Search Results (59)

This study presents a methodology for evaluating the impact of the pandemic on mortality rates in Italy. The primary objectives are to define criteria for identifying a ‘rise in mortality’, establish a robust evaluation approach, and assess pandemic repercussions using the proposed framework. To conduct a comparative analysis of mortality estimates, two classical models were employed: the Lee–Carter and the Renshaw–Haberman models. The analysis involved utilising actuarial tables and mortality models to quantify pandemic-induced excess deaths by calculating the disparity between these estimates. The proposed method aims to provide a comprehensive and clear understanding of the impact of the pandemic on mortality in Italy. Full article

Capital investment in longevity science—research targeting the biological processes of aging through interventions like cellular reprogramming, AI-driven drug discovery, and biological age monitoring—may create significant divergence between traditional actuarial projections and emerging mortality improvements. This paper examines how accelerating investment in life extension technologies affects mortality improvement trajectories beyond conventional actuarial assumptions, building on the comprehensive investment landscape analysis documented in “Investors in Longevity” supported by venture capital databases, industry reports, and regulatory filings. We introduce an Investment-Adjusted Mortality Model (IAMM) that incorporates capital allocation trends as leading indicators of mortality improvement acceleration. Under high-investment scenarios (annual funding of USD 15+ billion in longevity technologies), current insurance products may significantly underestimate longevity risk, creating potential solvency challenges. Our statistical analysis demonstrates that investment-driven mortality improvements—actual reductions in death rates resulting from new anti-aging interventions—could exceed traditional projections by 18–31% by 2040. We validate our model by backtesting historical data, showing improved predictive performance (35% reduction in MAPE) compared to traditional Lee–Carter approaches during periods of significant medical technology advancement. Based on these findings, we propose modified insurance structures, including dynamic mortality-linked products and biological age underwriting, quantifying their effectiveness in reducing longevity risk exposure by 42–67%. These results suggest the need for actuarial science to incorporate investment dynamics in response to the changing longevity investment environment detailed in “Investors in Longevity”. The framework presented provides both theoretically grounded and empirically tested tools for incorporating investment dynamics into mortality projections and insurance product design, addressing gaps in current risk management approaches for long-term mortality exposure. Full article

Background: Visual evoked potentials (VEPs) are used to detect chiasmal misrouting associated with albinism. However, VEPs are only performed in specialist centres and typically have long waiting lists. The portable electrophysiology device RETeval^® shows promise as a clinical screening tool across a range of ophthalmic conditions. Here, we explore its utility in detecting chiasmal abnormalities associated with albinism. Methods: Flash VEPs were recorded on the RETeval^® and by standard ISCEV techniques for 27 patients with suspected albinism and 40 control patients as part of routine appointments. We retrospectively investigated the agreeability between the two methods. The amplitude/latency of the main component was measured for standard VEPs whilst a correlation value of interhemispheric difference was calculated for the RETeval^® data. Results: We demonstrate a significant difference between albinism patients and controls (p < 0.001) with respect to the interhemispheric difference identified by the RETeval^®. By applying a threshold of 0.001865 to the correlation value, the RETeval^® detected chiasmal misrouting in all 27 patients with albinism and had 97% agreeability to standard testing. Conclusions: This study shows the potential of using the RETeval^® as a clinical tool for the diagnosis of chiasmal anomalies in albinism. The RETeval^® has significant time/cost savings which could hasten diagnoses. Full article

Age-specific mortality forecasting in Kazakhstan plays a crucial role in public health planning and healthcare management. By predicting mortality rates across different age groups, policymakers, healthcare providers, and researchers can make informed decisions that improve health outcomes and allocate resources more effectively. We analyzed Kazakhstan’s annual mortality data from 1991 to 2023. The Lee–Carter model and its extensions were used to predict mortality. But they did not give satisfactory results for predicting mortality. Including external socio-economic factors in the model did not improve the forecasting accuracy. The accuracy of the forecast increased with a separate analysis of the subpopulations of children and adults. This was because, since 1991 in the children subpopulation there has been a pronounced linear downward trend, while in the adult subpopulation the global trend in mortality dynamics is nonlinear. As a result, it is possible to make forecasts for 7 years with a high degree of accuracy (error < 10%) and forecast for the 8th, 9th, and 10th years with a “good” degree of accuracy (error 10–20%). In 2024–2033, a further mortality decline is expected in most age groups. Only in groups over 80 years old is a slight increase in mortality predicted in the coming year, but then a downward trend will be observed again. Full article

As life expectancy increases, pension plans face growing longevity risk. Standardized longevity-linked securities such as survivor contracts allow pension plans to transfer this risk to capital markets. However, more consensus is needed on the appropriate mortality model and premium principle to price these contracts. This paper investigates the impact of the mortality model and premium principle choice on the pricing, risk measurement, and modeling of survivor contracts. We present a framework for evaluating risk measures associated with survivor contracts, specifically survivor forwards (S-forward) and survivor swaps (S-swaps). We analyze how the mortality model and premium principle assumptions affect pricing and risk measures (value-at-risk and expected shortfall). Four mortality models (Lee–Carter, Renshaw–Haberman, Cairns–Blake–Dowd, and M6) and eight premium principles (Wang, proportional hazard, dual power, Gini, exponential, standard deviation, variance, and median absolute deviation) are considered. Our analysis highlights the need to refine mortality models and premium principles to enhance pricing accuracy and risk management. We also suggest regulators and practitioners incorporate expected shortfall alongside value-at-risk to capture tail risks and improve capital allocation. Full article

The Module-0 Demonstrator is a single-phase 600 kg liquid argon time projection chamber operated as a prototype for the DUNE liquid argon near detector. Based on the ArgonCube design concept, Module-0 features a novel 80k-channel pixelated charge readout and advanced high-coverage photon detection system. In this paper, we present an analysis of an eight-day data set consisting of 25 million cosmic ray events collected in the spring of 2021. We use this sample to demonstrate the imaging performance of the charge and light readout systems as well as the signal correlations between the two. We also report argon purity and detector uniformity measurements and provide comparisons to detector simulations. Full article

Background: Obstetric Anal Sphincter Injuries (OASI) are associated with significant morbidity. Data regarding induction of labor (IOL) and risk of OASI is conflicting. The objective of this study is to evaluate if IOL increases the odds of OASI when compared to spontaneous labor. Methods: This is a retrospective case–control study in women with term, singleton pregnancies, who had a vaginal delivery at a single, academic center in an urban setting from October 2015 to December 2021. Individuals with the primary outcome, OASI, were identified and matched with controls (no OASI) by delivery date. Results: 303 OASI individuals were identified and matched with 1106 controls. Women with OASI were more likely to be White or Asian, have commercial insurance, and have a previous cesarean delivery (CD). IOL increased the likelihood of OASI by 49% compared to spontaneous labor (OR 1.49, 95% CI [1.138, 1.949]). IOL was no longer significant when adjusting for confounding variables and known risk factors. Conclusion: IOL was not associated with OASI when accounting for known antepartum and intrapartum risk factors. Further investigation of modifiable and non-modifiable risks during labor is imperative to decrease the risk of OASI and associated pelvic floor disorders. Full article

Glassy carbon (GC) microelectrodes have been successfully used for the detection of electroactive neurotransmitters such as dopamine and serotonin through voltammetry. However, non-electroactive neurotransmitters such as glutamate, lactate, and gamma-aminobutyric acid (GABA) are inherently unsuitable for detection through voltammetry techniques without functionalizing the surface of the microelectrodes. To this end, we present here the immobilization of the L-glutamate oxidase (GluOx) enzyme on the surface of GC microelectrodes to enable the catalysis of a chemical reaction between L-glutamate, oxygen, and water to produce H₂O₂, an electroactive byproduct that is readily detectable through voltammetry. This immobilization of GluOx on the surface of bare GC microelectrodes and the subsequent catalytic reduction in H₂O₂ through fast-scan cyclic voltammetry (FSCV) helped demonstrate the indirect in vitro detection of glutamate, a non-electroactive molecule, at concentrations as low as 10 nM. The functionalized microelectrodes formed part of a four-channel array of microelectrodes (30 μm × 60 μm) on a 1.6 cm long neural probe that was supported on a flexible polymer, with potential for in vivo applications. The types and strengths of the bond between the GC microelectrode surface and its functional groups, on one hand, and glutamate and the immobilized functionalization matrix, on the other hand, were investigated through molecular dynamic (MD) modeling and Fourier transform infrared spectroscopy (FTIR). Both MD modeling and FTIR demonstrated the presence of several covalent bonds in the form of C-O (carbon–oxygen polar covalent bond), C=O (carbonyl), C-H (alkenyl), N-H (hydrogen bond), C-N (carbon–nitrogen single bond), and C≡N (triple carbon–nitrogen bond). Further, penetration tests on an agarose hydrogel model confirmed that the probes are mechanically robust, with their penetrating forces being much lower than the fracture force of the probe material. Full article

We introduce the function principal component regression (FPCR) forecasting method to model and forecast age-specific survival functions observed over time. The age distribution of survival functions is an example of constrained data whose values lie within a unit interval. Because of the constraint, such data do not reside in a linear vector space. A natural way to deal with such a constraint is through an invertible logit transformation that maps constrained onto unconstrained data in a linear space. With a time series of unconstrained data, we apply a functional time-series forecasting method to produce point and interval forecasts. The forecasts are then converted back to the original scale via the inverse logit transformation. Using the age- and sex-specific survival functions for Australia, we investigate the point and interval forecast accuracies for various horizons. We conclude that the functional principal component regression (FPCR) provides better forecast accuracy than the Lee–Carter (LC) method. Therefore, we apply FPCR to calculate annuity pricing and compare it with the market annuity price. Full article

Adverse experiences (e.g., acute stress) and alcohol misuse can both impair skeletal muscle homeostasis, resulting in reduced protein synthesis and greater protein breakdown. Exposure to acute stress is a significant risk factor for engaging in alcohol misuse. However, little is known about how these factors together might further affect skeletal muscle health. To that end, this study investigated the effects of acute stress exposure followed by a period of binge-patterned alcohol drinking on signaling factors along mouse skeletal muscle protein synthesis (MPS) and degradation (MPD) pathways. Young adult male C57BL/6J mice participated in the Drinking in the Dark paradigm, where they received 2–4 h of access to 20% ethanol (alcohol group) or water (control group) for four days to establish baseline drinking levels. Three days later, half of the mice in each group were either exposed to a single episode of uncontrollable tail shocks (acute stress) or remained undisturbed in their home cages (no stress). Three days after stress exposure, mice received 4 h of access to 20% ethanol (alcohol) to model binge-patterned alcohol drinking or water for ten consecutive days. Immediately following the final episode of alcohol access, mouse gastrocnemius muscle was extracted to measure changes in relative protein levels along the Akt-mTOR MPS, as well as the ubiquitin-proteasome pathway (UPP) and autophagy MPD pathways via Western blotting. A single exposure to acute stress impaired Akt singling and reduced rates of MPS, independent of alcohol access. This observation was concurrent with a potent increase in heat shock protein seventy expression in the muscle of stressed mice. Alcohol drinking did not exacerbate stress-induced alterations in the MPS and MPD signaling pathways. Instead, changes in the MPS and MPD signaling factors due to alcohol access were primarily observed in non-stressed mice. Taken together, these data suggest that exposure to a stressor of sufficient intensity may cause prolonged disruptions to signaling factors that impact skeletal muscle health and function beyond what could be further induced by periods of alcohol misuse. Full article

This work proposes a simple model to take into account the annual volatility of the mortality level observed on the scale of a country like France in the construction of prospective mortality tables. By assigning a frailty factor to a basic hazard function, we generalise the Lee–Carter model. The impact on prospective life expectancies and capital requirements in the context of a life annuity scheme is analysed in detail. Full article

Population events such as natural disasters, pandemics, extreme weather, and wars might cause jumps that have an immediate impact on mortality rates. The recent COVID-19 pandemic has demonstrated that these events should not be treated as nonrepetitive exogenous interventions. Therefore, mortality models incorporating jump effects are particularly important to capture the adverse mortality shocks. The mortality models with jumps, which we consider in this study, differ in terms of the duration of the jumps–transitory or permanent–the frequency of the jumps, and the size of the jumps. To illustrate the effect of the jumps, we also consider benchmark mortality models without jump effects, such as the Lee-Carter model, Renshaw and Haberman model and Cairns-Blake-Dowd model. We discuss the performance of all the models by analysing their ability to capture the mortality deterioration caused by COVID-19. We use data from different countries to simulate the mortality rates for the pandemic and post-pandemic years and examine their accuracy in forecasting the mortality jumps due to the pandemic. Moreover, we also examine the jump-free and jump models in terms of their impact on insurance pricing, specifically term annuity and life insurance present values calibrated for both pre- and post-COVID data. Full article

Human mortality has been improving faster than expected over the past few decades. This unprecedented improvement has caused significant financial stress to pension plan sponsors and annuity providers. The widely recognized Lee–Carter model often assumes linearity in its period effect as an integral part of the model. Nevertheless, deviation from linearity has been observed in historical mortality data. In this paper, we investigate the applicability of four nonlinear time-series models: threshold autoregressive model, Markov switching model, structural change model, and generalized autoregressive conditional heteroskedasticity model for mortality data. By analyzing the mortality data from England and Wales and Italy spanning the years 1900 to 2019, we compare the goodness of fit and forecasting performance of the four nonlinear models. We then demonstrate the implications of nonlinearity in mortality modeling on the pricing of longevity bonds as a practical illustration of our findings. Full article

A recent study demonstrated that noninvasive measurements of cortical hemodynamics and metabolism in the resting human prefrontal cortex can facilitate quantitative metrics of unilateral mitochondrial–hemodynamic coupling and bilateral connectivity in infraslow oscillation frequencies in young adults. The infraslow oscillation includes three distinct vasomotions with endogenic (E), neurogenic (N), and myogenic (M) frequency bands. The goal of this study was to prove the hypothesis that there are significant differences between young and older adults in the unilateral coupling (uCOP) and bilateral connectivity (bCON) in the prefrontal cortex. Accordingly, we performed measurements from 24 older adults (67.2 ± 5.9 years of age) using the same two-channel broadband near-infrared spectroscopy (bbNIRS) setup and resting-state experimental protocol as those in the recent study. After quantification of uCOP and bCON in three E/N/M frequencies and statistical analysis, we demonstrated that older adults had significantly weaker bilateral hemodynamic connectivity but significantly stronger bilateral metabolic connectivity than young adults in the M band. Furthermore, older adults exhibited significantly stronger unilateral coupling on both prefrontal sides in all E/N/M bands, particularly with a very large effect size in the M band (>1.9). These age-related results clearly support our hypothesis and were well interpreted following neurophysiological principles. The key finding of this paper is that the neurophysiological metrics of uCOP and bCON are highly associated with age and may have the potential to become meaningful features for human brain health and be translatable for future clinical applications, such as the early detection of Alzheimer’s disease. Full article

Stochastic mortality models seek to forecast future mortality rates; thus, it is apparent that the objective variable should be the mortality rate expressed in the original scale. However, the performance of stochastic mortality models—in terms, that is, of their goodness-of-fit and prediction accuracy—is often based on the logarithmic scale of the mortality rate. In this article, we examine whether the same forecast outcomes are obtained when the performance of mortality models is assessed based on the original and log scales of the mortality rate. We compare four different stochastic mortality models: the original Lee–Carter model, the Lee–Carter model with (log)normal distribution, the Lee–Carter model with Poisson distribution and the median Lee–Carter model. We show that the preferred model will depend on the scale of the objective variable, the selection criteria measure and the range of ages analysed. Full article