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Although Poisson processes are widely used in various applications for modeling of recurrent point events, there exist obvious limitations. Several specific mixed Poisson processes (which are formally not Poisson processes any more) that were recently introduced in the literature overcome some of these limitations. In this paper, we define a general mixed Poisson process with the phase-type (PH) distribution as the mixing one. As the PH distribution is dense in the set of lifetime distributions, the new process can be used to approximate any mixed Poisson process. We study some basic stochastic properties of the new process and discuss relevant applications by considering the extreme shock model, the stochastic failure rate model and the δ-shock model.

Schurz (2019, ch. 4) argues that probabilistic accounts of induction fail. In particular, he criticises probabilistic accounts of induction that appeal to direct inference principles, including subjective Bayesian approaches (e.g., Howson 2000) and objective Bayesian approaches (see, e.g., Williamson 2017). In this paper, I argue that Schurz’ preferred direct inference principle, namely Reichenbach’s Principle of the Narrowest Reference Class, faces formidable problems in a standard probabilistic setting. Furthermore, the main alternative direct inference principle, Lewis’ Principal Principle, is also hard to reconcile with standard probabilism. So, I argue, standard probabilistic approaches cannot appeal to direct inference to explicate the logic of induction. However, I go on to defend a non-standard objective Bayesian account of induction: I argue that this approach can both accommodate direct inference and provide a viable account of the logic of induction. I then defend this account against Schurz’ criticisms.

open access article Research out put of the COLOSS monitoring Project. COLOSS is a global network of honey bee researchers This article presents managed honey bee colony loss rates over winter 2019/20 resulting from using the standardised COLOSS questionnaire in 37 countries. Six countries were from outside Europe, including, for the first time in this series of articles, New Zealand. The 30,491 beekeepers outside New Zealand reported 4.5% of colonies with unsolvable queen problems, 11.1% of colonies dead after winter and 2.6% lost through natural disaster. This gave an overall colony winter loss rate of 18.1%, higher than in the previous year. The winter loss rates varied greatly between countries, from 7.4% to 36.5%. 3216 beekeepers from New Zealand managing 297,345 colonies reported 10.5% losses for their 2019 winter (six months earlier than for other, Northern Hemisphere, countries). We modelled the risk of loss as a dead/empty colony or from unresolvable queen problems, for all countries except New Zealand. Overall, larger beekeeping operations with more than 50 colonies experienced significantly lower losses (p

Background Antimicrobial resistance has been recognised as a global threat with carbapenemase- producing-Enterobacteriaceae (CPE) as a prime example. CPE has similarities to COVID-19 where asymptomatic patients may be colonised representing a source for onward transmission. There are limited treatment options for CPE infection leading to poor outcomes and increased costs. Admission screening can prevent cross-transmission by pre-emptively isolating colonised patients. Objective We assess the relative cost-effectiveness of screening programmes compared with no- screening. Methods A microsimulation parameterised with NHS Scotland date was used to model scenarios of the prevalence of CPE colonised patients on admission. Screening strategies were (a) two-step screening involving a clinical risk assessment (CRA) checklist followed by microbiological testing of high-risk patients; and (b) universal screening. Strategies were considered with either culture or polymerase chain reaction (PCR) tests. All costs were reported in 2019 UK pounds with a healthcare system perspective. Results In the low prevalence scenario, no screening had the highest probability of cost-effectiveness. Among screening strategies, the two CRA screening options were the most likely to be cost-effective. Screening was more likely to be cost-effective than no screening in the prevalence of 1 CPE colonised in 500 admitted patients or more. There was substantial uncertainty with the probabilities rarely exceeding 40% and similar results between strategies. Screening reduced non-isolated bed-days and CPE colonisation. The cost of screening was low in relation to total costs. Conclusion The specificity of the CRA checklist was the parameter with the highest impact on the cost-effectiveness. Further primary data collection is needed to build models with less uncertainty in the parameters.

Whether phytoplankton growth is solely constrained by temperature (hotter is better) or compensated by thermal adaptation is still under debate. We measured the temperature sensitivity of natural phytoplankton communities at both short‐term and seasonal timescales using temperature manipulation experiments. The activation energy across communities (mean ± SE: E i = 0.51 ± 0.12 eV, Q10 = 1.98) is significantly lower than that within communities (E a = 0.80 ± 0.10 eV, Q10 = 2.80). Moreover, using a larger dataset of phytoplankton growth rates measured in (sub)tropical waters, we estimated the across‐community activation energy as 0.33 ± 0.06 eV (Q10 = 1.56), which is also lower than E a . Our study is the first to suggest the “hotter is partially better” for natural phytoplankton communities, indicating that the phytoplankton communities can show some thermal adaptation capability. Our results highlight the importance of incorporating the differential temperature sensitivities at different timescales into the biogeochemical models to better evaluate how marine ecosystems will respond to climate changes.

An approximate 1:1 sex ratio of American lobsters can be skewed due to environmental factors or fisheries management. Substantial skewness can impact mating behaviour and lower reproduction which could have far-reaching ecological and economic consequences. The aim was to investigate the sex ratio patterns of lobsters in two lobster fishing areas (LFAs) in southwestern Nova Scotia, Canada and identify factors associated with skewed sex ratios. This study analyzed biological data from more than 270,000 lobsters sampled over ten years (2010–2019) by the Fishermen and Scientists Research Society. A mixed effect logistic regression model evaluated the effect of spatial, temporal and environmental factors as well as size on the sex ratio of lobsters. There were significant temporal patterns in sex ratios that differed by LFA. After the effects of sampling month, year and LFA were accounted for, lower bottom temperature and deeper water depth were associated with a higher prevalence of females, especially in larger lobsters. We present the first long term analyses of sex ratio patterns in H. americanus in Atlantic Canada’s most commercially important region for this species and provide evidence that these patterns are influenced by environmental factors and fisheries. In view of future climate change scenarios, monitoring the population dynamics of this iconic fishery species is crucial to ensure sustainable fisheries and healthy lobster stocks.

Estimating the spatially varying microstructures of heterogeneous and locally anisotropic media non-destructively is necessary for the accurate detection of flaws and reliable monitoring of manufacturing processes. Conventional algorithms used for solving this inverse problem come with significant computational cost, particularly in the case of high-dimensional, nonlinear tomographic problems, and are thus not suitable for near-real-time applications. In this paper, for the first time, we propose a framework which uses deep neural networks (DNNs) with full aperture, pitch-catch and pulse-echo transducer configurations, to reconstruct material maps of crystallographic orientation. We also present the first application of generative adversarial networks (GANs) to achieve super-resolution of ultrasonic tomographic images, providing a factor-four increase in image resolution and up to a 50% increase in structural similarity. The importance of including appropriate prior knowledge in the GAN training data set to increase inversion accuracy is demonstrated: known information about the material’s structure should be represented in the training data. We show that after a computationally expensive training process, the DNNs and GANs can be used in less than 1 second (0.9 s on a standard desktop computer) to provide a high-resolution map of the material’s grain orientations, addressing the challenge of significant computational cost faced by conventional tomography algorithms.

Funding: BREATHE - The Health Data Research Hub for Respiratory Health, which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK (MC_PC_19004); CSO Rapid Research in Covid-19 Programme (COV/SAN/20/06); HDR UK Measuring and Understanding Multi-morbidity using Routine Data in the UK (MurMuRUK) (HDR-9006-9006; CFC0110); Medical Research Council (MR/R008345/1). Objectives We investigated the association between multimorbidity among patients hospitalised with COVID-19 and their subsequent risk of mortality. We also explored the interaction between the presence of multimorbidity and the requirement for an individual to shield due to the presence of specific conditions and its association with mortality. Design We created a cohort of patients hospitalised in Scotland due to COVID-19 during the first wave (between 28 February 2020 and 22 September 2020) of the pandemic. We identified the level of multimorbidity for the patient on admission and used logistic regression to analyse the association between multimorbidity and risk of mortality among patients hospitalised with COVID-19. Setting Scotland, UK. Participants Patients hospitalised due to COVID-19. Main outcome measures Mortality as recorded on National Records of Scotland death certificate and being coded for COVID-19 on the death certificate or death within 28 days of a positive COVID-19 test. Results Almost 58% of patients admitted to the hospital due to COVID-19 had multimorbidity. Adjusting for confounding factors of age, sex, social class and presence in the shielding group, multimorbidity was significantly associated with mortality (adjusted odds ratio 1.48, 95%CI 1.26–1.75). The presence of multimorbidity and presence in the shielding patients list were independently associated with mortality but there was no multiplicative effect of having both (adjusted odds ratio 0.91, 95%CI 0.64–1.29). Conclusions Multimorbidity is an independent risk factor of mortality among individuals who were hospitalised due to COVID-19. Individuals with multimorbidity could be prioritised when making preventive policies, for example, by expanding shielding advice to this group and prioritising them for vaccination. Publisher PDF

[We congratulate Asadi, Hashemi, and Balakrishnan for a comprehensive review of age-based maintenance strategies and a thorough study of the statistic “signature” for age-based maintenance of multi-component coherent systems. Among many contributions, Asadi, Hashemi, and Balakrishnan's paper also provides a taxonomic framework with which to categorize and classify the plethora of age-based maintenance models. Section 2 is of great importance, providing new researchers with a reliable nomenclature. What is missing in this section, however, is a detailed explanation of the notation “coherent system,” which will also help clarify the type systems to which the notation signature is applicable. Case study in this article covers a wide range of scenarios, and the two exemplar systems are also representative. However, the case study serves more as a tutorial rather than a proof of superiority. The tables and figures are for demonstrating the (uniqueness of) optimization results, but not for justifying the advantages of using the statistic signature. It would be of much practical value to compare the relative performance of maintenance models with and without using signature...]

Background Dengue is a significant public health issue that is caused by Aedes spp. mosquitoes. The current vector control methods are unable to effectively reduce Aedes populations and thus fail to decrease dengue transmission. Hence, there is an urgent need for new tools and strategies to reduce dengue transmission in a wide range of settings. In this study, the Mosquito Home System (MHS) and Mosquito Home Aqua (MHAQ) formulations were assessed as commercial autodissemination traps in laboratory and small-scale field trials. Method Multiple series of laboratory and small-scale field trials were performed to assess the efficacy of MHS and MHAQ exposed to Ae. aegypti. In the laboratory trials, various parameters such as fecundity, fertility, wing size, oviposition preferences, residual effects, and MHAQ transference to other containers through controlled experiments were tested. For small-scale field trials, the efficacy of the MHS and MHAQ approaches was determined to ascertain whether wild mosquitoes could transfer the MHAQ formulation from MHS stations to ovitraps. Results The data revealed that Ae. aegypti was highly susceptible to low concentrations of MHAQ formulations and had a residual effect of up to 3 months, with MHAQ exposure affecting fecundity, fertility, and mosquito wing size. In the oviposition studies, gravid females strongly preferred the hay infusion compared to tap water and MHAQ during egg-laying in the laboratory. Nevertheless, the use of commercial MHAQ by MHS was highly attractive in field settings compared to conventional ovitraps among local Aedes spp. mosquitoes. In addition, MHAQ horizontal transfer activities in the laboratory and small-scale field trials were demonstrated through larval bioassays. These findings demonstrated the potential of MHAQ to be transferred to new containers in each study site. Conclusion This study provided proof of principle for the autodissemination of MHAQ. Through further refinement, this technique and device could become an effective oviposition trap and offer an alternative preventive tool for vector control management. Graphical abstract

This paper extends the principal component analysis (PCA) to moderately non-stationary vector time series. We propose a method that searches for a linear transformation of the original series such that the transformed series is segmented into uncorrelated subseries with lower dimensions. A columns’ rearrangement method is proposed to regroup transformed series based on their relationships. We discuss the theoretical properties of the proposed method for fixed and large dimensional cases. Many simulation studies show our approach is suitable for moderately non-stationary data. Illustrations on real data are provided.

ObjectiveTo determine whether COVID-19 has a significant impact on adequacy of household income to meet basic needs (primary outcome) and work absence due to sickness (secondary outcome), both at the onset of illness (short term) and subsequently (long term).DesignMultilevel mixed regression analysis of self-reported data from monthly online questionnaires, completed 1 May 2020 to 28 October 2021, adjusting for baseline characteristics including age, sex, socioeconomic status and self-rated health.Setting and participantsParticipants (n=16 910) were UK residents aged 16 years or over participating in a national longitudinal study of COVID-19 (COVIDENCE UK).ResultsIncident COVID-19 was independently associated with increased odds of participants reporting household income as being inadequate to meet their basic needs in the short term (adjusted OR (aOR) 1.39, 95% CI 1.12 to 1.73) though this did not persist in the long term (aOR 1.00, 95% CI 0.86 to 1.16). Exploratory analysis revealed a stronger short-term association among those who reported long COVID, defined as the presence of symptoms lasting more than 4 weeks after disease onset, than those reporting COVID-19 without long COVID (p for trend 0.002). Incident COVID-19 associated with increased odds of reporting sickness absence from work in the long term (aOR 4.73, 95% CI 2.47 to 9.06) but not in the short term (aOR 1.34, 95% CI 0.52 to 3.49).ConclusionsWe demonstrate an independent association between COVID-19 and increased risk of economic vulnerability among COVIDENCE participants, measured by both household income sufficiency and sickness absence from work. Taking these findings together with pre-existing research showing that socioeconomic disadvantage increases the risk of developing COVID-19, this may suggest a ‘vicious cycle’ of impaired health and poor economic outcomes.Trial registration numberNCT04330599.

Analyses of long-term temperature records based on satellite data have revealed an increase in the frequency and intensity of marine heatwaves (MHWs) in the world oceans, a trend directly associated with global change according to climate model simulations. However, these analyses often target open ocean pelagic systems and rarely include local scale, field temperature records that are more adequate to assess the impact of MHWs close to the land-sea interface. Here, we compared the incidence and characteristics of open ocean MHWs detected by satellites with those observed in the field over two decades (1998-2019) at two temperate intertidal locations in the central Cantabrian Sea, southern Bay of Biscay. Satellite retrievals tended to smooth out cooling events associated with intermittent, alongshore upwelling, especially during summer. These biases propagated to the characterization of MHWs and resulted in an overestimation of their incidence and duration close to the coast. To reconcile satellite and field records, we developed a downscaling approach based on regression modeling that enabled the reconstruction of past temperatures and analyze MHW trends. Despite the cooling effect due to upwelling, the temperature reconstructions revealed a six-fold increase in the incidence of MHWs in the Cantabrian Sea over the last four decades. A comparison between static (no trend) vs. dynamic (featuring a linear warming trend) MHW detection thresholds allowed us to attribute over half of the increase in MHW incidence to the ocean warming trend. Our results highlight the importance of local processes to fully characterize the complexity and impacts of MHWs on marine coastal ecosystems and call for the conservation of climate refugia associated with coastal upwelling to counter the impacts of climate warming. [Abstract copyright: Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.]

[This corrects the article DOI: 10.1007/s42081-022-00165-z.]. [Abstract copyright: © The Author(s) under exclusive licence to Japanese Federation of Statistical Science Associations 2022.]

EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE - The Health Data Research Hub for Respiratory Health [MC_PC_19004], which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). Additional support has been provided through Public Health Scotland and Scottish Government DG Health and Social Care. FDRH acknowledges part support as Director of the NIHR Applied Research Collaboration (ARC) Oxford Thames Valley, and Theme Lead of the NIHR OUH BRC. We investigated thrombocytopenic, thromboembolic and hemorrhagic events following a second dose of ChAdOx1 and BNT162b2 using a self-controlled case series analysis. We used a national prospective cohort with 2.0 million(m) adults vaccinated with two doses of ChAdOx or 1.6 m with BNT162b2. The incidence rate ratio (IRR) for idiopathic thrombocytopenic purpura (ITP) 14–20 days post-ChAdOx1 second dose was 2.14, 95% confidence interval (CI) 0.90–5.08. The incidence of ITP post-second dose ChAdOx1 was 0.59 (0.37–0.89) per 100,000 doses. No evidence of an increased risk of CVST was found for the 0–27 day risk period (IRR 0.83, 95% CI 0.16 to 4.26). However, few (≤5) events arose within this risk period. It is perhaps noteworthy that these events all clustered in the 7–13 day period (IRR 4.06, 95% CI 0.94 to 17.51). No other associations were found for second dose ChAdOx1, or any association for second dose BNT162b2 vaccination. Second dose ChAdOx1 vaccination was associated with increased borderline risks of ITP and CVST events. However, these events were rare thus providing reassurance about the safety of these vaccines. Further analyses including more cases are required to determine more precisely the risk profile for ITP and CVST after a second dose of ChAdOx1 vaccine. Publisher PDF

The recent report of the Intergovernmental Panel on Climate Change is stark in its warnings about the changing climate, including future increases in the frequency and intensity of extremely hot weather. The well-established impacts of extreme heat on human health have led to widespread implementation of national and city-wide heat plans for mitigating such impacts. Evaluations of the effectiveness of some heat plans have been published, with previous reviews highlighting key methodological challenges. This article reviews methods used since and that address those challenges, so helping to set an agenda for improving evaluations of heat plans in terms of their effectiveness in reducing heat-health impacts. We examined the reviews that identified the methodological challenges and systematically searched the literature to find evaluations that had since been conducted. We found 11 evaluations. Their methods help address the key challenge of identifying study control groups and address other challenges to a limited extent. For future evaluations, we recommend: utilising recent evaluation methodologies, such as difference-in-differences quasi-experimental designs where appropriate; cross-agency working to utilise data on morbidity and confounders; adoption of a proposed universal heat index; and greater publication of evaluations. More evaluations should assess morbidity outcomes and be conducted in low- and middle-income countries. Evaluations of heat plans globally should employ robust methodologies, as demonstrated in existing studies and potentially transferrable from other fields. Publication of such evaluations will advance the field and thus help address some of the health challenges resulting from our changing climate.

The phenology, distribution, and size composition of plankton communities are changing rapidly in response to warming. This may lead to shifts in the prey fields of planktivorous fish, which play a key role in transferring energy up marine food chains. Here, we use 60 + years of Continuous Plankton Recorder data to explore temporal trends in key taxa and community traits in the prey field of planktivorous lesser sandeels (Ammodytes marinus) in the North Sea, the Faroes and southern Iceland. We found marked spatial variation in the prey field, with Calanus copepods generally being much more common in the northern part of the study area. In the western North Sea, the estimated amount of available energy in the prey field has decreased by more than 50% since the 1960s. This decrease was accompanied by declining abundances of small copepods, and shifts in the timing of peak annual prey abundances. Further, the estimated average prey community body size has increased in several of the locations considered. Overall, our results point to the importance of regional studies of prey fields, and caution against inferring ecological consequences based only on large-scale trends in key taxa or mean community traits.

Background: Since its emergence in November, 2021, in southern Africa, the SARS-CoV-2 omicron variant of concern (VOC) has rapidly spread across the world. We aimed to investigate the severity of omicron and the extent to which booster vaccines are effective in preventing symptomatic infection. Methods: In this study, using the Scotland-wide Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) platform, we did a cohort analysis with a nested test-negative design incident case-control study covering the period Nov 1–Dec 19, 2021, to provide initial estimates of omicron severity and the effectiveness of vaccine boosters against symptomatic disease relative to 25 weeks or more after the second vaccine dose. Primary care data derived from 940 general practices across Scotland were linked to laboratory data and hospital admission data. We compared outcomes between infection with the delta VOC (defined as S-gene positive) and the omicron VOC (defined as S-gene negative). We assessed effectiveness against symptomatic SARS-CoV-2 infection, with infection confirmed through a positive RT-PCR. Findings: By Dec 19, 2021, there were 23 840 S-gene-negative cases in Scotland, which were predominantly among those aged 20–39 years (11 732 [49·2%]). The proportion of S-gene-negative cases that were possible reinfections was more than ten times that of S-gene-positive cases (7·6% vs 0·7%; p

We give formulae for the cumulants of complex Wishart (LUE) and inverse Wishart matrices (inverse LUE). Their large-$N$ expansions are generating functions of double (strictly and weakly) monotone Hurwitz numbers which count constrained factorisations in the symmetric group. The two expansions can be compared and combined with a duality relation proved in [F. D. Cunden, F. Mezzadri, N. O'Connell and N. J. Simm, arXiv:1805.08760] to obtain: i) a combinatorial proof of the reflection formula between moments of LUE and inverse LUE at genus zero and, ii) a new functional relation between the generating functions of monotone and strictly monotone Hurwitz numbers. The main result resolves the integrality conjecture formulated in [F. D. Cunden, F. Mezzadri, N. J. Simm and P. Vivo, J. Phys. A 49 (2016)] on the time-delay cumulants in quantum chaotic transport. The precise combinatorial description of the cumulants given here may cast new light on the concordance between random matrix and semiclassical theories., 19 pages, 1 figure

BackgroundYoung people report higher levels of unsafe sex and have higher rates of sexually transmitted infections than any other age group. Schools are well placed to facilitate early intervention, but more effective approaches are required. Peer-led approaches can augment school-based education, but often fail to capitalise on mechanisms of social influence. The potential of using social media in sexual health has not been tested in school settings.ObjectivesFinalise the design of the Sexually Transmitted infections And Sexual Health (STASH) intervention; assess the recruitment and retention of peer supporters, and acceptability to participants and stakeholders; assess the fidelity and reach, in addition to the barriers to and facilitators of, implementation; refine programme theory; understand the potential of social media; determine design parameters for a future randomised controlled trial, including economic evaluation; and establish whether or not progression criteria were met.DesignThis was a feasibility study comprising intervention development and refinement of the STASH pilot and non-randomised feasibility trial in six schools. Control data were provided by students in the year above the intervention group.SettingSecondary schools in Scotland.ParticipantsStudents aged 14–16 years, teachers and intervention delivery partners.InterventionsThe STASH intervention was adapted from A Stop Smoking In Schools Trial (ASSIST) (an effective peer-led smoking intervention). Based on diffusion of innovation theory, the STASH study involves peer nomination to identify the most influential students, with the aim of recruiting and training 15% of the year group as peer supporters. The peer supporters deliver sexual health messages to friends in their year group via conversations and use of Facebook (www.facebook.com; Facebook, Inc., Menlo Park, CA, USA) to share varied content from a curated set of web-based resources. Peer supporters are given support themselves via follow-up sessions and via trainer membership of Facebook groups.Main outcome measuresThe primary outcome was whether or not progression criteria were met in relation to intervention acceptability and feasibility. The study also piloted indicative primary outcomes for a full-scale evaluation.Data sourcesPeer supporter questionnaire; observations of activities; interviews with trainers, teachers, peer supporters and students; monitoring log of peer supporter activities (including on Facebook and meeting attendance); questionnaire to control year group (baseline characteristics, social networks, mediators and sexual health outcomes); baseline and follow-up questionnaire (approximately 6 months later) for intervention year group.ResultsA total of 104 students were trained as peer supporters (just over half of those nominated for the role by their peers). Role retention was very high (97%). Of 611 students completing the follow-up questionnaire, 58% reported exposure to STASH study activities. Intervention acceptability was high among students and stakeholders. Activities were delivered with good fidelity. The peer supporters were active, representative of their year group and well connected within their social network. Carefully managed social media use by peer supporters augmented conversations. A primary outcome of ‘always safer sex’ was identified, measured as no sex or always condom use for vaginal or anal sex in the last 6 months. The intervention cost £42 per student. Six progression criteria were met. A seventh criterion (regarding uptake of role by peer supporters) was not.LimitationsSmall feasibility study that cannot comment on effectiveness.ConclusionsThe STASH intervention is feasible and acceptable within the context of Scottish secondary schools. The results support continuation to a full-scale evaluation.Future workSmall-scale improvements to the intervention, refinement to programme theory and funding sought for full-scale evaluation.Trial registrationCurrent Controlled Trials ISRCTN97369178.FundingThis project was funded by the National Institute for Health Research (NIHR) Public Health Research programme and will be published in full inPublic Health Research; Vol. 8, No. 15. See the NIHR Journals Library website for further project information.

Purpose: To explore the frequency and outcomes of cataract surgery in eyes with previous vitrectomy.Setting: Fifteen European countries.Design: Retrospective cross-sectional register-based study.Methods: The European Registry of Quality Outcomes of Cataract and Refractive Surgery (EUREQUO) contains data on baseline characteristics, surgery, and follow-up for cataract surgeries. Previous vitrectomy is included as a mandatory parameter in baseline characteristics. According to the protocol for EUREQUO, consecutive cases should be reported by participating units.Results: This study included data from units in 15 European countries from 2008 to 2018; 1 715 348 cataract extractions with follow-up data were reported to EUREQUO. Previous vitrectomy was reported in 19 416 eyes comprising 1.1% of all cases. This proportion was about the same for each study year. Most patients were men, and their mean age was 64.1 years compared with 73.7 years for the rest of the database. The preoperative visual acuity was modestly worse in postvitrectomy eyes compared with the opposite (corrected distance visual acuity [CDVA] 0.45 vs 0.25, respectively). A postoperative CDVA of 0.5 or better was achieved by 82.8% of the postvitrectomy eyes compared with 95.6% for the non-postvitrectomy eyes. The absolute mean biometry prediction error for the same groups was 0.52 diopters (D) vs 0.43 D, respectively.Conclusions: Patients undergoing cataract extraction after previous vitrectomy were younger and mostly men. Their visual and refractive outcomes were slightly inferior compared with the patients without vitrectomy. Copyright (C) 2020 Published by Wolters Kluwer on behalf of ASCRS and ESCRS

Microzooplankton are the primary herbivores and nutrient regenerators in the marine food web, but their importance is often underestimated, and the quantitative relationships between environmental factors and the biomass and herbivory rate of microzooplankton remain obscure. To fill this gap, we conducted 224 dilution experiments to measure microzooplankton biomass and herbivory rate across a vast area of the marginal seas of China. To gain the potential mechanisms controlling microzooplankton herbivory, we also use a model that combines the Metabolic Theory of Ecology and the functional responses of grazing to quantify the effects of temperature, phytoplankton biomass, and microzooplankton biomass on microzooplankton grazing rate. We estimate an activation energy of 0.51 eV of microzooplankton and found that the Holling III function best described the functional response of microzooplankton grazing with a maximal ingestion rate of 4.76 d −1 at 15°C and a half-saturation constant of 0.27 μM N. We also find that microzooplankton biomass scales with phytoplankton biomass with an exponent of 0.77, consistent with the general 3/4 scaling law found in other ecosystems. This scaling relationship is accompanied by a shift from ciliates to heterotrophic dinoflagellates with increasing phytoplankton biomass. Our results provide empirical patterns that will be vital to parameterize and validate marine ecosystem models, particularly in China seas.

This paper addresses a data integration problem: given several mutually consistent datasets each of which measures a subset of the variables of interest, how can one construct a probabilistic model that fits the data and gives reasonable answers to questions which are under-determined by the data? Here we show how to obtain a Bayesian network model which represents the unique probability function that agrees with the probability distributions measured by the datasets and otherwise has maximum entropy. We provide a general algorithm, OBN-cDS, which offers substantial efficiency savings over the standard brute-force approach to determining the maximum entropy probability function. Furthermore, we develop modifications to the general algorithm which enable further efficiency savings but which are only applicable in particular situations. We show that there are circumstances in which one can obtain the model (i) directly from the data; (ii) by solving algebraic problems; and (iii) by solving relatively simple independent optimisation problems.

Background: Mobility restrictions prevent the spread of infections to disease-free areas, and early in the coronavirus disease 2019 (COVID-19) pandemic, most countries imposed severe restrictions on mobility as soon as it was clear that containment of local outbreaks was insufficient to control spread. These restrictions have adverse impacts on the economy and other aspects of human health, and it is important to quantify their impact for evaluating their future value. Methods: Here we develop Scotland Coronavirus transmission Model (SCoVMod), a model for COVID-19 in Scotland, which presents unusual challenges because of its diverse geography and population conditions. Our fitted model captures spatio-temporal patterns of mortality in the first phase of the epidemic to a fine geographical scale. Results: We find that lockdown restrictions reduced transmission rates down to an estimated 12\% of its pre-lockdown rate. We show that, while the timing of COVID-19 restrictions influences the role of the transmission rate on the number of COVID-related deaths, early reduction in long distance movements does not. However, poor health associated with deprivation has a considerable association with mortality; the Council Area (CA) with the greatest health-related deprivation was found to have a mortality rate 2.45 times greater than the CA with the lowest health-related deprivation considering all deaths occurring outside of carehomes. Conclusions: We find that in even an early epidemic with poor case ascertainment, a useful spatially explicit model can be fit with meaningful parameters based on the spatio-temporal distribution of death counts. Our simple approach is useful to strategically examine trade-offs between travel related restrictions and physical distancing, and the effect of deprivation-related factors on outcomes.

Electricity imbalance pricing provides the ultimate incentive for generators and suppliers to contract with one another ahead of time and deliver against their obligations. As delivery time approaches, traders must judge whether to trade-out a position or settle it in the balancing market at the as-yet-unknown imbalance price. Forecasting the imbalance price (and related volumes) is therefore a necessity in short-term markets. However, this topic has received surprisingly little attention in the academic literature despite clear need by practitioners. Furthermore, the emergence of algorithmic trading demands automated forecasting and decision-making, with those best able to extract predictive information from available data gaining a competitive advantage. Here we present the case for developing imbalance price forecasting methods and provide motivating examples from the Great Britain’s balancing market, demonstrating forecast skill and value.

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This analysis is part of the Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) study. EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE – The Health Data Research Hub for Respiratory Health (MC_PC_19004), which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through the Scottish Government DG Health and Social Care. SAS and AS are also supported by the COVID-19 Longitudinal Health and Wellbeing National Core Study, funded by the Medical Research Council (MC_PC_20030). SVK acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). JM is partly funded by the National Institute for Health Research Applied Research Collaboration West (NIHR ARC West). Objectives COVID-19 has resulted in the greatest disruption to National Health Service (NHS) care in its over 70-year history. Building on our previous work, we assessed the ongoing impact of pandemic-related disruption on provision of emergency and elective hospital-based care across Scotland over the first year of the pandemic. Design We undertook interrupted time-series analyses to evaluate the impact of ongoing pandemic-related disruption on hospital NHS care provision at national level and across demographics and clinical specialties spanning the period 29 March 2020?28 March 2021. Setting Scotland, UK. Participants Patients receiving hospital care from NHS Scotland. Main outcome measures We used the percentage change of accident and emergency attendances, and emergency and planned hospital admissions during the pandemic compared to the average admission rate for equivalent weeks in 2018-2019. Results As restrictions were gradually lifted in Scotland after the first lockdown, hospital-based admissions increased approaching pre-pandemic levels. Subsequent tightening of restrictions in September 2020 were associated with a change in slope of relative weekly admissions rate: -1.98% (-2.38, -1.58) in accident and emergency attendance, -1.36% (-1.68, -1.04) in emergency admissions and -2.31% (-2.95, -1.66) in planned admissions. A similar pattern was seen across sex, socioeconomic status and most age groups, except children (0-14 years) where accident and emergency attendance, and emergency admissions were persistently low over the study period. Conclusions We found substantial disruption to urgent and planned inpatient healthcare provision in hospitals across NHS Scotland. There is the need for urgent policy responses to address continuing unmet health needs and to ensure resilience in the context of future pandemics. Publisher PDF

Introduction: To define baseline echocardiographic, electrocardiographic (ECG) and computed tomographic (CT) findings of patients with heart failure undergoing transcatheter aortic valve replacement (TAVR) and analyze their overall procedural outcomes. Methods: Between 2018 and 2021, patients with severe aortic stenosis (AS) who performed transcatheter aortic valve replacement (TAVR) in Sabah Al Ahmad Cardiac Centre, Al Amiri Hospital were identified. A retrospective review of patients' parameters including pre-, intra-, and post-procedural data was conducted. Patients were grouped in 2 subgroups according to their EF: EF

Alcohol withdrawal syndrome (AWS) occurs in 2% of patients admitted to U.K. hospitals. Routine treatment includes thiamine and benzodiazepines. Laboratory studies indicate that thiamine requires magnesium for optimal activity, however this has not translated into clinical practice. Patients experiencing AWS were randomized to three groups: (group 1) thiamine, (group 2) thiamine plus MgSO4 or (group 3) MgSO4. Pre- and 2-h post-treatment blood samples were taken. AWS severity was recorded using the Glasgow Modified Alcohol Withdrawal Score (GMAWS). The primary outcome measure was 15% change in erythrocyte transketolase activity (ETKA) in group 3. Secondary outcome measures were change in plasma lactate concentrations and time to GMAWS = 0. 127 patients were recruited, 115 patients were included in the intention-to-treat analysis. Pre-treatment, the majority of patients had normal or high erythrocyte thiamine diphosphate (TDP) concentrations (≥ 275–675/> 675 ng/gHb respectively) (99%), low serum magnesium concentrations ( 2 mmol/L) (67%). Basal ETKA did not change significantly in groups 1, 2 or 3. Magnesium deficient patients (2 = 0.053 and R2 = 0.236). Median plasma lactate concentrations normalized (≤ 2.0 mmol/L) across all three groups (p p ClinicalTrials.gov: NCT03466528.

This work is concerned with the convergence and stability of the truncated Euler-Maruyama (EM) method for super-linear stochastic differential delay equations (SDDEs) with time-variable delay and Poisson jumps. By constructing appropriate truncated functions to control the super-linear growth of the original coefficients, we present two types of the truncated EM method for such jump-diffusion SDDEs with time-variable delay, which is proposed to be approximated by the value taken at the nearest grid points on the left of the delayed argument. The first type is proved to have a strong convergence order which is arbitrarily close to 1=2 in mean-square sense, under the Khasminskii-type, global monotonicity with U function and polynomial growth conditions. The second type is convergent in qth (q < 2) moment under the local Lipschitz plus generalized Khasminskii-type conditions. In addition, we show that the partially truncated EM method preserves the mean-square and H1 stabilities of the true solutions. Lastly, we carry out some numerical experiments to support the theoretical results.

BackgroundCoronavirus disease 2019 (COVID-19) has disproportionately affected people with mental health conditions.AimsWe investigated the association between receiving psychotropic drugs, as an indicator of mental health conditions, and COVID-19 vaccine uptake.MethodWe conducted a cross-sectional analysis of a prospective cohort of the Northern Ireland adult population using national linked primary care registration, vaccination, secondary care and pharmacy dispensing data. Univariable and multivariable logistic regression analyses investigated the association between anxiolytic, antidepressant, antipsychotic, and hypnotic use and COVID-19 vaccination status, accounting for age, gender, deprivation and comorbidities. Receiving any COVID-19 vaccine was the primary outcome.ResultsThere were 1 433 814 individuals, of whom 1 166 917 received a COVID-19 vaccination. Psychotropic medications were dispensed to 267 049 people. In univariable analysis, people who received any psychotropic medication had greater odds of receiving COVID-19 vaccination: odds ratio (OR) = 1.42 (95% CI 1.41–1.44). However, after adjustment, psychotropic medication use was associated with reduced odds of vaccination (ORadj = 0.90, 95% CI 0.89–0.91). People who received anxiolytics (ORadj = 0.63, 95% CI 0.61–0.65), antipsychotics (ORadj = 0.75, 95% CI 0.73–0.78) and hypnotics (ORadj = 0.90, 95% CI 0.87–0.93) had reduced odds of being vaccinated. Antidepressant use was not associated with vaccination (ORadj = 1.02, 95% CI 1.00–1.03).ConclusionsWe found significantly lower odds of vaccination in people who were receiving treatment with anxiolytic and antipsychotic medications. There is an urgent need for evidence-based, tailored vaccine support for people with mental health conditions.

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

Background: This study investigates in-hospital mortality amongst patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its relation to serum levels of gamma-glutamyl transferase (GGT). Methods: Patients were stratified according to serum levels of gamma-glutamyl transferase (GGT) (GGT

This study was supported by the Changing Arctic Ocean projects EcoLight (03V01465), Arctic PRIZE (NE/P00573X/1; NE/P005721/1), Diatom-ARCTIC (NE/R012849/1; 03F0810A), MiMeMo (NE/R012679/1), CHASE, Peanuts (NE/R012636/1) and Diapod (NE/P005985/1) jointly funded by the UKRI Natural Environment Research Council (NERC) and the German Federal Ministry of Education and Research (BMBF). VSK was funded by the FRontiers in Arctic marine Monitoring program (FRAM). Open Access funding enabled and organized by Projekt DEAL. The Arctic marine ecosystem is shaped by the seasonality of the solar cycle, spanning from 24-h light at the sea surface in summer to 24-h darkness in winter. The amount of light available for under-ice ecosystems is the result of different physical and biological processes that affect its path through atmosphere, snow, sea ice and water. In this article, we review the present state of knowledge of the abiotic (clouds, sea ice, snow, suspended matter) and biotic (sea ice algae and phytoplankton) controls on the underwater light field. We focus on how the available light affects the seasonal cycle of primary production (sympagic and pelagic) and discuss the sensitivity of ecosystems to changes in the light field based on model simulations. Lastly, we discuss predicted future changes in under-ice light as a consequence of climate change and their potential ecological implications, with the aim of providing a guide for future research. Publisher PDF

Funding: EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE—the Health Data Research Hub for Respiratory Health [MC_PC_19004] which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional EAVE II support has been provided through the Scottish Government DG Health and Social Care. COPS receive additional funding from Tommy’s Charity (Charity number 1060508; SC039280) and is supported by Sands (Charity number 299679). S.J.S. is supported by the Wellcome Trust (209560/Z/17/Z). S.V.K. acknowledges funding from an NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). B.A. was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No.813546, the Baily Thomas Charitable Fund, the Data Driven Innovation and the UK Economic and Social Research Council (ES/N018877/1) during the course of this work. Publisher PDF

The temporal evolution of the physical and biogeochemical properties of the Atlantic Jet (AJ) along the first similar to 75 m of the water column during a 4-day journey was analysed by following the trajectory of a drifter dragged by the jet from the Strait of Gibraltar towards the Alboran Sea. Three stages were differentiated based on the evolution of several variables (e.g., velocity, temperature, nutrients, fluorescence). (i) Within the Strait of Gibraltar, the water column was primarily influenced by the tidal cycle, leading to a nutrient-enrichment of surface waters. However, due to the short residence time, the phytoplankton community that was mainly dominated by diatoms, did not demonstrate significant changes. (H) Once outside the Strait, the drifter trajectory was mainly influenced by the frontal dynamics associated with the AJ. The drifter moved forward along the jet but also laterally across it and was continuously attracted to the mainstream (maximum current speed) or detached to its southern edge (minimum current speed). Due to the associated upwelling processes induced by the intensification of the current along the mainstream, the water column was characterized by colder, nutrient-richer water and lower fluorescence values. Conversely, along the southern edge of the jet, the water column was characterized by higher temperature, low nutrient concentration, and higher fluorescence. Along the first stations of this stage, diatom total abundance and biovolume continuously increased, reaching values similar to 12-times higher than the initial concentrations. (Hi) In the last stage, the water parcel was still influenced by the frontal dynamics but with less intensity. Additionally, the colder and denser water of the AJ and the associated phytoplankton community subducted progressively as it moved into the region surrounded by warmer waters. Concomitantly, fluorescence and diatoms total abundance and biovolume decreased and were influenced by the decline of nutrient availability and the increase of mesozooplankton. Our results reveal the coupled processes induced by the entrance of the AJ in the Alboran Sea and highlight the strong control of the physical environment over the ecological processes in this region., The authors gratefully acknowledge the officers, crew and technical staff of the R.V. Sarmiento de Gamboa for their altruistic help during the cruise, all the scientific team that participated in the MEGAN campaign collecting the different datasets, Manuel Arjonilla for nutrient sample measurements, and Reyes Garcia for her collaboration in the treatment of plankton samples. They also thank the Copernicus Marine Environmental Monitoring Service for providing access to satellite data. Neural network analyses were performed in the facilities of the Area de Sistemas de Informacion de la Universidad de Cadiz (https://supercomputacion.uca.es).Finally, the authors acknowledge Sara Soria Piriz (@nautillustrations) for the drawing of the conceptual diagram in Fig. 10. Comments provided by two anonymous reviewers substantially improved subsequent versions of the manuscript. The Spanish National Research Plan through project CTM2013-49048 has supported this work. Iria Sala and Marina Bolado-Penagos were supported by a grant of the FPI fellowship program, Spain. To accomplish this work, Iria Sala carried out a short-term stay with the research group Dinamica del Ecosistema Planctonico at the Instituto Espanol de Oceanografia de Gijon, under the supervision of Dr Angel Lopez-Urrutia, supported by a grant of the FPI fellowship program.

In the behavioral epidemiology (BE) of infectious diseases, little theoretical effort seems to have been devoted to understand the possible effects of individuals' behavioral responses during an epidemic outbreak in small populations. To fill this gap, here we first build general, behavior implicit, SIR epidemic models including behavioral responses and set them within the framework of nonlinear feedback control theory. Second, we provide a thorough investigation of the effects of different types of agents' behavioral responses for the dynamics of hybrid stochastic SIR outbreak models. In the proposed model, the stochastic discrete dynamics of infection spread is combined with a continuous model describing the agents' delayed behavioral response. The delay reflects the memory mechanisms with which individuals enact protective behavior based on past data on the epidemic course. This results in a stochastic hybrid system with time-varying transition probabilities. To simulate such system, we extend Gillespie's classic stochastic simulation algorithm by developing analytical formulas valid for our classes of models. The algorithm is used to simulate a number of stochastic behavioral models and to classify the effects of different types of agents' behavioral responses. In particular this work focuses on the effects of the structure of the response function and of the form of the temporal distribution of such response. Among the various results, we stress the appearance of multiple, stochastic epidemic waves triggered by the delayed behavioral response of individuals.

Background: \ud Reports suggest that COVID-19 vaccine effectiveness is decreasing, but whether this reflects waning or new SARS-CoV-2 variants—especially delta (B.1.617.2)—is unclear. We investigated the association between time since two doses of ChAdOx1 nCoV-19 vaccine and risk of severe COVID-19 outcomes in Scotland (where delta was dominant), with comparative analyses in Brazil (where delta was uncommon).\ud \ud Methods: \ud In this retrospective, population-based cohort study in Brazil and Scotland, we linked national databases from the EAVE II study in Scotland; and the COVID-19 Vaccination Campaign, Acute Respiratory Infection Suspected Cases, and Severe Acute Respiratory Infection/Illness datasets in Brazil) for vaccination, laboratory testing, clinical, and mortality data. We defined cohorts of adults (aged ≥18 years) who received two doses of ChAdOx1 nCoV-19 and compared rates of severe COVID-19 outcomes (ie, COVID-19 hospital admission or death) across fortnightly periods, relative to 2–3 weeks after the second dose. Entry to the Scotland cohort started from May 19, 2021, and entry to the Brazil cohort started from Jan 18, 2021. Follow-up in both cohorts was until Oct 25, 2021. Poisson regression was used to estimate rate ratios (RRs) and vaccine effectiveness, with 95% CIs.\ud \ud Findings: \ud 1 972 454 adults received two doses of ChAdOx1 nCoV-19 in Scotland and 42 558 839 in Brazil, with longer follow-up in Scotland because two-dose vaccination began earlier in Scotland than in Brazil. In Scotland, RRs for severe COVID-19 increased to 2·01 (95% CI 1·54–2·62) at 10–11 weeks, 3·01 (2·26–3·99) at 14–15 weeks, and 5·43 (4·00–7·38) at 18–19 weeks after the second dose. The pattern of results was similar in Brazil, with RRs of 2·29 (2·01–2·61) at 10–11 weeks, 3·10 (2·63–3·64) at 14–15 weeks, and 4·71 (3·83–5·78) at 18–19 weeks after the second dose. In Scotland, vaccine effectiveness decreased from 83·7% (95% CI 79·7–87·0) at 2–3 weeks, to 75·9% (72·9–78·6) at 14–15 weeks, and 63·7% (59·6–67·4) at 18–19 weeks after the second dose. In Brazil, vaccine effectiveness decreased from 86·4% (85·4–87·3) at 2–3 weeks, to 59·7% (54·6–64·2) at 14–15 weeks, and 42·2% (32·4–50·6) at 18–19 weeks.\ud \ud Interpretation: \ud We found waning vaccine protection of ChAdOx1 nCoV-19 against COVID-19 hospital admissions and deaths in both Scotland and Brazil, this becoming evident within three months of the second vaccine dose. Consideration needs to be given to providing booster vaccine doses for people who have received ChAdOx1 nCoV-19.\ud \ud Funding: \ud UK Research and Innovation (Medical Research Council), Scottish Government, Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK, Fiocruz, Fazer o Bem Faz Bem Programme; Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro.\ud \ud Translation: \ud For the Portuguese translation of the abstract see Supplementary Materials section.

A popular framing of Goodhart's Law states, "When a measure become a target, it ceases to be a good measure". The extent to which this may be the case in the reporting of sea louse infestation on salmon farms is explored here. Due to the importance of controlling sea louse infestation on salmon farms, monitoring programmes are active in most salmon producing regions and, in many, a maximum allowable sea louse level is specified. Using publicly accessible data from Norway and BC, Canada, this study investigated the extent to which the framing of these programmes, in particular the specification of low threshold levels, may be affecting the veracity of the reported sea louse infestation data. In BC, where the threshold level is set to 3 mobile Lepeophtheirus salmonis little evidence of anomalous patterns in the data and the overall proportion of females within the adult sea lice population is around 0.43. By contrast, in Norway where lower sea louse limits are in place (at either 0.5 or 0.2 adult female L. salmonis), there is evidence of unexpected and sharp reductions in the abundance of adult females reported around these threshold values. In addition, the average proportion of females is estimated to be only around 0.20 of the total adult L. salmonis population. The unexpected observations in the data were much more evident for farms in the southern areas of Norway and over the most recent years. These findings appear to support the case that the measurement of sea lice on salmon farms can be significantly influenced by targets (particularly those which are highly demanding), and that as such, researchers and fish health professionals should be aware of potential biases within these data. In addition, regulators should carefully consider the unintended consequences of setting certain sea louse thresholds and the ways in which the potential to effectively review data quality and accuracy may be impacted by the choice of sea louse stage(s) that are reported.

Various types of acceptance reliability sampling plans have been reported in the literature. Most of the existing studies deal with the lifetimes of items described by continuous distributions. However, discrete lifetimes are also frequently encountered in practice. For example, field failures are often collected and reported daily, weekly, and so forth. Items often operate in cycles and the experimenter observes the number of cycles successfully completed prior to failure. In this study, we develop a variables acceptance reliability sampling plan for items having discrete lifetimes. Furthermore, the reliability improvement in the population reliability characteristics after the testing procedure, as compared to those before the test, is discussed in detail. The reliability sampling acceptance test is applied for heterogeneous populations using the alternative discrete hazard rate for the corresponding proportional hazards model. Some numerical examples illustrate our findings.

Background Patients with acute pulmonary embolism (PE) exhibit a wide spectrum of clinical and laboratory features when presenting to hospital and pathophysiologic mechanisms differentiating low-risk and high-risk PE are poorly understood. Objectives To investigate the prognostic value of clinical, laboratory and radiological information that is available within routine tests undertaken for patients with acute PE. Methods Electronic patient records (EPR) of patients who underwent Computed Tomography Pulmonary Angiogram (CTPA) scan for the investigation of acute PE during 6-month period (01.01.2016–30.06.2016) were examined. Data was gathered from EPR for patients that met inclusion criteria and all CTPA scans were re-evaluated. Biochemical thresholds of low-grade and high-grade inflammation, serum CRP >10mg/L and >150mg/L and serum albumin concentrations Results Of the total CTPA reports (n = 2129) examined, 245 patients were eligible for inclusion. Of these, 20 (8%) patients had died at 28-days and 43 (18%) at 6-months. Of the 197 non-cancer related presentations, 28-day and 6-month mortality were 3% and 8% respectively. Of the 48 cancer related presentations, 28-day and 6-month mortality were 29% and 58% respectively. On univariate analysis, age ≥65 years (p Conclusion PESI score >100, poGPS≥1, NLR ≥3 and CAC score ≥6 were associated with 28-day and 6-month mortality. PESI score ≥100, poGPS≥1 and NLR ≥3 remained independently associated with 28-day mortality. PESI score ≥100 and CAC score ≥6 remained independently associated with 6-month mortality. When patients with underlying cancer were excluded from the analysis, GPS≥1 remained independently associated with 6-month mortality. The role of the systemic inflammatory response (SIR) in determining treatment and prognosis requires further study. Routine reporting of CAC scores in CTPA scans for acute PE may have a role in aiding clinical decision-making regarding treatment and prognosis.

Funding: This research is part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation (grant ref MC_PC_20058). SVK acknowledges funding from a NRS Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). Background The dynamics of acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and severity of disease among children and young people (CYP) across different settings are of considerable clinical, public health and societal interest. Severe COVID-19 cases, requiring hospitalisations, and deaths have been reported in some CYP suggesting a need to extend vaccinations to these age groups. As part of the ongoing Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II) study, we aim to investigate the uptake, effectiveness and safety of COVID-19 vaccines in children and young people (CYP) aged 0 to 17 years in Scotland. Specifically, we will estimate: (i) uptake of vaccines against COVID-19, (ii) vaccine effectiveness (VE) against the outcomes of symptomatic SARS-CoV-2 infection, hospitalisation, intensive care unit (ICU) admissions, and death; (iii) VE for first/second dose timing among different age groups and risk groups; and (iv) the safety of vaccines. Methods and analysis We will conduct an open prospective cohort study classifying exposure as time-varying. We will compare outcomes amongst first dose vaccinated and second dose vaccinated CYP to those not yet vaccinated. A Test Negative Design (TND) case control study will be nested within this national cohort to investigate VE against symptomatic infection. The primary outcomes will be (i) uptake of vaccines against COVID-19, (ii) time to COVID-19 infection, hospitalisation, ICU admissions or death, and (iii) adverse events related to vaccines. Vaccination status (unvaccinated, one dose and two doses) will be defined as a time-varying exposure. Data from multiple sources will be linked using a unique identifier. We will conduct descriptive analyses to explore trends in vaccine uptake, and association between different exposure variables and vaccine uptake will be determined using multivariable logistic regression models. VE will be assessed from time-dependent Cox models or Poisson regression models, adjusted for relevant confounders, including age, sex, socioeconomic status, and comorbidities. We will employ self-controlled study designs to determine the risk of adverse events following COVID-19 vaccination. Ethics and dissemination Ethics approval was obtained from the National Research Ethics Committee, South East Scotland 02. We will present findings of this study at international conferences, in peer-reviewed journals and to policy-makers. Publisher PDF

There is considerable interest in the waning of effectiveness of coronavirus disease 2019 (COVID-19) vaccines and vaccine effectiveness (VE) of booster doses. Using linked national Brazilian databases, we undertook a test-negative design study involving almost 14 million people (~16 million tests) to estimate VE of CoronaVac over time and VE of BNT162b2 booster vaccination against RT–PCR-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and severe COVID-19 outcomes (hospitalization or death). Compared with unvaccinated individuals, CoronaVac VE at 14–30 d after the second dose was 55.0% (95% confidence interval (CI): 54.3–55.7) against confirmed infection and 82.1% (95% CI: 81.4–82.8) against severe outcomes. VE decreased to 34.7% (95% CI: 33.1–36.2) against infection and 72.5% (95% CI: 70.9–74.0) against severe outcomes over 180 d after the second dose. A BNT162b2 booster, 6 months after the second dose of CoronaVac, improved VE against infection to 92.7% (95% CI: 91.0−94.0) and VE against severe outcomes to 97.3% (95% CI: 96.1−98.1) 14–30 d after the booster. Compared with younger age groups, individuals 80 years of age or older had lower protection after the second dose but similar protection after the booster. Our findings support a BNT162b2 booster vaccine dose after two doses of CoronaVac, particularly for the elderly.

Emerging reports of rare neurological complications associated with COVID-19 infection and vaccinations are leading to regulatory, clinical and public health concerns. We undertook a self-controlled case series study to investigate hospital admissions from neurological complications in the 28 days after a first dose of ChAdOx1nCoV-19 (n = 20,417,752) or BNT162b2 (n = 12,134,782), and after a SARS-CoV-2-positive test (n = 2,005,280). There was an increased risk of Guillain–Barré syndrome (incidence rate ratio (IRR), 2.90; 95% confidence interval (CI): 2.15–3.92 at 15–21 days after vaccination) and Bell’s palsy (IRR, 1.29; 95% CI: 1.08–1.56 at 15–21 days) with ChAdOx1nCoV-19. There was an increased risk of hemorrhagic stroke (IRR, 1.38; 95% CI: 1.12–1.71 at 15–21 days) with BNT162b2. An independent Scottish cohort provided further support for the association between ChAdOx1nCoV and Guillain–Barré syndrome (IRR, 2.32; 95% CI: 1.08–5.02 at 1–28 days). There was a substantially higher risk of all neurological outcomes in the 28 days after a positive SARS-CoV-2 test including Guillain–Barré syndrome (IRR, 5.25; 95% CI: 3.00–9.18). Overall, we estimated 38 excess cases of Guillain–Barré syndrome per 10 million people receiving ChAdOx1nCoV-19 and 145 excess cases per 10 million people after a positive SARS-CoV-2 test. In summary, although we find an increased risk of neurological complications in those who received COVID-19 vaccines, the risk of these complications is greater following a positive SARS-CoV-2 test., A self-controlled case series analysis of nearly 32 million people in England shows an increased risk of rare neurological complications in those who received COVID-19 vaccines and following SARS-CoV-2 infection. The results highlight 38 excess cases of Guillain–Barré syndrome per 10 million ChAdOx1nCoV-19 vaccinations.

Authors thank the EAVE II Patient Advisory Group for their support. EAVE II is funded by the Medical Research Council (MR/R008345/1) with the support of BREATHE—The Health Data Research Hub for Respiratory Health (MC_PC_19004)—which is funded through the UK Research and Innovation Industrial Strategy Challenge Fund and delivered through Health Data Research UK. Additional support has been provided through Public Health Scotland and Scottish Government Director-General Health and Social Care and the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation. SVK acknowledges funding from an NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the Medical Research Council (MC_UU_00022/2) and the Scottish Government Chief Scientist Office (SPHSU17). Background There is an urgent need to inform policy deliberations about whether children with asthma should be vaccinated against SARS-CoV-2 and, if so, which subset of children with asthma should be prioritised. We were asked by the UK's Joint Commission on Vaccination and Immunisation to undertake an urgent analysis to identify which children with asthma were at increased risk of serious COVID-19 outcomes. Methods This national incident cohort study was done in all children in Scotland aged 5–17 years who were included in the linked dataset of Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE II). We used data from EAVE II to investigate the risk of COVID-19 hospitalisation among children with markers of uncontrolled asthma defined by either previous asthma hospital admission or oral corticosteroid prescription in the previous 2 years. A Cox proportional hazard model was used to derive hazard ratios (HRs) and 95% CIs for the association between asthma and COVID-19 hospital admission, stratified by markers of asthma control (previous asthma hospital admission and number of previous prescriptions for oral corticosteroids within 2 years of the study start date). Analyses were adjusted for age, sex, socioeconomic status, comorbidity, and previous hospital admission. Findings Between March 1, 2020, and July 27, 2021, 752 867 children were included in the EAVE II dataset, 63 463 (8·4%) of whom had clinician-diagnosed-and-recorded asthma. Of these, 4339 (6·8%) had RT-PCR confirmed SARS-CoV-2 infection. In those with confirmed infection, 67 (1·5%) were admitted to hospital with COVID-19. Among the 689 404 children without asthma, 40 231 (5·8%) had confirmed SARS-CoV-2 infections, of whom 382 (0·9%) were admitted to hospital with COVID-19. The rate of COVID-19 hospital admission was higher in children with poorly controlled asthma than in those with well controlled asthma or without asthma. When using previous hospital admission for asthma as the marker of uncontrolled asthma, the adjusted HR was 6·40 (95% CI 3·27–12·53) for those with poorly controlled asthma and 1·36 (1·02–1·80) for those with well controlled asthma, compared with those with no asthma. When using oral corticosteroid prescriptions as the marker of uncontrolled asthma, the adjusted HR was 3·38 (1·84–6·21) for those with three or more prescribed courses of corticosteroids, 3·53 (1·87–6·67) for those with two prescribed courses of corticosteroids, 1·52 (0·90–2·57) for those with one prescribed course of corticosteroids, and 1·34 (0·98–1·82) for those with no prescribed course, compared with those with no asthma. Interpretation School-aged children with asthma with previous recent hospital admission or two or more courses of oral corticosteroids are at markedly increased risk of COVID-19 hospital admission and should be considered a priority for vaccinations. This would translate into 9124 children across Scotland and an estimated 109 448 children across the UK. Publisher PDF

We study a model system with nematic and magnetic orders, within a channel geometry modelled by an interval, $[-D, D]$. The system is characterised by a tensor-valued nematic order parameter $\mathbf{Q}$ and a vector-valued magnetisation $\mathbf{M}$, and the observable states are modelled as stable critical points of an appropriately defined free energy. In particular, the full energy includes a nemato-magnetic coupling term characterised by a parameter $c$. We (i) derive $L^\infty$ bounds for $\mathbf{Q}$ and $\mathbf{M}$; (ii) prove a uniqueness result in parameter regimes defined by $c$, $D$ and material- and temperature-dependent correlation lengths; (iii) analyse order reconstruction solutions, possessing domain walls, and their stabilities as a function of $D$ and $c$ and (iv) perform numerical studies that elucidate the interplay of $c$ and $D$ for multistability., Comment: accepted in SIAM Journal on Numerical Analysis

Motivated by small-scale natural and industrial processes involving flow over and/or through a layer of a porous medium, a mathematical model for the steady gravity-driven flow of a rivulet of fluid with finite width over and through a permeable membrane is formulated and analysed. The three-dimensional shape of the free surface of a rivulet with either fixed semi-width or fixed contact angle is determined, and it is shown how the length, base area and volume of the rivulet on the permeable part of the membrane depend on the physical properties of the system. In particular, whereas there is a physically realisable pendant rivulet solution only if the semi-width does not exceed a critical value, there are physically realisable sessile and vertical rivulet solutions for all values of the semi-width; moreover, a sessile rivulet with fixed semi-width has a finite maximum possible length which is attained in the limit of a wide rivulet.

Since Mao in 2013 discretised the system observations for stabilisation problem of hybrid SDEs (stochastic differential equations with Markovian switching) by feedback control, the study of this topic using a constant observation frequency has been further developed. However, time-varying observation frequencies have not been considered. Particularly, an observational more efficient way is to consider the time-varying property of the system and observe a periodic SDE system at the periodic time-varying frequencies. This study investigates how to stabilise a periodic hybrid SDE by a periodic feedback control, based on periodic discrete-time observations. This study provides sufficient conditions under which the controlled system can achieve pth moment exponential stability for p > 1 and almost sure exponential stability. Lyapunov's method and inequalities are main tools for derivation and analysis. The existence of observation interval sequences is verified and one way of its calculation is provided. Finally, an example is given for illustration. Their new techniques not only reduce observational cost by reducing observation frequency dramatically but also offer flexibility on system observation settings. This study allows readers to set observation frequencies according to their needs to some extent.