Equity is more important for the social cost of methane than climate uncertainty.

The social cost of methane (SC-CH4) measures the economic loss of welfare caused by emitting one tonne of methane into the atmosphere. This valuation may in turn be used in cost-benefit analyses or to inform climate policies1-3. However, current SC-CH4 estimates have not included key scientific findings and observational constraints. Here we estimate the SC-CH4 by incorporating the recent upward revision of 25 per cent to calculations of the radiative forcing of methane4, combined with calibrated reduced-form global climate models and an ensemble of integrated assessment models (IAMs). Our multi-model mean estimate for the SC-CH4 is US$933 per tonne of CH4 (5-95 per cent range, US$471-1,570 per tonne of CH4) under a high-emissions scenario (Representative Concentration Pathway (RCP) 8.5), a 22 per cent decrease compared to estimates based on the climate uncertainty framework used by the US federal government5. Our ninety-fifth percentile estimate is 51 per cent lower than the corresponding figure from the US framework. Under a low-emissions scenario (RCP 2.6), our multi-model mean decreases to US$710 per tonne of CH4. Tightened equilibrium climate sensitivity estimates paired with the effect of previously neglected relationships between uncertain parameters of the climate model lower these estimates. We also show that our SC-CH4 estimates are sensitive to model combinations; for example, within one IAM, different methane cycle sub-models can induce variations of approximately 20 per cent in the estimated SC-CH4. But switching IAMs can more than double the estimated SC-CH4. Extending our results to account for societal concerns about equity produces SC-CH4 estimates that differ by more than an order of magnitude between low- and high-income regions. Our central equity-weighted estimate for the USA increases to US$8,290 per tonne of CH4 whereas our estimate for sub-Saharan Africa decreases to US$134 per tonne of CH4.

Evidence for sharp increase in the economic damages of extreme natural disasters.

Climate change has increased the frequency and intensity of natural disasters. Does this translate into increased economic damages? To date, empirical assessments of damage trends have been inconclusive. Our study demonstrates a temporal increase in extreme damages, after controlling for a number of factors. We analyze event-level data using quantile regressions to capture patterns in the damage distribution (not just its mean) and find strong evidence of progressive rightward skewing and tail-fattening over time. While the effect of time on averages is hard to detect, effects on extreme damages are large, statistically significant, and growing with increasing percentiles. Our results are consistent with an upwardly curved, convex damage function, which is commonly assumed in climate-economics models. They are also robust to different specifications of control variables and time range considered and indicate that the risk of extreme damages has increased more in temperate areas than in tropical ones. We use simulations to show that underreporting bias in the data does not weaken our inferences; in fact, it may make them overly conservative.

Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management.

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.

[Personal Factors of the Bio-Psycho-Social Model (WHO): A Revised Classification by the German Society for Social Medicine and Prevention (DGSMP)]. / Personbezogene Faktoren im bio-psycho-sozialen Modell der WHO: Systematik der Deutschen Gesellschaft für Sozialmedizin und Prävention (DGSMP).

BACKGROUND: In 2010, the ICF working group of Faculty II "Applied Social Medicine and Rehabilitation" of the German Society for Social Medicine and Prevention, DGSMP proposed a classification of personal factors (PF) for the German-speaking area. Meanwhile, the International Classification of Functioning, Disability and Health (ICF) and WHO's bio-psycho-social model were increasingly integrated into the German Social Code (Book IX for Rehabilitation and Participation). It was a legislative decision that the needs assessment for the rehabilitation process must be "comprehensive". AIM: This publication aims to present an updated classification of PF to support the socio-medical assessment. For this purpose other published papers proposing a classification of PF were analyzed, especially the publication of Geyh et al. METHODS: The multiprofessional working group re-examined the basic structure, consistency and selection of factors of the 2010 classification using a qualitative approach and modified them if meaningful and necessary. The principles for the selection of factors were the same as in the 2010 publication (comprehensive, manageable, universal, impartial, relevant, unambiguous, focusing on finality, not regarding causality and non-discriminatory). RESULTS: A fundamental revision was not necessary; the basic structure remained primarily unchanged. Some items were included, excluded, summarized, shifted and editorially or content-related altered. Legal expertise shows that the classification of PF and their individual use for the socio-medical assessment, if necessary for the individual rehabilitation allocation, incur no problems with regard to data-protection regulations. PERSPECTIVES: The revised classification is ready to support users to describe and document relevant influences of the life background of individuals in a structured manner. Thus, influences on functioning and participation can be described comprehensively and transparently based on the bio-psycho-social model. A justiciable allocation of benefits for persons with disabilities is facilitated.

Building a Values-Informed Mental Model for New Orleans Climate Risk Management.

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals' values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a "Values-informed Mental Model" research approach, or ViMM, to elicit individuals' values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans' unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision-support processes and may encourage adoption of CRM strategies more in line with stakeholders' values.

Mutations in the human UBR1 gene and the associated phenotypic spectrum.

Johanson-Blizzard syndrome (JBS) is a rare, autosomal recessive disorder characterized by exocrine pancreatic insufficiency, typical facial features, dental anomalies, hypothyroidism, sensorineural hearing loss, scalp defects, urogenital and anorectal anomalies, short stature, and cognitive impairment of variable degree. This syndrome is caused by a defect of the E3 ubiquitin ligase UBR1, which is part of the proteolytic N-end rule pathway. Herein, we review previously reported (n = 29) and a total of 31 novel UBR1 mutations in relation to the associated phenotype in patients from 50 unrelated families. Mutation types include nonsense, frameshift, splice site, missense, and small in-frame deletions consistent with the hypothesis that loss of UBR1 protein function is the molecular basis of JBS. There is an association of missense mutations and small in-frame deletions with milder physical abnormalities and a normal intellectual capacity, thus suggesting that at least some of these may represent hypomorphic UBR1 alleles. The review of clinical data of a large number of molecularly confirmed JBS cases allows us to define minimal clinical criteria for the diagnosis of JBS. For all previously reported and novel UBR1 mutations together with their clinical data, a mutation database has been established at LOVD.

Chromosomal Numerical Aberrations and Rare Copy Number Variation in Patients with Inflammatory Bowel Disease.

BACKGROUND AND AIMS: Inflammatory bowel diseases [IBD] have a complex polygenic aetiology. Rare genetic variants can cause monogenic intestinal inflammation. The impact of chromosomal aberrations and large structural abnormalities on IBD susceptibility is not clear. We aimed to comprehensively characterise the phenotype and prevalence of patients with IBD who possess rare numerical and structural chromosomal abnormalities. METHODS: We performed a systematic literature search of databases PubMed and Embase; and analysed gnomAD, Clinvar, the 100 000 Genomes Project, and DECIPHER databases. Further, we analysed international paediatric IBD cohorts to investigate the role of IL2RA duplications in IBD susceptibility. RESULTS: A meta-analysis suggests that monosomy X [Turner syndrome] is associated with increased expressivity of IBD that exceeds the population baseline (1.86%, 95% confidence interval [CI] 1.48 to 2.34%) and causes a younger age of IBD onset. There is little evidence that Klinefelter syndrome, Trisomy 21, Trisomy 18, mosaic Trisomy 9 and 16, or partial trisomies contribute to IBD susceptibility. Copy number analysis studies suggest inconsistent results. Monoallelic loss of X-linked or haploinsufficient genes is associated with IBD by hemizygous or heterozygous deletions, respectively. However, haploinsufficient gene deletions are detected in healthy reference populations, suggesting that the expressivity of IBD might be overestimated. One duplication that has previously been identified as potentially contributing to IBD risk involves the IL2RA/IL15R loci. Here we provide additional evidence that a microduplication of this locus may predispose to very-early-onset IBD by identifying a second case in a distinct kindred. However, the penetrance of intestinal inflammation in this genetic aberration is low [<2.6%]. CONCLUSIONS: Turner syndrome is associated with increased susceptibility to intestinal inflammation. Duplication of the IL2RA/IL15R loci may contribute to disease risk.

Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods.

This study compares two widely used approaches for robustness analysis of decision problems: the info-gap method originally developed by Ben-Haim and the robust decision making (RDM) approach originally developed by Lempert, Popper, and Bankes. The study uses each approach to evaluate alternative paths for climate-altering greenhouse gas emissions given the potential for nonlinear threshold responses in the climate system, significant uncertainty about such a threshold response and a variety of other key parameters, as well as the ability to learn about any threshold responses over time. Info-gap and RDM share many similarities. Both represent uncertainty as sets of multiple plausible futures, and both seek to identify robust strategies whose performance is insensitive to uncertainties. Yet they also exhibit important differences, as they arrange their analyses in different orders, treat losses and gains in different ways, and take different approaches to imprecise probabilistic information. The study finds that the two approaches reach similar but not identical policy recommendations and that their differing attributes raise important questions about their appropriate roles in decision support applications. The comparison not only improves understanding of these specific methods, it also suggests some broader insights into robustness approaches and a framework for comparing them.

Probabilistic projections of baseline twenty-first century CO2 emissions using a simple calibrated integrated assessment model.

Probabilistic projections of baseline (with no additional mitigation policies) future carbon emissions are important for sound climate risk assessments. Deep uncertainty surrounds many drivers of projected emissions. Here, we use a simple integrated assessment model, calibrated to century-scale data and expert assessments of baseline emissions, global economic growth, and population growth, to make probabilistic projections of carbon emissions through 2100. Under a variety of assumptions about fossil fuel resource levels and decarbonization rates, our projections largely agree with several emissions projections under current policy conditions. Our global sensitivity analysis identifies several key economic drivers of uncertainty in future emissions and shows important higher-level interactions between economic and technological parameters, while population uncertainties are less important. Our analysis also projects relatively low global economic growth rates over the remainder of the century. This illustrates the importance of additional research into economic growth dynamics for climate risk assessment, especially if pledged and future climate mitigation policies are weakened or have delayed implementations. These results showcase the power of using a simple, transparent, and calibrated model. While the simple model structure has several advantages, it also creates caveats for our results which are related to important areas for further research. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10584-021-03279-7.

Childhood onset inflammatory bowel disease: predictors of delayed diagnosis from the CEDATA German-language pediatric inflammatory bowel disease registry.

OBJECTIVES: To examine predictors of delayed diagnosis of inflammatory bowel disease in children and adolescents. STUDY DESIGN: A total of 2,436 patients (age 0-18 years) with Crohn's disease, ulcerative colitis, or unclassified colitis were included from 53 pediatric gastroenterologists. Predictors were examined with the proportional hazards model, presented as hazard ratios (HR) with 95% confidence intervals. HR < 1.0 represent factors associated with late diagnosis. RESULTS: Median time to diagnosis was 4 (2-8) months. Crohn's disease (HR 0.62; 0.56-0.68), and within Crohn's disease, ileal disease (HR 0.77, 95% confidence interval 0.67 to 0.89) were associated with delayed diagnosis. Chances for early diagnosis increased with increasing age (HR 1.07 per year of age; 1.06 to 1.08). There was also an effect by center (HR 0.63, 0.52 to 0.67), but not by sex or country (Austria vs Germany). Growth failure was more common in those cases with delayed diagnosis. CONCLUSIONS: There is still concern about delays in the diagnosis of inflammatory bowel disease in the very young and in children with small bowel disease. Inequalities of care by region require further investigation.

Intrinsic ethics regarding integrated assessment models for climate management.

In this essay we develop and argue for the adoption of a more comprehensive model of research ethics than is included within current conceptions of responsible conduct of research (RCR). We argue that our model, which we label the ethical dimensions of scientific research (EDSR), is a more comprehensive approach to encouraging ethically responsible scientific research compared to the currently typically adopted approach in RCR training. This essay focuses on developing a pedagogical approach that enables scientists to better understand and appreciate one important component of this model, what we call intrinsic ethics. Intrinsic ethical issues arise when values and ethical assumptions are embedded within scientific findings and analytical methods. Through a close examination of a case study and its application in teaching, namely, evaluation of climate change integrated assessment models, this paper develops a method and case for including intrinsic ethics within research ethics training to provide scientists with a comprehensive understanding and appreciation of the critical role of values and ethical choices in the production of research outcomes.

A tighter constraint on Earth-system sensitivity from long-term temperature and carbon-cycle observations.

The long-term temperature response to a given change in CO2 forcing, or Earth-system sensitivity (ESS), is a key parameter quantifying our understanding about the relationship between changes in Earth's radiative forcing and the resulting long-term Earth-system response. Current ESS estimates are subject to sizable uncertainties. Long-term carbon cycle models can provide a useful avenue to constrain ESS, but previous efforts either use rather informal statistical approaches or focus on discrete paleoevents. Here, we improve on previous ESS estimates by using a Bayesian approach to fuse deep-time CO2 and temperature data over the last 420 Myrs with a long-term carbon cycle model. Our median ESS estimate of 3.4 °C (2.6-4.7 °C; 5-95% range) shows a narrower range than previous assessments. We show that weaker chemical weathering relative to the a priori model configuration via reduced weatherable land area yields better agreement with temperature records during the Cretaceous. Research into improving the understanding about these weathering mechanisms hence provides potentially powerful avenues to further constrain this fundamental Earth-system property.

Considering uncertainties expands the lower tail of maize yield projections.

Crop yields are sensitive to extreme weather events. Improving the understanding of the mechanisms and the drivers of the projection uncertainties can help to improve decisions. Previous studies have provided important insights, but often sample only a small subset of potentially important uncertainties. Here we expand on a previous statistical modeling approach by refining the analyses of two uncertainty sources. Specifically, we assess the effects of uncertainties surrounding crop-yield model parameters and climate forcings on projected crop yield. We focus on maize yield projections in the eastern U.S.in this century. We quantify how considering more uncertainties expands the lower tail of yield projections. We characterized the relative importance of each uncertainty source and show that the uncertainty surrounding yield model parameters is the main driver of yield projection uncertainty.

Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks.

Homeowners around the world elevate houses to manage flood risks. Deciding how high to elevate a house poses a nontrivial decision problem. The U.S. Federal Emergency Management Agency (FEMA) recommends elevating existing houses to the Base Flood Elevation (the elevation of the 100-year flood) plus a freeboard. This recommendation neglects many uncertainties. Here we analyze a case-study of riverine flood risk management using a multi-objective robust decision-making framework in the face of deep uncertainties. While the quantitative results are location-specific, the approach and overall insights are generalizable. We find strong interactions between the economic, engineering, and Earth science uncertainties, illustrating the need for expanding on previous integrated analyses to further understand the nature and strength of these connections. Considering deep uncertainties surrounding flood hazards, the discount rate, the house lifetime, and the fragility can increase the economically optimal house elevation to values well above FEMA's recommendation.

Acute Infectious Gastroenteritis in Infancy and Childhood.

BACKGROUND: Despite the introduction of vaccination against rotavirus, and even though it can often be treated on an outpatient basis, acute infectious gastroenteritis is nevertheless the second most common non-traumatic cause of emergency hospitaliza - tion in children aged 1 to 5 years, accounting for approximately 9% of cases (39 410 cases in 2017). The most common path - ogens are viruses (47% rotavirus, 29% norovirus, and 14% adenovirus). METHODS: This review is based on publications retrieved by a selective search in PubMed employing the terms "acute gastro - enteritis children" AND "dehydration" OR "rehydration" OR "prevention," and by manual searching (based, for example, on reference lists and expert knowledge), with subsequent evaluation including consideration of the relevant guidelines. RESULTS: The degree of dehydration can be judged from weight loss and other clinical findings. In 17 randomized controlled trials conducted on a total of 1811 children with mild or moderate dehydration, oral rehydration with oral rehydration solution was just as effective as intravenous rehydration with respect to weight gain, duration of diarrhea, and fluid administration, and was associated with shorter hospital stays (weighted mean difference, -1.2 days; 95% confidence interval [-2.38; -0.02]). Oral rehydration therapy failed in 4% of patients [1; 7]. In children who are vomiting or who refuse oral rehydration solution, continuous nasogastric application is just as effective as intravenous rehydration and is the treatment of first choice. CONCLUSION: In Germany, children with mild or moderate dehydration are often hospitalized for intravenous rehydration therapy, despite the good evidence supporting ambulatory oral rehydration. Obstacles to intersectoral care, the nursing shortage, and inadequate reimbursement must all be overcome in order to reduce unnecessary hospitalizations and thereby lessen the risk of nosocomial infection.

Characterizing the deep uncertainties surrounding coastal flood hazard projections: A case study for Norfolk, VA.

Coastal planners and decision makers design risk management strategies based on hazard projections. However, projections can differ drastically. What causes this divergence and which projection(s) should a decision maker adopt to create plans and adaptation efforts for improving coastal resiliency? Using Norfolk, Virginia, as a case study, we start to address these questions by characterizing and quantifying the drivers of differences between published sea-level rise and storm surge projections, and how these differences can impact efforts to improve coastal resilience. We find that assumptions about the complex behavior of ice sheets are the primary drivers of flood hazard diversity. Adopting a single hazard projection neglects key uncertainties and can lead to overconfident projections and downwards biased hazard estimates. These results highlight key avenues to improve the usefulness of hazard projections to inform decision-making such as (i) representing complex ice sheet behavior, (ii) covering decision-relevant timescales beyond this century, (iii) resolving storm surges with a low chance of occurring (e.g., a 0.2% chance per year), (iv) considering that storm surge projections may deviate from the historical record, and (v) communicating the considerable deep uncertainty.