Multispecies genetic objectives in spatial conservation planning.

The growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision-making. Yet there is no clear-cut guidance on how genetic features can be incorporated into conservation planning processes, with multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns also differ between species, but the potential trade-offs amongst genetic objectives for multiple species in conservation planning are currently understudied. This study compares spatial conservation prioritizations derived from two metrics of both genetic diversity (nucleotide and haplotype diversity) and genetic isolation (private haplotypes and local genetic differentiation) for mitochondrial DNA for five marine species. The findings show that conservation plans based solely on habitat representation noticeably differ from those additionally including genetic data, with habitat-based conservation plans selecting fewer conservation priority areas. Furthermore, all four genetic metrics selected approximately similar conservation priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, the results suggest that multi-species genetic conservation objectives are vital to create protected area networks that appropriately preserve community-level evolutionary patterns. This article is protected by copyright. All rights reserved

The genome sequence of rosebay willowherb Chamaenerion angustifolium (L.) Scop., 1771 (syn. Epilobium angustifolium L., 1753) (Onagraceae).

We present a genome assembly from an individual Chamaenerion angustifolium (fireweed; Tracheophyta; Magnoliopsida; Myrtales; Onagraceae). The genome sequence is 655.9 megabases in span. Most of the assembly is scaffolded into 18 chromosomal pseudomolecules. The mitochondrial and plastid genome assemblies have lengths of 495.18 kilobases and 160.41 kilobases in length, respectively

What is a good level of soil organic matter? An index based on organic carbon to clay ratio

Simple measures of appropriate levels of soil organic matter are needed for soil evaluation, management and monitoring, based on readily‐measurable soil properties. We test an index of soil organic matter based on the soil organic carbon (SOC) to clay ratio, defined by thresholds of SOC/clay ratio for specified levels of soil structural quality. The thresholds were originally delineated for a small number of Swiss soils. We assess the index using data from the initial sampling (1978–83) of the National Soil Inventory of England and Wales, covering 3809 sites under arable land, grassland and woodland. Land use, soil type, annual precipitation and soil pH together explained 21% of the variance in SOC/clay ratio in the dataset, with land use the most important variable. Thresholds of SOC/clay ratio of 1/8, 1/10 and 1/13 indicated the boundaries between ‘very good’, ‘good’, ‘moderate’ and ‘degraded’ levels of structural condition. On this scale, 38.2, 6.6, and 5.6% of arable, grassland and woodland sites, respectively, were degraded. The index gives a method to assess and monitor soil organic matter at national, regional or sub‐regional scales based on two routinely measured soil properties. Given the wide range of soils and land uses across England and Wales in the dataset used to test the index, we suggest it should apply to other European soils in similar climate zones

Elevated Atmospheric Carbon Dioxide Concentrations Amplify Alternaria alternata Sporulation and Total Antigen Production

Background Although the effect of elevated carbon dioxide (CO2) concentration on pollen production has been established in some plant species, impacts on fungal sporulation and antigen production have not been elucidated. Objective Our purpose was to examine the effects of rising atmospheric CO2 concentrations on the quantity and quality of fungal spores produced on timothy (Phleum pratense) leaves. Methods Timothy plants were grown at four CO2 concentrations (300, 400, 500, and 600 μmol/mol). Leaves were used as growth substrate for Alternaria alternata and Cladosporium phlei. The spore abundance produced by both fungi, as well as the size (microscopy) and antigenic protein content (ELISA) of A. alternata, were quantified. Results Leaf carbon-to-nitrogen ratio was greater at 500 and 600 μmol/mol, and leaf biomass was greater at 600 μmol/mol than at the lower CO2 concentrations. Leaf carbon-to-nitrogen ratio was positively correlated with A. alternata spore production per gram of leaf but negatively correlated with antigenic protein content per spore. At 500 and 600 μmol/mol CO2 concentrations, A. alternata produced nearly three times the number of spores and more than twice the total antigenic protein per plant than at lower concentrations. C. phlei spore production was positively correlated with leaf carbon-to-nitrogen ratio, but overall spore production was much lower than in A. alternata, and total per-plant production did not vary among CO2 concentrations. Conclusions Elevated CO2 concentrations often increase plant leaf biomass and carbon-to-nitrogen ratio. Here we demonstrate for the first time that these leaf changes are associated with increased spore production by A. alternata, a ubiquitous allergenic fungus. This response may contribute to the increasing prevalence of allergies and asthma