Long-term cost-effectiveness analysis of tirzepatide versus semaglutide 1.0 mg for the management of type 2 diabetes in the United States

AIM

To evaluate the long-term cost-effectiveness of tirzepatide (5, 10 and 15 mg doses), a novel glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) receptor agonist, versus semaglutide 1.0 mg, an injectable glucagon-like peptide-1 receptor agonist, based on the results of the head-to-head SURPASS-2 trial, from a US healthcare payer perspective.

MATERIALS AND METHODS

The PRIME Type 2 Diabetes Model was used to make projections of clinical and cost outcomes over a 50-year time horizon. Baseline cohort characteristics, treatment effects and adverse event rates were derived from the 40-week SURPASS-2 trial. Intensification to insulin therapy occurred when HbA1c reached 7.5%, in line with American Diabetes Association recommendations. Direct costs in 2021 US dollars (US$) and health state utilities were derived from published sources. Future costs and clinical benefits were discounted at 3% annually.

RESULTS

All three doses of tirzepatide were associated with lower diabetes-related complication rates, improved life expectancy, improved quality-adjusted life expectancy and higher direct costs versus semaglutide. This resulted in incremental cost-effectiveness ratios of US$ 75 803, 58 908 and 48 785 per quality-adjusted life year gained for tirzepatide 5, 10 and 15 mg, respectively, versus semaglutide. Tirzepatide remained cost-effective versus semaglutide over a range of sensitivity analyses.

CONCLUSIONS

Long-term projections based on the SURPASS-2 trial results indicate that 5, 10 and 15 mg doses of tirzepatide are likely to be cost-effective versus semaglutide 1.0 mg for the treatment of type 2 diabetes in the United States.

Particle size influences decay rates of environmental DNA in aquatic systems

Environmental DNA (eDNA) analysis is a powerful tool for remote detection of target organisms. However, obtaining quantitative and longitudinal information from eDNA data is challenging, requiring a deep understanding of eDNA ecology. Notably, if the various size components of eDNA decay at different rates, and we can separate them within a sample, their changing proportions could be used to obtain longitudinal dynamics information on targets. To test this possibility, we conducted an aquatic mesocosm experiment in which we separated fish-derived eDNA components using sequential filtration to evaluate the decay rate and changing proportion of various eDNA particle sizes over time. We then fit four alternative mathematical decay models to the data, building towards a predictive framework to interpret eDNA data from various particle sizes. We found that medium-sized particles (1-10 μm) decayed more slowly than other size classes (i.e., <1 and > 10 μm), and thus made up an increasing proportion of eDNA particles over time. We also observed distinct eDNA particle size distribution (PSD) between our Common carp and Rainbow trout samples, suggesting that target-specific assays are required to determine starting eDNA PSDs. Additionally, we found evidence that different sizes of eDNA particles do not decay independently, with particle size conversion replenishing smaller particles over time. Nonetheless, a parsimonious mathematical model where particle sizes decay independently best explained the data. Given these results, we suggest a framework to discern target distance and abundance with eDNA data by applying sequential filtration, which theoretically has both metabarcoding and single-target applications.

Is It Possible to Prepare a "Super" Anion-Exchange Membrane by a Polypyrrole-Based Modification?

In spite of wide variety of commercial ion-exchange membranes, their characteristics, in particular, electrical conductivity and counterion permselectivity, are unsatisfactory for some applications, such as electrolyte solution concentration. This study is aimed at obtaining an anion-exchange membrane (AEM) of high performance in concentrated solutions. An AEM is prepared with a polypyrrole (PPy)-based modification of a heterogeneous AEM with quaternary ammonium functional groups. Concentration dependences of the conductivity, diffusion permeability and Cl− transport number in NaCl solutions are measured and simulated using a new version of the microheterogeneous model. The model describes changes in membrane swelling with increasing concentration and the effect of these changes on the transport characteristics. It is assumed that PPy occupies macro- and mesopores of the host membrane where it replaces non-selective electroneutral solution. Increasing conductivity and selectivity are explained by the presence of positively charged PPy groups. It is found that the conductivity of a freshly prepared membrane reaches 20 mS/cm and the chloride transport number > 0.99 in 4 M NaCl. A choice of input parameters allows quantitative agreement between the experimental and simulation results. However, PPy has shown itself to be an unstable material. This article discusses what parameters a membrane can have to show such exceptional characteristics.

Thermoradiationally Modified Polytetrafluoroethylene as a Basis for Membrane Fabrication: Resistance to Hydrogen Penetration, the Effect of Ion Treatment on the Chemical Structure and Surface Morphology, Evaluation of the Track Radius

A study of the properties of thermoradiationally modified polytetrafluoroethylene and its importance for use as the basis of polymer membranes is presented. The hydrogen permeability of a TRM-PTFE film was studied in comparison with an original PTFE film, and showed a three-fold decrease in hydrogen permeability. Further, TRM-PTFE films were irradiated with accelerated Xe ions with an energy of 1 MeV with fluences from 1 × 10⁸ to 1 × 10¹¹. The changes induced by ion treatment were analyzed by infrared spectroscopy of disturbed total internal reflection (IR-ATR) and by atomic force microscopy (ASM). IR-ATR indicated the absence of destruction in the fluence range from 1 × 10⁸ to 3 × 10¹⁰ cm^-2 (in the area of isolated tracks) and the beginning of overlap of latent tracks on fluences from 3 × 10¹⁰ to 1 × 10¹¹ cm^-2. Topographic images with AFM showed layered lamellar structures that collapsed at a fluence of 10⁸ cm^-2. The destruction was accompanied by a decrease in roughness about seven times the size of the track core observed by the ASM method, fully corresponding to the value obtained on the basis of calculations using modeling in an SRIM program.

Hand Hygiene, Face Mask Use, and Associated Factors during the COVID-19 Pandemic among the Students of Mongar Higher Secondary School, Bhutan: A Cross-Sectional Study

Non-pharmacological measures, such as hand hygiene and face mask use, continue to play an important role in the fight against the COVID-19 pandemic. However, there is a paucity of studies on the adherence to these measures among students in Bhutan. Therefore, we aimed to investigate hand hygiene and face mask-wearing behaviours, as well as their associated factors, among the students of Mongar Higher Secondary School, Bhutan. We conducted a cross-sectional study amongst the students of Mongar Higher Secondary School in Bhutan. The students self-answered the questionnaire on web-based Google Forms. Multivariable logistic regression for good hand washing and face mask use was conducted in order to identify statistically significant socio-demographic covariates. The correlation between hand hygiene and mask use was investigated using Pearson’s correlation coefficient. A total of 533 students completed the survey questionnaire, 52.9% (282) of whom were female students. Facebook (44.3%, 236) and TV (35.5%, 189) were the two most popular sources of information on COVID-19 prevention and control. Good (scores of ≥80% of total scores) hand hygiene and face mask use were reported in 33.6% (179) and 22.1% (118) of students. In multivariable logistic regression, male students presented 79% (adjusted odds ratio [AOR] = 1.79, 95% confidence interval [CI] = 1.23−2.613) odds of engaging in good hand hygiene, compared to female students. Compared to grade 9, those in grade 10 were 60% (AOR = 0.4, 95% CI 0.158−0.998) less likely to engage in good hand hygiene. Boarding students presented 68% (AOR = 1.68, 95% CI 1.001, 2.813) higher odds of wearing a face mask compared to day students. There was a significant positive correlation between good hand hygiene and face mask use (r = 0.3671, p-value < 0.001). Good hand hygiene and face mask use were reported in less than one-third of the study participants. It is recommended to continue educating students on good hand hygiene and face mask use through popular information sources.

The Surprising Dynamics of Electrochemical Coupling at Membrane Sandwiches in Plants

Transport processes across membranes play central roles in any biological system. They are essential for homeostasis, cell nutrition, and signaling. Fluxes across membranes are governed by fundamental thermodynamic rules and are influenced by electrical potentials and concentration gradients. Transmembrane transport processes have been largely studied on single membranes. However, several important cellular or subcellular structures consist of two closely spaced membranes that form a membrane sandwich. Such a dual membrane structure results in remarkable properties for the transport processes that are not present in isolated membranes. At the core of membrane sandwich properties, a small intermembrane volume is responsible for efficient coupling between the transport systems at the two otherwise independent membranes. Here, we present the physicochemical principles of transport coupling at two adjacent membranes and illustrate this concept with three examples. In the supplementary material, we provide animated PowerPoint presentations that visualize the relationships. They could be used for teaching purposes, as has already been completed successfully at the University of Talca.

Advances in Pharmacokinetic Modelling and Computational Approaches for Nanoparticles in Drug Delivery Systems

Generally, therapeutic drugs have issues like poor solubility, rapid removal from the bloodstream, lack of targeting, and an inability to translocate across cell membranes. Some of these barriers can be overcome by using nano drug delivery systems (DDS), which results in more efficient drug delivery to the site of action. Due to their potential application as drug delivery systems, nanoparticles are the main topic of discussion in this article. Experimental and computational investigations have substantially aided in the understanding of how nanocarriers work and how they interact with medications, biomembranes and other biological components. This review explores how computational modelling can aid in the rational design of DDS that has been optimized and improved upon. The most commonly used simulation methods for studying DDS and some of the most important biophysical elements of DDS are also discussed. Then, we conclude by investigating the computational properties of various types of nanocarriers, such as dendrimers and dendrons, polymer-, peptide-, nucleic acid-, lipid-, carbon-based DDS, and gold nanoparticles.

Women's behaviours towards cervical cancer screening in the COVID-19 pandemic: A moderated-mediation-model based on Information-Motivation-Behavioural Skills

AIMS

(1) To establish a predictive model based on the Information-Motivation-Behavioural Skills model, which can analyse the factors affecting the behaviours of women towards cervical cancer screening in the COVID-19 pandemic, and (2) to test the mediating effects of behavioural skills in the model, and (3) to test the moderated mediation effect of age.

DESIGN

A cross-sectional study was conducted among 354 women aged 30-65 between May and August 2021 in Turkey.

METHODS

Data were collected by using an online survey. The direct and indirect effects were tested in the structural equation model and the moderated-mediation effect was tested in the PROCESS macro.

RESULTS

Behavioural skills mediate the effect of motivation on cervical cancer screening behaviours. In addition, age has a moderated mediation effect on this mediation effect.

CONCLUSION

Our study revealed that as women's motivation for cervical cancer screening increased, their behavioural skills also increased. It can be stated that middle-aged and older women with higher behavioural skills are more likely to have screening during the pandemic and to comply with national recommendations.

IMPACT

This study is the first quantitative study to test the impact of the components of the Information-Motivation-Behavioural Skills model on cervical cancer screening during the COVID-19 pandemic. In addition, the results reveal the mediating effect of behavioural skills in the relationship between motivation and cervical cancer scanning behaviour and the moderated mediation effect of age. Our results can provide insight for nurses into how to triage women with delayed cervical cancer screening, how to build screening capacity, and how intervention strategies should be developed to improve compliance with cervical cancer screening and follow-up recommendations in women at risk during and after the pandemic.

Does the model reflect the system? When two-dimensional biomechanics is not 'good enough'

Models are mathematical representations of systems, processes or phenomena. In biomechanics, finite-element modelling (FEM) can be a powerful tool, allowing biologists to test form-function relationships in silico, replacing or extending results of in vivo experimentation. Although modelling simplifications and assumptions are necessary, as a minimum modelling requirement the results of the simplified model must reflect the biomechanics of the modelled system. In cases where the three-dimensional mechanics of a structure are important determinants of its performance, simplified two-dimensional modelling approaches are likely to produce inaccurate results. The vertebrate mandible is one among many three-dimensional anatomical structures routinely modelled using two-dimensional FE analysis. We thus compare the stress regimes of our published three-dimensional model of the chimpanzee mandible with a published two-dimensional model of the chimpanzee mandible and identify several fundamental differences. We then present a series of two-dimensional and three-dimensional FE modelling experiments that demonstrate how three key modelling parameters, (i) dimensionality, (ii) symmetric geometry, and (iii) constraints, affect deformation and strain regimes of the models. Our results confirm that, in the case of the primate mandible (at least), two-dimensional FEM fails to meet this minimum modelling requirement and should not be used to draw functional, ecological or evolutionary conclusions.

Homogenization modelling of antibiotic diffusion and adsorption in viral liquid crystals

Systems of rod-shaped viruses have long been important to the science of living liquid crystals, as their monodispersity and uniform charge make them convenient model systems. Recently, it was shown that, upon the addition of polymers, suspensions of rod-shaped viruses form liquid crystals that are linked with increased tolerance of bacteria against antibiotics. We use homogenization to obtain effective equations describing antibiotic diffusion through these liquid crystals. The analytical results of homogenization are compared with numerical results from an exact microscopic model, showing good agreement and thus allowing us to identify the key parameters behind the process. Our modelling shows that the adsorption plays a key role in increasing antibiotic diffusion time and therefore the presence of nematic rod-shaped viruses may increase antibiotic tolerance through physical mechanisms alone. These results demonstrate the applicability of homogenization as an analytical tool to systems of liquid crystalline viruses, with relatively straightforward extension to more complex problems such as liquid crystalline biofilms, other biological liquid crystals and biological systems with different types of local structural order.

System Identification and Mathematical Modeling of A Piezoelectric Actuator through A Practical Three-Stage Mechanism

Piezoelectric elements (PEMs) are used in a variety of applications. In this paper, we developed a full analytical model and a simple system identification (SI) method of a piezoelectric actuator, which includes piezostack elements and a three-stage amplification mechanism. The model was derived separately for each unit of the system. Next, the units were combined, while taking into account their coupling. The hysteresis phenomenon, which is significant in piezoelectric materials, is described extensively. The theoretical model was verified in a laboratory setup. This setup includes a piezoelectric actuator, measuring devices and an acquisition system. The measured results were compared to the theoretical results. Some of the most well-known forms of system identification are shown briefly, while a new and simple algorithm is described systematically and verified by the model. The main advantage of this work is to provide a solid background and domain knowledge of modelling and system identification methods for further investigations in the field of piezoelectric actuators. Due to their simplicity, both the model and the system identification method can be easily modified in order to be applied to other PEMs or other amplification mechanism methods. The main novelty of this work lies in applying a simple system identification algorithm while using the system-level approach for piezoelectric actuators. Lastly, this review work is concluded and some recommendations for researchers working in this area are presented.

Predictive Model for National Minimal CFR during Spontaneous Initial Outbreak of Emerging Infectious Disease: Lessons from COVID-19 Pandemic in 214 Nations and Regions

The minimal case fatality rate (CFR) is one of the essential fundaments for the establishment of a diverse national response strategy against the COVID-19 epidemic, but cannot be quantitatively predicted. The aim of the present study was to explore the applicable quantitative parameters labeling integrating responding capacity from national daily CFR curves, and whether the minimal CFR during initial emerging epidemic outbreaks can be predicted. We analyzed data from 214 nations and regions during the initial 2020 COVID-19 epidemic and found similar falling zones marked with two turning points within a fitting three-day-moving CFR curve which occurred for many nations and regions. The turning points can be quantified with parameters for the day duration (T1, T2, and ΔT) and for the three-day moving arithmetic average CFRs (CFR1, CFR2, and ΔCFR) under wave theory for 71 nations and regions after screening. Two prediction models of minimal CFR were established with multiple linear regressions (M1) and multi-order curve regressions (M2) after internal and external evaluation. Three kinds of falling zones could be classified in the other 71 nations and regions. Only the minimal CFR showed significant correlations with nine independent national indicators in 65 nations and regions with CFRs less than 7%. Model M1 showed that logarithmic population, births per 1000 people, and household size made significant positive contributions, and logarithmic GDP, percentage of population aged 65+ years, domestic general government health expenditure, physicians per 1000 people, nurses per 1000 people, and body mass index made negative contributions to the minimal CFR against COVID-19 epidemics for most nations and regions. The spontaneous minimal CFR was predicted well with model M1 for 57 nations and regions based on the nine national indicators (R² = 0.5074), or with model M2 for 59 nations and regions based on the nine national indicators (R² = 0.8008) at internal evaluation. The study confirmed that national spontaneous minimal CFR could be predicted with models successfully for most nations and regions against COVID-19 epidemics, which provides a critical method to predict the essential early evidence to evaluate the integrating responding capacity and establish national responding strategies reasonably for other emerging infectious diseases in the future.

Preparing for the upcoming 2022/23 influenza season: A modelling study of the susceptible population in Australia, France, Germany, Italy, Spain and the United Kingdom

We analysed the influenza epidemic that occurred in Australia during the 2022 winter using an age-structured dynamic transmission model, which accounts for past epidemics to estimate the population susceptibility to an influenza infection. We applied the same model to five European countries. Our analysis suggests Europe might experience an early and moderately large influenza epidemic. Also, differences may arise between countries, with Germany and Spain experiencing larger epidemics, than France, Italy and the United Kingdom, especially in children.

Effect of flight connectivity on the introduction and evolution of the COVID-19 outbreak in Canadian provinces and territories

BACKGROUND

The COVID-19 pandemic has challenged health services and governments in Canada and around the world. Our research aims to evaluate the effect of domestic and international air travel patterns on the COVID-19 pandemic in Canadian provinces and territories.

METHODS

Air travel data were obtained through licensed access to the 'BlueDot Intelligence Platform', BlueDot Inc. Daily provincial and territorial COVID-19 cases for Canada and global figures, including mortality, cases recovered and population data were downloaded from public datasets. The effects of domestic and international air travel and passenger volume on the number of local and non-local infected people in each Canadian province and territory were evaluated with a semi-Markov model. Provinces and territories are grouped into large (>100 000 confirmed COVID-19 cases and >1 000 000 inhabitants) and small jurisdictions (≤100 000 confirmed COVID-19 cases and ≤1 000 000 inhabitants).

RESULTS

Our results show a clear decline in passenger volumes from March 2020 due to public health policies, interventions and other measures taken to limit or control the spread of COVID-19. As the measures were eased, some provinces and territories saw small increases in passenger volumes, although travel remained below pre-pandemic levels. During the early phase of disease introduction, the burden of illness is determined by the connectivity of jurisdictions. In provinces with a larger population and greater connectivity, the burden of illness is driven by case importation, although local transmission rapidly replaces imported cases as the most important driver of increasing new infections. In smaller jurisdictions, a steep increase in cases is seen after importation, leading to outbreaks within the community.

CONCLUSIONS

Historical travel volumes, combined with data on an emerging infection, are useful to understand the behaviour of an infectious agent in regions of Canada with different connectivity and population size. Historical travel information is important for public health planning and pandemic resource allocation.

A Novel Concept of Transperineal Focused Ultrasound Transducer for Prostate Cancer Local Deep Hyperthermia Treatments

Design, embodiment, and experimental study of a novel concept of extracorporeal phased array ultrasound transducer for prostate cancer regional deep hyperthermia treatments using a transperineal acoustic window is presented. An optimized design of hyperthermia applicator was derived from a modelling software where acoustic and thermal fields were computed based on anatomical data. Performance tests have been experimentally conducted on gel phantoms and tissues, under 3T MRI guidance using PRFS thermometry. Feedback controlled hyperthermia (ΔT = 5 °C during 20min) was performed on two ex vivo lamb carcasses with prostate mimicking pelvic tissue, to demonstrate capability of spatio-temporal temperature control and to assess potential risks and side effects. Our optimization approach yielded a therapeutic ultrasound transducer consisting of 192 elements of variable shape and surface, pseudo randomly distributed on 6 columns, using a frequency of 700 kHz. Radius of curvature was 140 mm and active water circulation was included for cooling. The measured focusing capabilities covered a volume of 24 × 50 × 60 mm³. Acoustic coupling of excellent quality was achieved. No interference was detected between sonication and MR acquisitions. On ex vivo experiments the target temperature elevation of 5 °C was reached after 5 min and maintained during another 15 min with the predictive temperature controller showing 0.2 °C accuracy. No significant temperature rise was observed on skin and bonny structures. Reported results represent a promising step toward the implementation of transperineal ultrasound hyperthermia in a pilot study of reirradiation in prostate cancer patients.

Simulations of cortical networks using spatially extended conductance-based neuronal models

The Hodgkin-Huxley model of action potential generation and propagation, published in the Journal of Physiology in 1952, initiated the field of biophysically detailed computational modelling in neuroscience, which has expanded to encompass a variety of species and components of the nervous system. Here we review the developments in this area with a focus on efforts in the community towards modelling the mammalian neocortex using spatially extended conductance-based neuronal models. The Hodgkin-Huxley formalism and related foundational contributions, such as Rall's cable theory, remain widely used in these efforts to the current day. We argue that at present the field is undergoing a qualitative change due to new very rich datasets describing the composition, connectivity and functional activity of cortical circuits, which are being integrated systematically into large-scale network models. This trend, combined with the accelerating development of convenient software tools supporting such complex modelling projects, is giving rise to highly detailed models of the cortex that are extensively constrained by the data, enabling computational investigation of a multitude of questions about cortical structure and function.

How to Create Trusted Tribological Characterization Data of Soft Polymers as Input for FEM Simulations?

Soft polymers such as the investigated polyurethane, characterized by low Young's moduli and prone to high shear deflection, are frequently applied in pneumatic cylinders. Their performance and lifetime without external lubrication are highly determined by the friction between seal and shaft and the wear rate. FEM simulation has established itself as a tool in seal design processes but requires input values for friction and wear depending on material, load, and velocity. This paper presents a tribological test configuration for long stroke, reciprocating movement, allowing the generation of data which meet the requirements of input parameters for FEM simulations without the geometrical influences of specific seal profiles. A numerical parameter study, performed with an FEM model, revealed the most eligible sample geometry as a flat, disc-shaped sample of the polymer glued on a stiff sample holder. At the same time, the study illustrates that the sensitivity of the contact pressure distribution to Poisson's ratio and CoF can be minimized by the developed and verified setup. It ensures robust, reliable, and repeatable experimental results with uniform contact pressures and constant contact areas to be used in databases and FEM simulations of seals, enabling upscaling from generically shaped samples to complex seal profiles.

Estimated incidence and transmission intensity of rubella infection in Zambia pre-vaccine era 2005-2016

The rubella disease burden in Zambia may be under-estimated. Using models, we describe the transmission dynamics, determine the incidence estimates and assess the level of underestimation of the real burden of rubella infection in Zambia during the pre-vaccination period 2005-2016. This study used both the deterministic compartmental model and likelihood-based method using a Bayesian framework to describe the epidemiology of rubella. A total of 1313 cases of rubella were confirmed with the highest annual number of 255 new cases recorded in 2008. However, 2014 recorded the highest monthly median positivity rate of 9.0%. The observed median rubella cases were 5.5. There was a seasonal pattern in the occurrence of laboratory-confirmed rubella, with higher test positivity rates of rubella infection usually recorded in the months of September, October and November. The modelled monthly median incidence of rubella infection among the general population was 76 and 20 among pregnant women. The incidence of rubella among the non-pregnant women was 44. The average effective reproductive number (Rt) between 2005 and 2016 was estimated as 1.2 with the peak of infection occurring in 2016. The measles surveillance system underestimates the observed burden of rubella. A mass vaccination campaign conducted between January and July is recommended.

Prevalence of undiagnosed HIV among children in South Africa, Côte d'Ivoire and Zimbabwe: a model-based analysis to inform paediatric HIV screening programmes

INTRODUCTION

To improve the diagnosis and survival of children living with HIV (CLWH), the World Health Organization recommends testing approaches beyond traditional infant HIV testing programmes. Information about undiagnosed HIV prevalence among children of varying ages in the general population is needed to guide innovative national/subnational case-finding and testing approaches.

METHODS

We used the Cost-Effectiveness of Preventing AIDS Complications (CEPAC)-Pediatric model to estimate the prevalence of undiagnosed HIV in 2-, 5- and 10-year-old children in South Africa, Côte d'Ivoire and Zimbabwe in 2018. We simulated cohorts of children born in 2008 (10-year-olds), 2013 (5-year-olds) and 2016 (2-year-olds). Country-/year-specific inputs for pregnant/breastfeeding women included: HIV prevalence (4.2-32.3%), HIV incidence (0.03-0.24%/month), knowledge of HIV status (27-89%) and antiretroviral drug coverage (36-95%). Paediatric inputs included early infant testing coverage (6-95%) and breastfeeding duration (0-20 months). We projected the proportion of surviving CLWH in whom HIV remained undiagnosed and the undiagnosed HIV prevalence among surviving children of each age in the general population. For children born in 2016, we projected survival and diagnosis of all CLWH through 2026. We conducted sensitivity analyses on model parameters.

RESULTS

In 2018, the projected proportion of surviving CLWH whose HIV remained undiagnosed in South Africa/Côte d'Ivoire/Zimbabwe was 44.2%/55.8%/52.9% among 2-year-old CLWH; 29.0%/37.8%/33.2% among 5-year-old CLWH; and 18.3%/25.4%/23.1% among 10-year-old CLWH. Projected general population undiagnosed HIV prevalence in South Africa/Côte d'Ivoire/Zimbabwe was 0.44%/0.32%/0.68% among 2-year-olds; 0.25%/0.17%/0.41% among 5-year-olds; and 0.24%/0.14%/0.38% among 10-year-olds. Among all CLWH born in 2016, 50-54% were projected to die without HIV diagnosis (and subsequently without treatment) within 10 years after birth; 80-85% of these deaths occurred in the first 2 years.

CONCLUSIONS

Projected population-level undiagnosed HIV prevalence is low and sharply decreases after age 2, with more CLWH dying than being diagnosed. Despite low undiagnosed prevalence in the general population of older children, we project that a large proportion of CLWH remain undiagnosed, suggesting that innovative strategies targeting untested children of all ages outside of health facility settings should be prioritized. Programmes could consider routine testing of the general population of children below 2 in all settings and children of all ages in high-prevalence settings.

Neurophysiological consequences of synapse loss in progressive supranuclear palsy

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from clinical to preclinical models of pathology, and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations like electro- and magneto-encephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by [11C]UCB-J positron emission tomography, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology, and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.

Neurophysiological consequences of synapse loss in progressive supranuclear palsy

Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from clinical to preclinical models of pathology, and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations like electro- and magneto-encephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by [11C]UCB-J positron emission tomography, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology, and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.

Plasmonic properties of aluminium nanowires in amorphous silicon

Plasmonic structures can help enhance optical activity in the ultraviolet (UV) region and therefore enhancing photocatalytic reactions and the detection of organic and biological species. Most plasmonic structures are composed of Ag or Au. However, producing structures small enough for optical activity in the UV region has proved difficult. In this study, we demonstrate that aluminium nanowires are an excellent alternative. We investigated the plasmonic properties of the Al nanowires as well as the optoelectronic properties of the surroundinga - Simatrix by combining scanning transmission electron microscopy imaging, electron energy loss spectroscopy and electrodynamic modelling. We have found that the Al nanowires have distinct plasmonic modes in the UV and far UV region, from 0.75 eV to 13 eV. In addition, simulated results found that the size and spacing of the Al nanowires, as well as the embedding material were shown to have a large impact on the type of surface plasmon energies that can be generated in the material. Using electromagnetic modelling, we have identified the modes and illustrated how they could be tuned further.

A Database of Static Thermal Insulation and Evaporative Resistance Values of Dutch Firefighter Clothing Items and Ensembles

The rescue operations' environment can impair firefighters' performance and increase the risk of injuries, e.g., burns and hyperthermia. The bulk and carried weight of heavy protection contributes to lower physical performance, higher metabolic load and internal body heat production. For recommending optimal protection for the tasks and incident scenarios, knowledge of clothing thermal properties is needed. However, detailed data on firefighter protective clothing systems are not available. The aim of the study was to provide scientific background and a dataset that would allow for validation of thermo-physiological models for task-specific conditions of rescue work. Thermal insulation of 37 single items and their variations and 25 realistic protective clothing ensembles were measured on a thermal manikin. Twelve (12) ensembles that evenly covered the whole insulation range were selected for evaporative resistance testing. The equations for summing up individual item's insulation to ensemble insulation and calculating clothing area factor were derived from the dataset. The database of a firefighter clothing system was created. In addition, the local and regional thermal properties of the clothing ensembles were provided for use in future validation of advanced thermo-physiological models for rescue worker exposure predictions and for designing decision aid tools.

Modelling inflammatory biomarker dynamics in a human lipopolysaccharide (LPS) challenge study using delay differential equations

Clinical studies in healthy volunteers challenged with lipopolysaccharide (LPS), a constituent of the cell wall of Gram-negative bacteria, represent a key model to characterize the Toll-like receptor 4 (TLR4)-mediated inflammatory response. Here, we developed a mathematical modelling framework to quantitatively characterize the dynamics and inter-individual variability of multiple inflammatory biomarkers in healthy volunteer LPS challenge studies. Data from previously reported LPS challenge studies were used, which included individual-level time-course data for tumour necrosis factor α (TNF-α), interleukin 6 (IL-6), interleukin 8 (IL-8) and C-reactive protein (CRP). A one-compartment model with first-order elimination was used to capture the LPS kinetics. The relationships between LPS and inflammatory markers was characterized using indirect response (IDR) models. Delay differential equations were applied to quantify the delays in biomarker response profiles. For LPS kinetics, our estimates of clearance and volume of distribution were 35.7 L h^-1 and 6.35 L, respectively. Our model adequately captured the dynamics of multiple inflammatory biomarkers. The time delay for the secretion of TNF-α, IL-6 and IL-8 were estimated to be 0.924, 1.46 and 1.48 h, respectively. A second IDR model was used to describe the induced changes of CRP in relation to IL-6, with a delayed time of 4.2 h. The quantitative models developed in this study can be used to inform design of clinical LPS challenge studies and may help to translate preclinical LPS challenge studies to humans.

Is Pain Contagious? Innocuous Stimulation Can be Transformed Into the Pain Experience by Observational Learning

Studies indicate that classical and operant conditioning have potential to play a role in the formation of the allodynic effect. Only a few studies have examined the role of observational learning in pain induction. Due to some methodological challenges, evidence that the allodynic effect can be learned through observation is limited. In the present study, healthy participants (n = 88) received 2 series of innocuous electrocutaneous stimuli: at the beginning of the study and after observation of a model who rated all the stimuli as painful. Participants and the model rated all the stimuli alternately (real-time group), or the participant first observed the model and then rated the stimuli, while the model stayed in (post-hoc+ group) or left (post-hoc- group) the laboratory. There was no model in the control group. The study demonstrated that allodynia can be induced by observational learning. Furthermore, this effect was shown to be similar, regardless of whether stimuli were received during the observation of the model and rated immediately afterwards, or when the observation and stimuli reception were time-separated. The mere presence of the model during the stimuli reception also did not affect the magnitude of this effect. This research may contribute to our understanding of the mechanisms of chronic pain development and assist in the development of suitable treatment for it. PERSPECTIVE: This article presents study results on the role of observational learning in allodynia induction without tissue injury. The results may contribute to our understanding of the mechanisms of chronic pain development and assist in the development of suitable treatment for it.

Effect of particularisation size on the accuracy and efficiency of a multiscale tumours' growth model

In silico, medicine models are frequently used to represent a phenomenon across multiples space-time scales. Most of these multiscale models require impracticable execution times to be solved, even using high performance computing systems, because typically each representative volume element in the upper scale model is coupled to an instance of the lower scale model; this causes a combinatory explosion of the computational cost, which increases exponentially as the number of scales to be modelled increases. To attenuate this problem, it is a common practice to interpose between the two models a particularisation operator, which maps the upper-scale model results into a smaller number of lower-scale models, and an operator, which maps the fewer results of the lower-scale models on the whole space-time homogenisation domain of upper-scale model. The aim of this study is to explore what is the simplest particularisation / homogenisation scheme that can couple a model aimed to predict the growth of a whole solid tumour (neuroblastoma) to a tissue-scale model of the cell-tissue biology with an acceptable approximation error and a viable computational cost. Using an idealised initial dataset with spatial gradients representative of those of real neuroblastomas, but small enough to be solved without any particularisation, we determined the approximation error and the computational cost of a very simple particularisation strategy based on binning. We found that even such simple algorithm can significantly reduce the computational cost with negligible approximation errors.

Fen ecohydrologic trajectories in response to groundwater drawdown with an edaphic feedback

Fens are high conservation value ecosystems that depend on consistent discharge of groundwater that saturates the near surface for most of the growing season. Reduced groundwater inputs can result in losses of native diversity, decreases in rare-species abundance and increased invasion by non-native species. As such, fen ecosystems are known to be particularly susceptible to changes in groundwater conditions including reduction in water levels due to nearby groundwater pumping. However, research is lacking on whether floristic degradation is influenced by feedbacks between hydrology and soil properties. We present a model of an archetype hillslope fen that couples a hydrological niche model with a variably saturated groundwater flow model to predict changes in vegetation composition in response to different groundwater drawdown scenarios. The model explores a potential edaphic feedback through the use of an observed relationship between fen floristic quality and soil/peat water retention characteristics that is attenuated with separate edaphic and floristic memory terms representing lags in biophysical responses to dewatering. Model parameters were determined based on data collected from six fens in Wisconsin under various states of degradation. We observed different water retention characteristics between sites that were minimally impacted versus degraded that are likely due to peat decomposition, oxidation and compaction at the degraded sites. These characteristics were also correlated with floristic quality. The results reveal a complex response to drawdown where changes in peat hydraulic properties following dewatering lead to even drier conditions and further shifts away from typical fen species.

General clinical and methodological considerations on the extrapolation of pharmacokinetics and optimization of study protocols for small molecules and monoclonal antibodies in children

Pharmacometric modelling plays a key role in both the design and analysis of regulatory trials in paediatric drug development. Studies in adults provide a rich source of data to inform the paediatric investigation plans, including knowledge on drug pharmacokinetics (PK), safety and efficacy. In children, drug disposition differs widely from birth to adolescence but extrapolating adult to paediatric PK, safety and efficacy either with pharmacometric or physiologically based approaches can help design or in some cases reduce the need for clinical studies. Aspects to consider when extrapolating PK include the maturation of drug metabolizing enzyme expression, glomerular filtration, drug excretory systems, and the expression and activity of specific transporters in conjunction with other drug properties such as fraction unbound. Knowledge of these can be used to develop extrapolation tools such as allometric scaling plus maturation functions or physiologically based PK. PK/pharmacodynamic approaches and well-designed clinical trials in children are of key importance in paediatric drug development. In this white paper, state-of-the-art of current methods used for paediatric extrapolation will be discussed. This paper is part of a conect4children implementation of innovative methodologies including pharmacometric and physiologically based PK modelling in clinical trial design/paediatric drug development through dissemination of expertise and expert advice. The suggestions arising from this white paper should define a minimum set of standards in paediatric modelling and contribute to the regulatory science.

Mapping the risk distribution of Borrelia burgdorferi sensu lato in China from 1986 to 2020: a geospatial modelling analysis

Lyme borreliosis, recognized as one of the most important tick-borne diseases worldwide, has been increasing in incidence and spatial extent. Currently, there are few geographic studies about the distribution of Lyme borreliosis risk across China. Here we established a nationwide database that involved Borrelia burgdorferi sensu lato (B. burgdorferi) detected in humans, vectors, and animals in China. The eco-environmental factors that shaped the spatial pattern of B. burgdorferi were identified by using a two-stage boosted regression tree model and the model-predicted risks were mapped. During 1986−2020, a total of 2,584 human confirmed cases were reported in 25 provinces. Borrelia burgdorferi was detected from 35 tick species with the highest positive rates in Ixodes granulatus, Hyalomma asiaticum, Ixodes persulcatus, and Haemaphysalis concinna ranging 20.1%−24.0%. Thirteen factors including woodland, NDVI, rainfed cropland, and livestock density were determined as important drivers for the probability of B. burgdorferi occurrence based on the stage 1 model. The stage 2 model identified ten factors including temperature seasonality, NDVI, and grasslands that were the main determinants used to distinguish areas at high or low-medium risk of B. burgdorferi, interpreted as potential occurrence areas within the area projected by the stage 1 model. The projected high-risk areas were not only concentrated in high latitude areas, but also were distributed in middle and low latitude areas. These high-resolution evidence-based risk maps of B. burgdorferi was first created in China and can help as a guide to future surveillance and control and help inform disease burden and infection risk estimates.

Improving bitter pit prediction by the use of X-ray fluorescence (XRF): A new approach by multivariate classification

Bitter pit (BP) is one of the most relevant post-harvest disorders for apple industry worldwide, which is often related to calcium (Ca) deficiency at the calyx end of the fruit. Its occurrence takes place along with an imbalance with other minerals, such as potassium (K). Although the K/Ca ratio is considered a valuable indicator of BP, a high variability in the levels of these elements occurs within the fruit, between fruits of the same plant, and between plants and orchards. Prediction systems based on the content of elements in fruit have a high variability because they are determined in samples composed of various fruits. With X-ray fluorescence (XRF) spectrometry, it is possible to characterize non-destructively the signal intensity for several mineral elements at a given position in individual fruit and thus, the complete signal of the mineral composition can be used to perform a predictive model to determine the incidence of bitter pit. Therefore, it was hypothesized that using a multivariate modeling approach, other elements beyond the K and Ca could be found that could improve the current clutter prediction capability. Two studies were carried out: on the first one an experiment was conducted to determine the K/Ca and the whole spectrum using XRF of a balanced sample of affected and non-affected 'Granny Smith' apples. On the second study apples of three cultivars ('Granny Smith', 'Brookfield' and 'Fuji'), were harvested from two commercial orchards to evaluate the use of XRF to predict BP. With data from the first study a multivariate classification system was trained (balanced database of healthy and BP fruit, consisting in 176 from each group) and then the model was applied on the second study to fruit from two orchards with a history of BP. Results show that when dimensionality reduction was performed on the XRF spectra (1.5 - 8 KeV) of 'Granny Smith' apples, comparing fruit with and without BP, along with K and Ca, four other elements (i.e., Cl, Si, P, and S) were found to be deterministic. However, the PCA revealed that the classification between samples (BP vs. non-BP fruit) was not possible by univariate analysis (individual elements or the K/Ca ratio).Therefore, a multivariate classification approach was applied, and the classification measures (sensitivity, specificity, and balanced precision) of the PLS-DA models for all cultivars evaluated ('Granny Smith', 'Fuji' and 'Brookfield') on the full training samples and with both validation procedures (Venetian and Monte Carlo), ranged from 0.76 to 0.92. The results of this work indicate that using this technology at the individual fruit level is essential to understand the factors that determine this disorder and can improve BP prediction of intact fruit.

Cost-effectiveness of hepatitis C virus test-and-treat and risk reduction strategies among men who have sex with men living with HIV in France

INTRODUCTION

Studies suggest that hepatitis C virus (HCV) micro-elimination is feasible among men who have sex with men (MSM) living with human immunodeficiency virus (HIV), through treatment-as-prevention and interventions aimed at reducing risk behaviours. However, their economic impact is poorly understood. The aim of this study was to assess the cost-effectiveness of HCV screening and risk reduction strategies in France.

METHODS

A compartmental deterministic mathematical model was developed to describe HCV disease transmission and progression among MSM living with HIV in France. We evaluated different combinations of HCV screening frequency (every 12, 6 or 3 months) and risk reduction strategies (targeting only high-risk or all MSM) from 2021 onwards. The model simulated the number of HCV infections, life-expectancy (LYs), quality-adjusted life-expectancy (QALYs), lifetime costs and incremental cost-effectiveness ratio (ICER) over a lifetime horizon (leading to an end of the simulation in 2065).

RESULTS

All strategies increased QALYs, compared with current practices, that is yearly HCV screening, with no risk reduction. A behavioural intervention resulting in a 20% risk reduction in the high-risk group, together with yearly screening, was the least expensive strategy, and, therefore, cost-saving compared to current practices. The ICER per QALY gained for the strategy combining risk reduction for the high-risk group with 6-month HCV screening, compared to risk reduction with yearly screening, was €61,389. It also prevented 398 new HCV infections between 2021 and 2065, with a cost per infection averted of €37,790. All other strategies were dominated (more expensive and less effective than some other available alternative) or not cost-effective (ICER per QALY gained > €100,000).

CONCLUSIONS

In the French context, current HCV screening practices without risk reduction among MSM living with HIV cannot be justified on economic grounds. Risk reduction interventions targeted to high-risk individuals-alongside screening either once or twice a year-could be cost-effective depending on the policymaker's willingness-to-pay.

Risk factors associated with readmission within 30 days following stoma surgery: Development of a 'traffic light' prediction model

AIM

Patients undergoing stoma surgery have a higher risk for early readmission. Some patients may benefit from closer postdischarge surveillance to provide early detection of complications and timely intervention. However, there is a paucity of validated tools to identify those at higher risk of readmission. Here, we aim to determine the independent risk factors associated with readmission within 30 days of discharge following stoma surgery, attempt to validate previous predictive models and develop a novel prediction tool.

METHOD

A retrospective review of 423 patients who underwent ileostomy or colostomy stoma formation at a UK tertiary colorectal centre between 2019 and 2021. Univariate, multivariate and logistic regression analyses were used to analyse a large number of demographics and risk factors and the association with readmission.

RESULTS

This study cohort included 220 ileostomy and 203 colostomy patients. Of these, 87 (20.6%) were readmitted within 30 days of discharge following index surgery. A large number of demographics were evaluated for association with readmission. Readmission was associated with chronic heart failure (p < 0.05), postoperative stoma-specific complications (bleeding, p = 0.02; high-output stoma, p = 0.01) and those with a loop ileostomy (34.0% vs. 18.6%; p = 0.01). A previous predictive model was ineffective in this cohort, therefore a simplified 'traffic light' risk scoring system was developed and found to have improved discrimination.

CONCLUSION

Readmission following stoma formation is associated with key variables that could provide the means to triage, risk score and potentially predict readmissions. We found that a novel and simplified scoring system may provide improved prediction.

Use of Neural Networks for Lifetime Analysis of Teeming Ladles

When describing the behaviour and modelling of real systems, which are characterized by considerable complexity, great difficulty, and often the impossibility of their formal mathematical description, and whose operational monitoring and measurement are difficult, conventional analytical-statistical models run into the limits of their use. The application of these models leads to necessary simplifications, which cause insufficient adequacy of the resulting mathematical description. In such cases, it is appropriate for modelling to use the methods brought by a new scientific discipline-artificial intelligence. Artificial intelligence provides very promising tools for describing and controlling complex systems. The method of neural networks was chosen for the analysis of the lifetime of the teeming ladle. Artificial neural networks are mathematical models that approximate non-linear functions of an arbitrary waveform. The advantage of neural networks is their ability to generalize the dependencies between individual quantities by learning the presented patterns. This property of a neural network is referred to as generalization. Their use is suitable for processing complex problems where the dependencies between individual quantities are not exactly known.

Mathematical model and stability analysis on the transmission dynamics of skin sores

In this study, a non-linear deterministic model for the transmission dynamics of skin sores (impetigo) disease is developed and analysed by the help of stability of differential equations. Some basic properties of the model including existence and positivity as well as boundedness of the solutions of the model are investigated. The disease-free and endemic equilibrium were investigated, as well as the basic reproduction number, R₀, also calculated using the next-generation matrix approach. When R₀ < 1, the model's stability analysis reveals that the system is asymptotically stable at disease-free critical point globally as well as locally. If R₀ > 1, the system is asymptotically stable at disease-endemic equilibrium both locally and globally. The long-term behaviour of the skin sores model's steady-state solution in a population is investigated using numerical simulations of the model.

Hybrid Polymer Composites Based on Polystyrene (PS) Used in the Melted and Extruded Manufacturing Technology

As part of the work, innovative hybrid polymer composites dedicated to rapid prototyping, especially for 3D printing with the melted and extruded manufacturing (MEM) technique, were developed. For this purpose, the influence of modified fillers, such as alumina-modified silica, bentonite modified with quaternary ammonium salt, and lignin/silicon dioxide hybrid filler, on the functional properties of polystyrene-based composites was investigated. The introduced additives were selected to improve the processing properties of polystyrene (PS), in particular its thermal stability, while maintaining good mechanical properties. In the first part of the work, using the proprietary technological line, filaments from unfilled PS and its composites were obtained, which contain modified fillers in the amount of 1.5% to 3.0% by weight. Samples for testing functional properties were obtained by 3D printing in MEM technology and injection technique. The rheological properties-mass melt flow rate (MFR), viscosity, and mechanical properties-are presented in the further part of the work. The size and the respective dispersion in the polystyrene polymer matrix of the fillers used were determined by scanning electron microscopy with energy dispersion spectroscopy (SEM/EDS). The correct dispersion of additives in PS was also confirmed by wide-angle X-ray analysis (WAXS). A significant improvement in the thermal stability of the obtained composites after the introduction of fillers into the polymer matrix was confirmed on the basis of thermogravimetric analysis (TGA). The remaining tests of physicochemical properties, differential scanning calorimetry (DSC), and infrared spectroscopy with Fourier transform (FT-IR) allowed us to state no significant changes in relation to polystyrene. The obtained test results allowed us to conclude that the amount and type of fillers used in the PS polymer matrix significantly affect the performance properties of the tested hybrid composites. The composites obtained as part of the work can be successfully used in rapid prototyping technologies, especially for the production of details originally designed from PS, which are required to have higher thermal stability than is guaranteed only by the polymer matrix.

Elastic Moduli of Non-Chiral Singe-Walled Silicon Carbide Nanotubes: Numerical Simulation Study

Silicon carbide nanotubes (SiCNTs) have generated significant research interest due to their potential use in the fabrication of electronic and optoelectronic nanodevices and biosensors. The exceptional chemical, electrical and thermal properties of SiCNTs are beneficial for their application in high-temperature and harsh-environments. In view of the limited thermal stability of carbon nanotubes, they can be replaced by silicon carbide nanotubes in reinforced composites, developed for operations at high temperatures. However, fundamentally theoretical studies of the mechanical properties of the silicon carbide nanotubes are at an early stage and their results are still insufficient for designing and exploiting appropriate nanodevices based on SiCNTs and reinforced composites. In this context, the present study deals with the determination of Young's and shear moduli of non-chiral single-walled silicon carbide nanotubes, using a three-dimensional finite element model.

Impact and cost-effectiveness of non-governmental organizations on the HIV epidemic in Ukraine among MSM

OBJECTIVE

Non-governmental organizations (NGOs) in Ukraine have provided HIV testing, treatment, and condom distribution for MSM. HIV prevalence among MSM in Ukraine is 5.6%. We estimated the impact and cost-effectiveness of MSM-targeted NGO activities in Ukraine.

DESIGN

A mathematical model of HIV transmission among MSM was calibrated to data from Ukraine (2011-2018).

METHODS

The model, designed before the 2022 Russian invasion of Ukraine, evaluated the impact of 2018 status quo coverage levels of 28% of MSM being NGO clients over 2016-2020 and 2021-2030 compared with no NGO activities over these time periods. Impact was measured in HIV incidence and infections averted. We compared the costs and disability adjusted life years (DALYs) for the status quo and a counterfactual scenario (no NGOs 2016-2020, but with NGOs thereafter) until 2030 to estimate the mean incremental cost-effectiveness ratio (cost per DALY averted).

RESULTS

Without NGO activity over 2016-2020, the HIV incidence in 2021 would have been 44% (95% credibility interval: 36-59%) higher than with status quo levels of NGO activity, with 25% (21-30%) more incident infections occurring over 2016-2020. Continuing with status quo NGO coverage levels will decrease HIV incidence by 41% over 2021-2030, whereas it will increase by 79% (60-120%) with no NGOs over this period and 37% (30-51%) more HIV infections will occur. Compared with if NGO activities had ceased over 2016-2020 (but continued thereafter), the status quo scenario averts 14 918 DALYs over 2016-2030 with a mean incremental cost-effectiveness ratio of US$600.15 per DALY averted.

CONCLUSION

MSM-targeted NGOs in Ukraine have prevented considerable HIV infections and are highly cost-effective compared with a willingness-to-pay threshold of 50% of Ukraine's 2018 GDP (US$1548).

Prediction Models for the Content of Calcium, Boron and Potassium in the Fruit of 'Huangguan' Pears Established by Using Near-Infrared Spectroscopy

It has been proved that the imbalance of the proportion of elements of 'Huangguan' pears in the pulp and peel, especially calcium, boron and potassium, may be important factors that can seriously affect the pears' appearance quality and economic benefits. The objective of this study was to predict the content of calcium, boron and potassium in the pulp and peel of 'Huangguan' pears nondestructively and conveniently by using near-infrared spectroscopy (900-1700 nm) technology. Firstly, 12 algorithms were used to preprocess the original spectral data. Then, based on the original and preprocessed spectral data, full-band prediction models were established by using Partial Least Squares Regression and Gradient Boosting Regression Tree. Finally, the characteristic wavelengths were extracted by Genetic Algorithms to establish the characteristic wavelength prediction models. According to the prediction results, the value of the determination coefficient of the prediction sets of the best prediction models for the three elements all reached ideal levels, and the values of their Relative analysis error also showed high levels. Therefore, the micro near-infrared spectrometer based on machine learning can predict the content of calcium, boron and potassium in the pulp and peel of 'Huangguan' pears accurately and quickly. The results also provide an important scientific theoretical basis for further research on the degradation of the quality of 'Huangguan' pears caused by a lack of nutrients.

Effectiveness of subnational implementation of minimum unit price for alcohol: policy appraisal modelling for local authorities in England

AIMS

Evidence exists on the potential impact of national level minimum unit price (MUP) policies for alcohol. This study investigated the potential effectiveness of implementing MUP at regional and local levels compared with national implementation.

DESIGN

Evidence synthesis and computer modelling using the Sheffield Alcohol Policy Model (Local Authority version 4.0; SAPMLA).

SETTING

Results are produced for 23 Upper Tier Local Authorities (UTLAs) in North West England, 12 UTLAs in North East England, 15 UTLAs in Yorkshire and Humber, the nine English Government Office regions and England as a whole.

CASES

Health Survey for England (HSE) data 2011-13 (n = 24 685).

MEASUREMENTS

Alcohol consumption, consumer spending, retailers' revenues, hospitalizations, National Health Service costs, crimes and alcohol-attributable deaths and health inequalities.

FINDINGS

Implementing a local £0.50 MUP for alcohol in northern English regions is estimated to result in larger percentage reductions in harms than the national average. The reductions for England, North West, North East and Yorkshire and Humber regions, respectively, in annual alcohol-attributable deaths are 1024 (-10.4%), 205 (-11.4%), 121 (-17.4%) and 159 (-16.9%); for hospitalizations are 29 943 (-4.6%), 5956 (-5.5%), 3255 (-7.9%) and 4610 (-6.9%); and for crimes are 54 229 (-2.4%), 8528 (-2.5%), 4380 (-3.5%) and 8220 (-3.2%). Results vary among local authorities; for example, annual alcohol-attributable deaths estimated to change by between -8.0 and -24.8% throughout the 50 UTLAs examined.

CONCLUSIONS

A minimum unit price local policy for alcohol is likely to be more effective in those regions, such as the three northern regions of England, which have higher levels of alcohol consumption and higher rates of alcohol harm than for the national average. In such regions, the minimum unit price policy would achieve larger reductions in alcohol consumption, alcohol-attributable mortality, hospitalization rates, NHS costs, crime rates and health inequalities.

Recovery of carbon benefits by overharvested baleen whale populations is threatened by climate change

Despite the importance of marine megafauna on ecosystem functioning, their contribution to the oceanic carbon cycle is still poorly known. Here, we explored the role of baleen whales in the biological carbon pump across the southern hemisphere based on the historical and forecasted abundance of five baleen whale species. We modelled whale-mediated carbon sequestration through the sinking of their carcasses after natural death. We provide the first temporal dynamics of this carbon pump from 1890 to 2100, considering both the effects of exploitation and climate change on whale populations. We reveal that at their pre-exploitation abundance, the five species of southern whales could sequester 4.0 × 105 tonnes of carbon per year (tC yr-1). This estimate dropped to 0.6 × 105 tC yr-1 by 1972 following commercial whaling. However, with the projected restoration of whale populations under a RCP8.5 climate scenario, the sequestration would reach 1.7 × 105 tC yr-1 by 2100, while without climate change, recovered whale populations could sequester nearly twice as much (3.2 × 105 tC yr-1) by 2100. This highlights the persistence of whaling damages on whale populations and associated services as well as the predicted harmful impacts of climate change on whale ecosystem services.

Lung Cancer Screening in Greece: A Modelling Study to Estimate the Impact on Lung Cancer Life Years

(1) Background: Lung cancer causes a substantial epidemiological burden in Greece. Yet, no formal national lung cancer screening program has been introduced to date. This study modeled the impact on lung cancer life years (LCLY) of a hypothetical scenario of comprehensive screening for lung cancer with low-dose computed tomography (LDCT) of the high-risk population in Greece, as defined by the US Preventive Services Taskforce, would be screened and linked to care (SLTC) for lung cancer versus the current scenario of background (opportunistic) screening only; (2) Methods: A stochastic model was built to monitor a hypothetical cohort of 100,000 high-risk men and women as they transitioned between health states (without cancer, with cancer, alive, dead) over 5 years. Transition probabilities were based on clinical expert opinion. Cancer cases, cancer-related deaths, and LCLYs lost were modeled in current and hypothetical scenarios. The difference in outcomes between the two scenarios was calculated. 150 iterations of simulation scenarios were conducted for 100,000 persons; (3) Results: Increasing SLTC to a hypothetical 100% of eligible high-risk people in Greece leads to a statistically significant reduction in deaths and in total years lost due to lung cancer, when compared with the current SLTC paradigm. Over 5 years, the model predicted a difference of 339 deaths and 944 lost years between the hypothetical and current scenario. More specifically, the hypothetical scenario led to fewer deaths (−24.56%, p < 0.001) and fewer life years lost (−31.01%, p < 0.001). It also led to a shift to lower-stage cancers at the time of diagnosis; (4) Conclusions: Our study suggests that applying a 100% screening strategy amongst high-risk adults aged 50−80, would result in additional averted deaths and LCLYs gained over 5 years in Greece.

Biomechanical Modelling for Tooth Survival Studies: Mechanical Properties, Loads and Boundary Conditions-A Narrative Review

Recent biomechanical studies have focused on studying the response of teeth before and after different treatments under functional and parafunctional loads. These studies often involve experimental and/or finite element analysis (FEA). Current loading and boundary conditions may not entirely represent the real condition of the tooth in clinical situations. The importance of homogenizing both sample characterization and boundary conditions definition for future dental biomechanical studies is highlighted. The mechanical properties of dental structural tissues are presented, along with the effect of functional and parafunctional loads and other environmental and biological parameters that may influence tooth survival. A range of values for Young's modulus, Poisson ratio, compressive strength, threshold stress intensity factor and fracture toughness are provided for enamel and dentin; as well as Young's modulus and Poisson ratio for the PDL, trabecular and cortical bone. Angles, loading magnitude and frequency are provided for functional and parafunctional loads. The environmental and physiological conditions (age, gender, tooth, humidity, etc.), that may influence tooth survival are also discussed. Oversimplifications of biomechanical models could end up in results that divert from the natural behavior of teeth. Experimental validation models with close-to-reality boundary conditions should be developed to compare the validity of simplified models.

COVID-19 detection using a model of photoplethysmography (PPG) signals

Objective:Coronavirus disease 2019 (COVID-19) targets several tissues of the human body; among these, a serious impact has been observed in the microvascular system. The aim of this study was to verify the presence of photoplethysmographic (PPG) signal modifications in patients affected by COVID-19 at different levels of severity.

Approach: The photoplethysmographic signal was evaluated in 93 patients with COVID-19 of different severity (46: grade 1; 47: grade 2) and in 50 healthy control subjects. A pre-processing step removes the long-term trend and segments of each pulsation in the input signal. Each pulse is approximated with a model generated from a multi-exponential curve, and a Least Squares fitting algorithm determines the optimal model parameters. Using the parameters of the mathematical model, three different classifiers (Bayesian, SVM and KNN) were trained and tested to discriminate among healthy controls and patients with COVID, stratified according to the severity of the disease. Results are validated with the leave-one-subject-out validation method.

Main results: Results indicate that the fitting procedure obtains a very high determination coefficient (above 99% in both controls and pathological subjects). The proposed Bayesian classifier obtains promising results, given the size of the dataset, and variable depending on the classification strategy. The optimal classification strategy corresponds to 79% of accuracy, with 90% of specificity and 67% of sensibility.

Significance:The proposed approach opens the possibility of introducing a low cost and non-invasive screening procedure for the fast detection of COVID-19 disease, as well as a promising monitoring tool for hospitalized patients, with the purpose of stratifying the severity of the disease.

Simulation of Varroa mite control in honey bee colonies without synthetic acaricides: Demonstration of Good Beekeeping Practice for Germany in the BEEHAVE model

The BEEHAVE model simulates the population dynamics and foraging activity of a single honey bee colony (Apis mellifera) in great detail. Although it still makes numerous simplifying assumptions, it appears to capture a wide range of empirical observations. It could, therefore, in principle, also be used as a tool in beekeeper education, as it allows the implementation and comparison of different management options. Here, we focus on treatments aimed at controlling the mite Varroa destructor. However, since BEEHAVE was developed in the UK, mite treatment includes the use of a synthetic acaricide, which is not part of Good Beekeeping Practice in Germany. A practice that consists of drone brood removal from April to June, treatment with formic acid in August/September, and treatment with oxalic acid in November/December. We implemented these measures, focusing on the timing, frequency, and spacing between drone brood removals. The effect of drone brood removal and acid treatment, individually or in combination, on a mite-infested colony was examined. We quantify the efficacy of Varroa mite control as the reduction of mites in treated bee colonies compared to untreated bee colonies. We found that drone brood removal was very effective, reducing mites by 90% at the end of the first simulation year after the introduction of mites. This value was significantly higher than the 50-67% reduction expected by bee experts and confirmed by empirical studies. However, literature reports varying percent reductions in mite numbers from 10 to 85% after drone brood removal. The discrepancy between model results, empirical data, and expert estimates indicate that these three sources should be reviewed and refined, as all are based on simplifying assumptions. These results and the adaptation of BEEHAVE to the Good Beekeeping Practice are a decisive step forward for the future use of BEEHAVE in beekeeper education in Germany and anywhere where organic acids and drone brood removal are utilized.

The Relevance of Goodness-of-fit, Robustness and Prediction Validation Categories of OECD-QSAR Principles with Respect to Sample Size and Model Type

We investigated the relevance of the validation principles on the Quantitative Structure Activity Relationship models issued by Organization for Economic and Co-operation and Development. We checked the goodness-of-fit, robustness and predictivity categories in linear and nonlinear models using benchmark datasets. Most of our conclusions are drawn using the sample size dependence of the different validation parameters. We found that the goodness-of-fit parameters misleadingly overestimate the models on small samples. In the case of neural network and support vector models, the feasibility of the goodness-of-fit parameters often might be questioned. We propose to use the simplest y-scrambling method to estimate chance correlation. We found that the leave-one-out and leave-many-out cross-validation parameters can be rescaled to each other in all models and the computationally feasible method should be chosen depending on the model type. We assessed the interdependence of the validation parameters by calculating their rank correlations. Goodness of fit and robustness correlate quite well over a sample size for linear models and one of the approaches might be redundant. In the rank correlation between internal and external validation parameters, we found that the assignment of good and bad modellable data to the training or the test causes negative correlations.

MODELLING OF PATHOGENS IMPACT ON THE HUMAN DISEASE TRANSMISSION WITH OPTIMAL CONTROL STRATEGIES

This study concentrates on a nonlinear deterministic mathematical model for the impact of pathogens on human disease transmission with optimal control strategies. Both pathogen-free and coexistence equilibria are computed. The basic reproduction number R₀, which plays a vital role in mathematical epidemiology, was derived. The qualitative analysis of the model revealed the scenario for both pathogen-free and coexistence equilibria together with R₀. The local stability of the equilibria is established via the Jacobian matrix and Routh-Hurwitz criteria, while the global stability of the equilibria is proven by using an appropriate Lyapunov function. Also, the normalized sensitivity analysis has been performed to observe the impact of different parameters on R₀. The proposed model is extended into optimal control problem by incorporating three control variables, namely, preventive measure variable based on separation of susceptible from contacting the pathogens, integrated vector management based on chemical, biological control, ... etc. to kill pathogens and their carriers, and supporting infective medication variable based on the care of the infected individual in quarantine center. Optimal disease control analysis is examined using Pontryagin minimum principle. Numerical simulations are performed depending on analytical results and discussed quantitatively.

Variance-based sensitivity analysis of tuberculosis transmission models

Mathematical models are widely used to provide evidence to inform policies for tuberculosis (TB) control. These models contain many sources of input uncertainty including the choice of model structure, parameter values and input data. Quantifying the role of these different sources of input uncertainty on the model outputs is important for understanding model dynamics and improving evidence for policy making. In this paper, we applied the Sobol sensitivity analysis method to a TB transmission model used to simulate the effects of a hypothetical population-wide screening strategy. We demonstrated how the method can be used to quantify the importance of both model parameters and model structure and how the analysis can be conducted on groups of inputs. Uncertainty in the model outputs was dominated by uncertainty in the intervention parameters. The important inputs were context dependent, depending on the setting, time horizon and outcome measure considered. In particular, the choice of model structure had an increasing effect on output uncertainty in high TB incidence settings. Grouping inputs identified the same influential inputs. Wider use of the Sobol method could inform ongoing development of infectious disease models and improve the use of modelling evidence in decision making.

A model study of convergent dynamics in the marginal ice zone

With the increasing resolution of operational forecasting models, the marginal ice zone (MIZ), the area where waves and sea ice interact, can now be better represented. However, the proper mechanics of wave propagation and attenuation in ice, and especially their influence on sea ice dynamics, still remain poorly understood and constrained in models. Observations have shown exponential wave energy decrease with distance in sea ice, particularly strong at higher frequencies. Some of this energy is transferred to the ice, breaking it into smaller floes and weakening it, as well as exerting a stress on the ice similar to winds and currents. In this article, we present a one-dimensional, fully integrated wave and ice model that has been developed to test different parameterizations of wave-ice interactions. The response of the ice cover to the wind and wave radiative stresses is investigated for a variety of wind, wave and ice conditions at different scales. Results of sensitivity analyses reveal the complex interplay between wave attenuation and rheological parameters and suggest that the compressive strength of the MIZ may be better represented by a Mohr-Coulomb parameterization with a nonlinear dependence on thickness. This article is part of the theme issue 'Theory, modelling and observations of marginal ice zone dynamics: multidisciplinary perspectives and outlooks'.