Substantial Uncertainty Research Articles

Automated Neuroprognostication Via Machine Learning in Neonates with Hypoxic-Ischemic Encephalopathy.

Neonatal hypoxic-ischemic encephalopathy is a serious neurologic condition associated with death or neurodevelopmental impairments. Magnetic resonance imaging (MRI) is routinely used for neuroprognostication, but there is substantial subjectivity and uncertainty about neurodevelopmental outcome prediction. We sought to develop an objective and automated approach for the analysis of newborn brain MRI to improve the accuracy of prognostication. We created an anatomic MRI template from a sample of 286 infants treated with therapeutic hypothermia, and labeled the deep gray-matter structures. We extracted quantitative information, including shape-related information, and information represented by complex patterns (radiomic measures), from each of these structures in all infants. We then trained an elastic net model to use either only these measures, only the infants' demographic and laboratory data, or both, to predict neurodevelopmental outcomes, as measured by the Bayley Scales of Infant and Toddler Development at 18 months of age. Among those infants for whom Bayley scores were available for cognitive, language, and motor outcomes, we found sets of MRI-based measures that could predict their Bayley scores with correlations that were greater than the correlations based on only the demographic and laboratory data, explained more of the variance in the observed scores, and generated a smaller error; predictions based on the combination of the demographic-laboratory and MRI-based measures were similar or marginally better. Our findings show that machine learning models using MRI-based measures can predict neurodevelopmental outcomes in neonates with hypoxic-ischemic encephalopathy across all neurodevelopmental domains and across the full spectrum of outcomes. ANN NEUROL 2024.

Transboundary sky waters in the Middle East: Definition, challenges, and opportunities

Transboundary water disputes in the Middle East have increased in recent years due to growing constraints on water resources. Efforts to harvest more water from the atmosphere through weather intervention projects have exacerbated existing conflicts. Here, we propose that atmospheric water vapor should be recognized as a transboundary resource that involves substantial uncertainty. As such, this note serves as a starting point for characterizing various components of this concept, the knowledge gaps, and a roadmap to address those gaps. These efforts would reduce uncertainties and help integrate the sky water into transboundary water negotiations and collaborative understanding.

Cost-effectiveness of a randomized controlled trial comparing low-dose aspirin to placebo for the prevention of recurrent preterm birth.

To assess the cost-effectiveness of low-dose aspirin compared to placebo for the prevention of recurrent preterm birth from a healthcare perspective. This was a cost-effectiveness analysis alongside a multicenter, randomized, double-blinded, placebo-controlled trial. We included women with a singleton pregnancy and a previous spontaneous preterm birth <37 weeks of gestation of a singleton. Women were randomized between aspirin 80 mg daily and placebo, initiated between 8 and 16 weeks of gestation. We estimated the difference in preterm births (<37 weeks of gestation), and maternal and neonatal healthcare costs using seemingly unrelated linear regression analyses. Bootstrapping was performed to estimate statistical uncertainty. A total of 387 women were included: 194 in the aspirin group and 193 in the placebo group. We observed a small, statistically non-significant difference in preterm birth (21.2% vs. 25.4%; risk difference -4.3%; 95% CI: -12.7% to 4.1%) and healthcare costs (mean -€99; 95% CI: -€2385 to €2325) in the aspirin group compared to placebo. The cost-effectiveness acceptability curve showed that the probability of aspirin being cost-effective was 54% for a willingness to pay threshold of €0 for one prevented preterm birth and 78% for €50 000 for one prevented preterm birth. Our findings suggest that aspirin is the dominant strategy over placebo for the prevention of preterm birth. However, there was substantial uncertainty around the results and definite conclusions regarding the cost-effectiveness of aspirin cannot be drawn.

Health Economic Evaluation of Antimicrobial Stewardship, Procalcitonin Testing, and Rapid Blood Culture Identification in Sepsis Care: A 90-Day Model-Based, Cost-Utility Analysis.

We evaluated the cost-effectiveness of a bundled intervention including an antimicrobial stewardship program (ASP), procalcitonin (PCT) testing, and rapid blood culture identification (BCID), compared with pre-implementation standard care in critically ill adult patients with sepsis. We conducted a decision tree model-based cost-effectiveness analysis alongside a previously published pre- and post-implementation quality improvement study. We adopted a public Canadian healthcare payer's perspective. Two intensive care units in Alberta with 727 adult critically ill patients were included. Our bundled intervention was compared with pre-implementation standard care. We collected healthcare resource use and estimated unit costs in 2022 Canadian dollars (CAD) over a time horizon from study entry to hospital discharge or death. We calculated the incremental net monetary benefit (iNMB) of the intervention group compared with the pre-intervention group. The primary outcome was cost per sepsis case. Secondary outcomes included readmission rates, Clostridioides difficile infections, mortality, and lengths of stay. Uncertainty was investigated using cost-effectiveness acceptability curves, cost-effectiveness plane scatterplots, and sensitivity analyses. Mean (standard deviation [SD]) cost per index hospital admission was CAD $83,251 ($107,926) for patients in the intervention group and CAD $87,044 ($104,406) for the pre-intervention group, though the difference ($3,793 [$7,897]) was not statistically significant. Costs were higher in the pre-intervention group for antibiotics, readmissions, and C. difficile infections. The intervention group had a lower mean expected cost; $110,580 ($108,917) compared with pre-intervention ($125,745 [$113,210]), with a difference of $15,165 ($8278). There were no statistically significant differences in quality adjusted life years (QALYs) between groups. The iNMB of the intervention group compared with pre-intervention was greater than $15,000 for willingness-to-pay (WTP) per QALY values of between $0 and $100,000. In our sensitivity analysis, the intervention was most likely to be cost-effective in roughly 56% of simulations at all WTP thresholds. Our bundled intervention of ASP, PCT, and BCID among adult critically ill patients with sepsis was potentially cost-effective, but with substantial decision uncertainty.

Validating the Precision and Accuracy of Coral Fragment Photogrammetry

Photogrammetry is a common tool for evaluating ecosystem-scale questions on coral reefs due to the ability to measure complex structures in situ. This technique is also increasingly being used at smaller scales to collect growth and morphometric data about individual coral fragments in manipulative experiments. However, there are substantial uncertainties in data quality and interpretation and limited reporting of the parameters useful for standardization across studies. There is a need to characterize the capabilities of photogrammetry as applied to coral fragments, to establish validation metrics for reporting, and to determine sources of variation in measurements to refine and improve methods. Here, we used fragments of two common reef-building corals (Montipora capitata and Porites compressa) and known size standards to evaluate accuracy and precision and present suggested validation metrics. We also used a tiered experimental design to evaluate sources of error in a photogrammetry workflow in a manipulative experiment using a purpose-built multi-camera workstation. We demonstrate extremely high accuracy (R2 &gt; 0.999) in determining the surface area and volume of known objects, as well as very high precision (average CV &lt; 0.01) in coral measurements during tests of reproducibility. These outcomes show the utility of fragment photogrammetry for experimental coral reef science and present suggested validation metrics and approaches that can help standardize data evaluation and interpretation in any application of photogrammetry to coral fragments.

Extreme Events Contributing to Tipping Elements and Tipping Points

AbstractThis review article provides a synthesis and perspective on how weather and climate extreme events can play a role in influencing tipping elements and triggering tipping points in the Earth System. An example of a potential critical global tipping point, induced by climate extremes in an increasingly warmer climate, is Amazon rainforest dieback that could be driven by regional increases in droughts and exacerbated by fires, in addition to deforestation. A tipping element associated with the boreal forest might also be vulnerable to heat, drought and fire. An oceanic example is the potential collapse of the Atlantic meridional overturning circulation due to extreme variability in freshwater inputs, while marine heatwaves and high acidity extremes can lead to coral reef collapse. Extreme heat events may furthermore play an important role in ice sheet, glacier and permafrost stability. Regional severe extreme events could also lead to tipping in ecosystems, as well as in human systems, in response to climate drivers. However, substantial scientific uncertainty remains on mechanistic links between extreme events and tipping points. Earth observations are of high relevance to evaluate and constrain those links between extreme events and tipping elements, by determining conditions leading to delayed recovery with a potential for tipping in the atmosphere, on land, in vegetation, and in the ocean. In the subsurface ocean, there is a lack of consistent, synoptic and high frequency observations of changes in both ocean physics and biogeochemistry. This review article shows the importance of considering the interface between extreme events and tipping points, two topics usually addressed in isolation, and the need for continued monitoring to observe early warning signs and to evaluate Earth system response to extreme events as well as improving model skill in simulating extremes, compound extremes and tipping elements.

Heterogenous Chemistry of I2O3 as a Critical Step in Iodine Cycling.

Global iodine emissions have been increasing rapidly in recent decades, further influencing the Earth's climate and human health. However, our incomplete understanding of the iodine chemical cycle, especially the fate of higher iodine oxides, introduces substantial uncertainties into atmospheric modeling. I2O3 was previously deemed a "dead end" in iodine chemistry; however, we provide atomic-level evidence that I2O3 can undergo rapid air-water or air-ice interfacial reactions within several picoseconds; these reactions are facilitated by prevalent chemicals on seawater such as amines and halide ions, to produce photolabile reactive iodine species such as HOI and IX (X = I, Br, and Cl). The heterogeneous chemistry of I2O3 leads to the rapid formation of iodate ions (IO3-), which is the predominant soluble iodine and its concentration cannot be well explained by current chemistry. These new loss pathways for atmospheric I2O3 can further explain its absence in field observations and its presence in laboratory experiments; furthermore, these pathways represent a heterogeneous recycling mechanism that can activate the release of reactive iodine from oceans, polar ice/snowpack, or aerosols. Rapid reactive adsorption of I2O3 can also promote the growth of marine aerosols. These findings provide novel insights into iodine geochemical cycling.

Climate variability and worldwide migration: Current evidence and future projections

Abstract The literature linking climatic drivers and migration is growing, but there is still limited evidence and substantial uncertainty regarding future bilateral flows driven by climate stress on a global scale. The aim of this paper is to fill this gap by projecting changes in the flows of international migrants from medium-term population and climate change projections. We employ a bilateral gravity equation for emigration rates controlling for decadal weather averages of temperature, precipitation, droughts, and extreme precipitation in the origin countries. We use the parameter estimates of the gravity equation to estimate global, regional, and country-by-country emigration flows for several combinations of socio-economic development and climate change. Results indicate that global emigration flows are projected to increase to around 110 million in 2060 for SSP1 and RCP 4.5 and SSP5 and RCP 4.5; to 135 million for SSP5 and RCP 8.5; to 163 million for SSP3 and RCP 4.5. We report that changes in emigration flows are largely due to population growth in the origin countries.

How to ensure an appropriate oral health workforce? Modelling future scenarios for the Netherlands

BackgroundCurrent methods for oral health workforce planning lack responsiveness to dynamic needs, hampering efficiency, equity and sustainability. Effective workforce planning is vital for resilient health care systems and achieving universal health coverage. Given this context, we developed and operationalised a needs-adaptive oral health workforce planning model and explored the potential of various future scenarios.MethodsUsing publicly available data, including the Special Eurobarometer 330 Oral Health Survey, we applied the model in a hypothetical context focusing on the Dutch population’s dental needs from 2022 to 2050. We compared current and future provider supply and requirement and examined, in addition to a base case scenario, several alternative scenarios. These included epidemiological transition scenarios with different oral health morbidity trajectories, skill-mix scenarios with independent oral hygienists conducting check-ups and multiple dental student intake and training duration (5 instead of 6 years) scenarios.ResultsBased on the aforementioned historical data, our model projects that provider requirement will exceed supply for the planning period. If the percentage of people having all natural teeth increases by 10% or 20% in 2032, 34 or 68 additional full-time equivalent (FTE) dentists will be required, respectively, compared to the base case scenario. In the skill-mix scenario, the model indicates that prioritising oral hygienists for check-ups and shifting dentists’ focus to primarily complex care could address population needs more efficiently. Among the student intake and training duration scenarios, increasing intake to 375 and, to a lesser extent, reducing training to 5 years is projected to most effectively close the provider gap.ConclusionsThe study underscores the importance of understanding oral health morbidity trajectories for effective capacity planning. Due to limited dental epidemiological data, projections carry substantial uncertainty. Currently, demand for FTE dentists seems to exceed supply, though this may vary with epidemiological changes. Skill-mix strategies could offer efficiency gains by redistributing tasks, while adjustments in dental intake and training duration could also help address the requirement-supply gap. Resolving dentistry workforce challenges requires a multifaceted approach, including strengthening oral epidemiology projections, addressing the root causes of dental health issues and prioritising harmonious dental public health and general practice prevention measures.

Primary Modes of Northern Hemisphere Snowfall Particle Size Distributions

Abstract A comprehensive understanding of snowfall microphysics is crucial for enhancing the accuracy of remote sensing snowfall retrievals. However, variations in regional and seasonal snow particle size distributions (PSDs) contribute substantial uncertainty. Here, we examine snowfall PSDs from across the Northern Hemisphere, applying Principal Component Analysis (PCA) to disdrometer observations with the aim of identifying dominant modes of variability across varying regional climates. The PCA revealed three Empirical Orthogonal Functions (EOFs) that account for a combined 95% of the variability across the dataset, which are attributed to latent linear embeddings of snowfall intensity (EOF1), snowfall character (EOF2) and snowfall regime (EOF3). Examining point clusters with the highest combined EOF values reveals six distinct modes of variability (i.e., Principal Component [PC] groups) with unique PSD traits. These groups are then correlated with environmental factors using data from collocated vertically pointing radar, surface meteorology, and reanalysis to assist in assigning physical attributes. The first and second PC groups, linked to EOF1’s intensity embedding, are described by their PSD intercepts, snowfall rates, and reflectivity and Doppler velocity values, representing low and high intensity snowfall modes, respectively. The third and fourth PC groups, associated with EOF2’s character embedding, are defined by temperature, fall speed, and density, indicative of cold, fluffy snowfall and warm, dense snowfall, respectively. The fifth and sixth PC groups, related to EOF3’s regime embedding, are distinguished by their PSD slope, snowfall rate, and reflectivity profiles, signifying shallow, weak convective systems with small particles, and deep, stratiform snowfall events with large aggregates, respectively.

Assessing spatiotemporal variations of soil organic carbon and its vulnerability to climate change: A bottom-up machine learning approach

Soil organic carbon (SOC) is a crucial component of the terrestrial carbon cycle and essential for agricultural productivity. Quantifying its sensitivity to future climate change is vital for sustaining agricultural practices and mitigating greenhouse gas emissions. However, this remains a challenge as long-term SOC data are scarce and substantial uncertainties regarding future climate scenarios. This study presents a bottom-up machine learning framework to assess the spatiotemporal variations of SOC and its vulnerability to climate change in the Jinghe River Basin, a typical loess hilly and gully watershed. Firstly, the long-term (2000–2023) dynamics of SOC was estimated by integrating in-situ measurements with machine learning techniques. Results show that the high SOC values are primarily distributed in the farmland of the mountain-loess transition zone, while the low-value areas are mainly found in the loess region. During the study period, the SOC content exhibited a slight increasing trend with a rate of 0.02 ​g ​kg−1 ​yr−1 (p ​= ​0.449). The vulnerability of farmland surface SOC to future climate change was then evaluated by combining a robust machine learning model with the bottom-up framework. To this end, the study explored a wide range of possible future climates to identify critical climate thresholds and their spatial variation across the basin’s farmlands. Based on this analysis, this research found that the farmland in the northern basin is generally more susceptible to changing climate with even marginal rises in temperature could lead to severe loss in SOC. These results highlight the need for proactive climate adaptation strategies to safeguard SOC in vulnerable agricultural landscapes, ensuring soil health and resilience in the face of climate change.

Field Validation of the Superelevation Method for Debris‐Flow Velocity Estimation Using High‐Resolution Lidar and UAV Data

AbstractEstimating flow velocities is key to assessing hazards associated with debris flows. One approach to post‐event velocity estimation is the superelevation method, which uses debris‐flow mudlines to measure the cross‐channel surface inclination, or superelevation, produced by centripetal forces acting on the flow in a bend. Flow velocities are then calculated using a subjective parameterization of the forced vortex equation modified to include a debris‐flow specific correction factor. Subjective parameterization of this equation leads to substantial variability and uncertainty in the resulting flow velocities. We present an analysis of the reliability of the superelevation method using a large UAV‐based data set of 14 debris flows with front velocities of ∼0.8–6.5 m s−1 and cross‐channel surface inclinations of ∼0.6–8.5°, as well as a validation for a single debris flow measured using high‐resolution, high‐frequency 3D lidar data fused to video imagery. The validation event indicates that when the flow surface inclination can be measured directly, the forced vortex equation produces excellent results without needing a correction factor for Froude numbers ranging from 0.7 to 1.5. This finding indicates that the main challenge with the superelevation method lies in obtaining accurate measurements of superelevation from the mudlines, and that a correction factor may serve to compensate for measurement difficulties rather than variable flow properties. For very small and highly subcritical flows, the superelevation method may generate a large overestimation of flow velocities.

Health and air pollutant emission impacts of net zero CO2 by 2050 scenarios from the energy modeling forum 37 study

Carbon dioxide and non-greenhouse gas air pollutants are emitted from many of the same sources. Decarbonization actions thus typically yield air pollutant emission reductions, resulting in significant air quality benefits. Although several studies have highlighted this connection, including in the context of net zero carbon emission targets, substantial uncertainty remains regarding how alternative technological pathways to this goal will affect the spatial distribution and magnitude of air pollutants. Comprehensive multi-model and multi-scenario analyzes are needed to explore the relative impacts of alternative pathways. Our study begins to address this gap by leveraging the results from the recent Energy Modeling Forum 37 inter-model comparison exercise on U.S. decarbonization pathways. Comparing the results of the six teams who submitted air pollutant emissions suggests that strategies that target net zero U.S. carbon emissions would yield significant reductions in many air pollutants, and that this finding is generally robust across pathways. However, some energy sources, such as biomass and fossil fuels with carbon capture, will emit air pollutants and can potentially influence the magnitude, spatial distribution, and even sign of localized air pollutant emission changes. In the second part of this analysis, a simplified air quality and health impacts screening model is used to evaluate the air quality impacts in 2035 of sectoral emission changes from the three models that provided sectoral detail. Relative to a reference scenario, a net zero pathway is estimated to reduce fine particulate matter concentrations across the contiguous U.S., with health benefits from reduced mortality ranging from $65 billion to $250 billion in 2035 alone (2023$s). These benefits would be expected to grow over time as the net zero trajectory becomes more stringent. Both the magnitude of potential benefits and the substantial variation of the projections across models underscore the need for an EMF-like inter-model comparison exercise focused on air quality.

No evidence for interstellar fireballs in the CNEOS database

Context. The detection of interstellar meteors, especially meteorite-dropping meteoroids, would be transformative, as this would enable direct sampling of material from other stellar systems on Earth. One candidate is the fireball observed by U.S. government sensors on January 8, 2014. It has been claimed that fragments of this meteoroid have been recovered from the ocean floor near Papua New Guinea and that they support an extrasolar origin. Based on its parameters reported in the Center for Near Earth Object Studies (CNEOS) catalog, the fireball exhibits a hyperbolic excess velocity that indicates an interstellar origin; however, the catalog does not report parameter uncertainties. Aims. To achieve a clear confirmation of the fireball’s interstellar origin, we assessed the underlying error distributions of the catalog data. Our aim was also to confirm whether the fragments of this meteoroid survived passage through the atmosphere and assess all conditions needed to unambiguously determine the fragments’ origin. Methods. We approached the investigation of the entire catalog using statistical analyses and modeling, and we provide a comprehensive analysis of the individual hyperbolic CNEOS cases. Results. We have developed several independent arguments indicating substantial uncertainties in the velocity and radiant position of the CNEOS events. We determined that all the hyperbolic fireballs exhibit significant deviations from the majority of the events in one of their velocity components, and we show that such mismeasurements can produce spurious parameters. According to our estimation of the speed measurement uncertainty for the catalog, we found that it is highly probable that such a catalog containing only Sun-bound meteors would show at least one event that appears highly unlikely to be Sun-bound. We also establish that it is unlikely that any fragments from a fireball traveling at the high inferred velocities could survive passage through the atmosphere. When assuming a much lower velocity, some fragments of this meteoroid could survive; however, they would be of a common Solar System origin and thus highly probable to be indistinguishable from the quantity of other local micrometeorites that have gradually accumulated on the sea floor. Conclusions. We conclude that there is no evidence in the CNEOS data to confirm or reject the interstellar origin of any of the nominally hyperbolic fireballs in the CNEOS catalog. Therefore, the claim of an interstellar origin for the fireball recorded over Papua New Guinea in 2014 remains unsubstantiated. We have also gathered arguments that refute the claim that the collected spherules from the sea floor originated in the body of this fireball.

Impacts of Black-hole-forming Supernova Explosions on the Diffuse Neutrino Background

The flux spectrum, event rate, and experimental sensitivity are investigated for the diffuse supernova (SN) neutrino background (DSNB), which originates from past stellar collapses and is also known as a supernova relic neutrino background. For this purpose, the contribution of collapses that lead to successful supernova explosion and black hole (BH) formation simultaneously, which are suggested to be a nonnegligible population from the perspective of Galactic chemical evolution, is taken into account. If the BH-forming SNe involve matter fallback onto the protoneutron star for the long term, their total emitted neutrino energy becomes much larger than that of ordinary SNe and failed SNe (BH formation without explosion). Then, in the case of the normal mass hierarchy in neutrino oscillations and with half of all core-collapse SNe being BH-forming SNe, the expected event rate according to the current DSNB model is enhanced by up to a factor of 2 due to the BH-forming SNe. While substantial uncertainties exist regarding the duration of the matter fallback, which determines the total amount of emitted neutrinos, and the fraction of BH-forming SNe, the operation time required to detect the DSNB at Hyper-Kamiokande would be reduced by such contribution in any case.

Comment on Krüger, L. Decreasing Trends of Chinstrap Penguin Breeding Colonies in a Region of Major and Ongoing Rapid Environmental Changes Suggest Population Level Vulnerability. Diversity 2023, 15, 327

Historical data on chinstrap penguin (Pygoscelis antarctica) breeding population sizes are sparse and sometimes highly uncertain, making it hard to estimate true population trajectories. Yet, information on population trends is desirable as changes in population size can help inform conservation assessments. Recently, Krüger (2023) (Diversity 2023, 15, 327) used chinstrap penguin nest count data to predict breeding colony size trends between 1960 and 2020, to estimate whether the level of population change within three generations exceeded IUCN Red List Criteria for “Vulnerable” populations. Chinstrap penguin population trends are an important research topic, but we caution that Krüger (2023)’s statistical analyses (intended to form the foundation for drawing valid, evidence-based inferences from sparse data) contain fundamental errors that invalidate that paper’s findings. We discuss oversights in several key steps (data processing, exploratory data analysis, model fitting, model evaluation, and prediction) of that paper’s analysis to help others detect and avoid some of the pitfalls associated with estimating population trends via mixed models. We also show through reanalysis that improved statistical modelling can yield better predictions of chinstrap penguin population trends, at least within the range of observed data. This case study highlights (1) the profound influence that seemingly minor differences in modelling procedures (both unintentional errors and other decisions) can have on predictions of population trends, and (2) the substantial inherent uncertainty in population trend predictions derived from sparse, heterogenous data.

Characteristics, impacts and future research directions of Mongolian peatlands

Mongolia is an important peatland distribution area in the world. Over the past few decades, Mongolian peatlands have undergone significant degradation due to climate change and human activities, yet there remains substantial uncertainty about the impacts of Mongolian peatland changes on regional environment and human society. Here, compiling the data of peatland distribution, climate, human activity, as well as the permafrost, we systematically review the distribution, changes, and the ecosystem service values of the Mongolian peatlands in the face of climate warming and intensifying human activities. The current data show that the total area of peatland in the Mongolian is 15500~27000 km2, and most of the peatlands are distributed in permafrost regions, while the accuracies of these maps were not assessed. In addition to climate warming, overgrazing, mining activities, and transportation, we suggest permafrost degradation also poses significant threatens on the peatlands. Although the importance of Mongolian peatlands has been recognized, the ecosystem service values, including water provision, habitat quality, carbon fixation, soil conservation, and wind erosion prevention largely remain unknown. Currently, efforts have been made to protect the Mongolian grassland, but there are no specific measures to combat peatland degradation. To better understand the changes and roles of peatland ecosystems in regulating regional development, we propose three research directions for future studies: 1) produce a detailed map of peatland distribution based on field survey data, new remote sensing data, and new algorithms; 2) Unveil the mechanisms underlying the interaction of peat, vegetation, and permafrost; 3) Evaluate the ecosystem services of Mongolian peatlands. These knowledges are the scientific foundation to propose and implement measures to protect, maintain, and sustainably utilize peatlands in Mongolia.

Effectiveness and efficiency of immunisation strategies to prevent RSV among infants and older adults in Germany: a modelling study

BackgroundRecently, several novel RSV immunisation products that protect infants and older adults against RSV disease have been licensed in Europe. We estimated the effectiveness and efficiency of introducing these RSV immunisation strategies in Germany.MethodsWe used a Bayesian framework to fit a deterministic age-structured dynamic transmission model of RSV to sentinel surveillance and RSV-specific hospitalisation data in Germany from 2015 to 2019. The calibrated model was used to evaluate different RSV intervention strategies over 5 years: long-acting, single-dose monoclonal antibodies (mAbs) in high-risk infants aged 1–5 months; long-acting mAbs in all infants aged 1–5 months; seasonal vaccination of pregnant women and one-time seasonal vaccination of older adults (75 + /65 + /55 + years). We performed sensitivity analysis on vaccine uptake, seasonal vs. year-round maternal vaccination, and the effect of under-ascertainment for older adults.ResultsThe model was able to match the various RSV datasets. Replacing the current short-acting mAB for high-risk infants with long-acting mAbs prevented 1.1% of RSV-specific hospitalisations in infants per year at the same uptake. Expanding the long-acting mAB programme to all infants prevented 39.3% of infant hospitalisations per year. Maternal vaccination required a larger number to be immunised to prevent one additional hospitalisation than a long-acting mAB for the same uptake. Vaccination of adults older than 75 years at an uptake of 40% in addition to Nirsevimab in all infants prevented an additional 4.5% of all RSV hospitalisations over 5 years, with substantial uncertainty in the correction for under-ascertainment of the RSV burden.ConclusionsImmunisation has the potential to reduce the RSV disease burden in Germany.

Uncertainty in model estimates of global groundwater depth

Abstract Knowing the depth at which groundwater can be found below the land surface is critical for understanding its potential accessibility by ecosystems and society. Uncertainty in global scale water table depth (WTD) limits our ability to assess groundwater’s role in a water cycle altered by changing climate, land cover, and human water use. Global groundwater models offer a top–down pathway to gain this knowledge, but their uncertainty is currently poorly quantified. Here, we investigate four global groundwater models and reveal steady-state WTD disagreements of more than 100 m for one-third of the global land area. We find that model estimates of land areas with shallow groundwater at &lt;10 m depth vary from 10% to 71% (mean of 23%). This uncertainty directly translates into subsequent assessments, as land areas with potential groundwater accessibility for forests, population, and areas equipped for irrigation, differ substantially depending on the chosen model. We explore reasons for these differences and find that contrary to observations, 3 out of 4 models show deeper water tables in humid than in arid climates and greatly overestimate how strongly topographic slope controls WTD. These results highlight substantial uncertainty associated with any global-scale groundwater analysis, which should be considered and ultimately reduced.

Stomatal closure as a driver of minimum leaf conductance declines at high temperature and vapor pressure deficit in Quercus.

Rising global temperatures and vapor pressure deficits (VPD) are increasing plant water demand and becoming major drivers of large-scale plant mortality. Controlling transient leaf water loss after stomatal closure (gmin) is recognized as a key trait determining how long plants survive during soil drought. Yet, substantial uncertainty remains regarding how gmin responds to elevated temperatures and VPD and the underlying mechanisms. We measured gmin in 24 Quercus species from temperate and Mediterranean climates to determine if gmin was sensitive to a coupled temperature and VPD increase. We also explored mechanistic links to phenology, climate, evolutionary history, and leaf anatomy. We found that gmin in all species exhibited a non-linear negative temperature and VPD dependence. At 25°C (VPD = 2.2 kPa), gmin varied from 1.19 to 8.09 mmol m-2 s-1 across species but converged to 0.57 ± 0.06 mmol m-2 s-1 at 45°C (VPD = 6.6 kPa). In a subset of species, the effect of temperature and VPD on gmin was reversible and linked to the degree of stomatal closure, which was greater at 45°C than at 25°C. Our results show that gmin is dependent on temperature and VPD, is highly conserved in Quercus species, and is linked to leaf anatomy and stomatal behavior.