Low-intensity online intervention (LiON) for distressed young people in Hong Kong: Preliminary findings

Previous studies have demonstrated that low-intensity intervention is effective in improving mental health in young people. Whilst interventions have majorly been offered online during COVID-19 pandemic, it is not known whether low-intensity interventions delivered online can also help reduce the level of distress experienced by young people. The study aimed to determine whether a low-intensity online intervention (LiON) can reduce levels of distress in young people greater than those in similar initial distress levels but received no intervention. Young people aged 15 to 24 were recruited for the 4-weekly LiON intervention consisting of three modules namely sleep and relaxation, stress-coping and problem-solving. The reductions in distress level after intervention were compared to those that occurred over a period of 3 months among community young people with similar baseline K6 distress levels. Seventy-four young people (mean age 20.24 [SD 2.26] years, 71.6% female) received the LiON intervention from December 2021 to July 2022. We observed a greater improvement in their distress levels after receiving the intervention than those with no intervention in the community (beta -4.13, 95%CI -5.12, -3.07, p < .001, Cohen's f2 0.027). The findings offered evidence that the LiON intervention significantly reduced young people's distress level in addition to the improvement that may occur naturally. The use of LiON is adaptable to a wider variety of frontline community organizations. Future evaluation of its cost-effectiveness is warranted.

Asymmetric volatility connectedness between cryptocurrencies and energy: Dynamics and determinants

We explore the dynamics and determinants of volatility connectedness between cryptocurrencies and energy. We employed a block dynamic equicorrelation model and a group volatility connectedness measurement to measure the cross-equicorrelation and volatility connectedness between cryptocurrencies and energy. We also adopted dynamic model averaging to identify the time-varying drivers. The results suggest that changes in cross-equicorrelation between the two groups were affected by influential global events and increased after the COVID-19 pandemic. Volatilities were transmitted in both directions between cryptocurrencies and energy, but the transmission from energy to cryptocurrencies is by far the strongest. The driver identification implies that the factors related to cryptocurrencies and global financial markets had important roles in explaining the volatility connectedness from cryptocurrencies to energy in some periods after the COVID-19 pandemic, but the effects were marginal. In contrast, factors such as electricity consumption, cryptocurrency turnovers, and VIX were important in affecting the volatility connectedness from energy to cryptocurrencies, and the effects depended on factors and changed over time. Copyright © 2023 Wan, Song, Zhang and Yin.

A Systematic Review of Technology Reviews in Language Teaching and Learning Journals

Technology reviews are a specific article genre published in several language teaching and learning journals. Their emergence is likely due to the proliferation of technology that facilitates and supports language acquisition. These reviews aim to increase teachers' and learners' awareness of the forms of technology available and succinctly describe their benefits and limitations for language teaching and learning. As education enters a new digital age, accelerated by the COVID-19 pandemic, it is essential to determine which forms of technology support teachers' professional learning and how they can be utilized. This article presents a systematic review of technology reviews published between 2017 and 2022 in five Q1 SCOPUS-indexed language teaching and learning journals: RELC Journal, TESOL Journal, CALICO Journal, Language Learning and Technology and Teaching English as a Second Language Electronic Journal (TESL-EJ). These five journals were the only Q1 language teaching and learning journals we identified that publish technology reviews. All 73 technology reviews published in the 5-year period in the 5 journals were reviewed. Using professional digital competence as a framework, we explore what the articles reveal about how technology is used, as well as the knowledge gaps that remain. We examine the types and features of the technology described in the reviews, the language skills and educational levels of the learners, and the pedagogical implications of technology use. We found that the technology reviews mainly introduced the technological features and functions of the reviewed technologies with less emphasis placed on their pedagogical utilities and social aspects of their use for language teaching. The article concludes with recommendations for authors and journal editors regarding the content that should be included in a technology review to ensure that it is helpful to the profession. We also offer advice to practitioners on how to benefit from technology reviews. © The Author(s) 2023.

Health Resource Utilisation and Disparities: an Ecological Study of Admission Patterns Across Ethnicity in England Between 2017 and 2020.

BACKGROUND AND AIM: The COVID-19 pandemic highlighted adverse outcomes in Asian, Black, and ethnic minority groups. More research is required to explore underlying ethnic health inequalities. In this study, we aim to examine pre-COVID ethnic inequalities more generally through healthcare utilisation to contextualise underlying inequalities that were present before the pandemic. DESIGN: This was an ecological study exploring all admissions to NHS hospitals in England from 2017 to 2020. METHODS: The primary outcomes were admission rates within ethnic groups. Secondary outcomes included age-specific and age-standardised admission rates. Sub-analysis of admission rates across an index of multiple deprivation (IMD) deciles was also performed to contextualise the impact of socioeconomic differences amongst ethnic categories. Results were presented as a relative ratio (RR) with 95% confidence intervals. RESULTS: Age-standardised admission rates were higher in Asian (RR 1.40 [1.38-1.41] in 2019) and Black (RR 1.37 [1.37-1.38]) and lower in Mixed groups (RR 0.91 [0.90-0.91]) relative to White. There was significant missingness or misassignment of ethnicity in NHS admissions: with 11.7% of admissions having an unknown/not-stated ethnicity assignment and 'other' ethnicity being significantly over-represented. Admission rates did not mirror the degree of deprivation across all ethnic categories. CONCLUSIONS: This study shows Black and Asian ethnic groups have higher admission rates compared to White across all age groups and when standardised for age. There is evidence of incomplete and misidentification of ethnicity assignment in NHS admission records, which may introduce bias to work on these datasets. Differences in admission rates across individual ethnic categories cannot solely be explained by socioeconomic status. Further work is needed to identify ethnicity-specific factors of these inequalities to allow targeted interventions at the local level.

Research on the spread trend of COVID-19 based on SEIR-C model

The latent and insidious nature of COVID-19 transmission poses a great challenge to epidemic prevention and control. In order to predict its transmission trend more accurately, optimal epidemic prevention and control strategies and measures can be formulated. In this paper, we propose a SEIR-C epidemic transmission trend prediction model, which improves the traditional SEIR infectious disease model and combines it with the GRU model, and experiments show that the model has better results in epidemic transmission prediction. The paper also analyses the situation of isolation measures and vaccines in epidemic prevention and control, providing some reference for the formulation of epidemic prevention and control policies. © 2022 ACM.

Trajectories of UCR as a measure of biological mechanisms underlying ethnicity associated outcomes in COVID-19

Introduction: Patients with Black and Asian ethnic background have been disproportionately affected by COVID-19 with increased disease severity, organ failure, intensive care admission, and premature mortality. 1-3 The urea-to-creatinine ratio (UCR) has been described as a biochemical signature of persistent critical illness, its hallmark catabolic state and late mortality during prolonged ICU stay.4 Low serum creatinine reflecting reduced muscle mass, which declines rapidly in acute severe illness in combination with net muscle protein breakdown which contribute substrate for increased hepatic urea synthesis, results in markedly elevated UCR. Objectives: To assess UCR as a candidate biological feature driving ethnicity associated outcomes of COVID-19 disease. Methods: Prospective analysis using registry data from all patients aged ≥16 years with an emergency admission to hospitals within Barts Health NHS Trust with SARSCoV-2 infection during 1 January 2020 - 13 May 2020 (wave 1), and 1 September 2020 -17 February 2021 (wave 2). Trajectories of routine haematology and clinical biochemistry blood results during hospital admission were assessed, and distinct phenotypes defined using unsupervised longitudinal clustering techniques using day 0 to 15 results.We determined distribution of identified phenotypes within patients categorised by ethnic group. Multivariable logistic regression accounting for predefined baseline risk factors was used to assess association between ethnicity, phenotypes, and 30-day mortality. All analyses were performed using R software v4.02 and the kml package for clustering. 5 Results are presented as n (%) and adjusted odds ratios (OR) with 95% confidence intervals. Results: We assessed 459 (wave 1) and 1337 (wave 2) patients after excluding those with unknown ethnicity and those with <7 blood results. Three clusters were identified based on trajectories of UCR. In wave 1, 48.1% of patients had persistently low levels of UCR (A), 38.6% had higher but stable levels (B), and 13.3% had the highest levels peaking after day 7 (C). In wave 2, three clusters were identified in similar proportions: 42.8% (a), 45.1% (b), 12.1% (c). In wave 1, patients in cluster C compared to A had the highest risk of death at 30 days (OR 4.59 [2.27-9.26], p<0.001). In wave 2, both clusters b (OR 1.58 [1.18-2.12], p< 0.001) and c (OR 3.96 [2.62-5.99], p<0.001) had higher risk of death compared to a. Distribution of cluster membership varied by ethnic category. In both waves, greater proportions of patients within cluster A/a were observed in patients with Black ethnicity (65.5% wave 1, 61.1% wave 2) compared to Asian (50.0% wave 1, 37.3% wave 2) and White (39.7% wave 1, 39.6% wave 2) ethnicity. Black ethnicity patients also had lowest proportions in cluster C/c (6.9% wave 1, 6.3% wave 2) compared to Asian (17.4% wave 1, 14.2% wave 2) and White (13.2% wave 1, 12.9% wave 2) ethnicity. Inclusion of UCR trajectory attenuated the higher risk of death seen in Asian patients in wave 1. Conclusion: Phenotypes based on UCR trajectories during hospital admission are associated with adverse outcomes following COVID-19 infection. Further work is needed to understand phenotypes of prolonged COVID-19 disease muscle wasting and its association with longerterm outcomes.

Nutritional adequacy and accuracy in long-stay critically ill patients as measured by indirect calorimetry

Introduction: Nutritional optimisation is recognised as having significant impact on clinical and functional outcomes of critically ill patients.1 Clinical recommendations suggest use of indirect calorimetry guided nutrition in the intensive care unit (ICU),2 and a recent systematic review demonstrated improved outcomes from its use.3 The COVID-19 pandemic has seen a greater proportion of patients with prolonged critical illness, a cohort for whom nutritional optimisation is a key unmet need.4 Objectives: To assess rates of over and underfeeding in a tertiary centre ICU and how these relate to markers of catabolism and persistent critical illness. Methods: Serial measurements of REE (resting energy expenditure) and RQ (respiratory quotient) by indirect calorimetry were performed using Q-NRG+ device (COSMED, Rome, Italy). Nutritional intake and estimations of requirements were recorded concurrently together with routine clinical observations, and markers of critical illness, catabolism and over or underfeeding. Results: Across 30 patients, REE was lower than estimated energy requirements, 24.2 (IQR 20.0-28.1) kcal/ day/kg IBW vs. 29.1(IQR 25.4-33.1) kcal/day/kg IBW, p<0.001. 41.8% of measurements showed overfeeding (actual calorie intake >110% of REE), and 23.3% showed underfeeding (actual calorie intake <85% of REE). Obese patients (n=15) were underfed (-98kcal/day deficit) compared to non-obese patients (n=15), who were on average overfed (+256kcal/day surplus), p=0.021. Overfeeding was also associated with greater length of ICU admission (R2 0.159, p<0.005). Median day of ICU admission in overfed patients was 39 days (IQR 24-56), and in underfed patients 21.5 (IQR 7.5-45.25). However, there was no significant association between calorie surplus or deficit, and other markers of overfeeding PaCO2, insulin use, ureacreatinine-ratio. Conclusion: This service evaluation recorded measurements of REE and RQ in critically ill patients with high lengths of ICU stay (up to 66 days). We observed increased rates of overfeeding with increased duration of ICU admission, and increased overfeeding in non-obese patients.

Epidemiological and clinical features of COVID-19 infected with SARS-CoV-2 Delta variant in Gansu Province

Objective To analyze the epidemiological and clinical features of coronavirus disease 2019 (COVID-19) infected with the Delta variant of SARS-CoV-2. Methods Retrospectively analyze the epidemiological and clinical features of 138 confirmed cases of COVID-19 infected with the Delta variant of SARS-CoV-2 from October 25, 2021 to November 19, 2021 in Yantan Branch of the Second People's Hospital of Lanzhou City. The epidemiological and demographic information, clinical symptoms, laboratory tests, chest CT, treatment and prognosis data were collected, with a final follow-up date of November 27, 2021. Results As of November 19, 2021, a total of 144 confirmed cases of COVID-19 were reported in Gansu Province, of which 138 cases [65 males (47.1%) and 73 females (52.9%), aged 2-87 (42.7±21.0) years old, with the clinical classification of mainly common type (48.6%, 67/138)] were concentrically treated in the Yantan Branch of the Second People's Hospital of Lanzhou City. The transmission mode of the Delta variant of SARS-CoV-2 is mainly in confined spaces, with obvious tour group and family aggregation;screening the close contacts and community investigation are the main approaches of finding the infected persons;86.2% (119/138) of confirmed patients have been vaccinated with the domestic inactivated COVID-19 vaccine. The most common clinical symptoms are cough (57.2%, 79/138), followed by sore throat (28.3%, 39/138), dry throat (24.6%, 34/138), and expectoration (21.0%, 29/138). Only 20.3% (28/138) of patients have fever, and 4 patients (2.9%) have decreased or lost sense of smell and taste. Laboratory tests showed that serum amyloid A and high-density lipoprotein cholesterol increased significantly. The Ct value of SARS-CoV-2 ORF1ab gene is 26.31±7.63, and N gene is 26.35±7.17. Chest CT fined that 71.3% (72/101) of confirmed patients showed bilateral lung lobes involvement, and the lesions are mostly located in the lower lobes of both lungs;the lesions are mainly flaky and patchy ground-glass opacities. All confirmed cases are treated with integrated traditional Chinese and Western medicine, mainly prone position ventilation and traditional Chinese medicine (TCM) treatment. The TCM treatment rate is 100% for severe cases. On the basis of respiratory support, nutritional support and anticoagulation, immunotherapy such as neutralizing antibodies are combined. Conclusions The main clinical features of COVID-19 infected by the Delta variant of SARS-CoV-2 in Gansu Province are low rate of fever, long time for viral nucleic acid turned to negative, low risk of severe illness after vaccination, the good therapeutic effect, no intubation, no extracorporeal membrane oxygenation (ECMO), and no deaths. "One person, one plan" personalized treatment with integrated Chinese and Western medicine can effectively control the progression of the disease and cure the disease.

Federated Transfer Learning-Based IDS for the Internet of Medical Things (IoMT)

The Internet of Medical Things (IoMT) is a set of medical devices and applications that connect to healthcare systems through the Internet. Those devices are equipped with communication technologies that allow them to communicate with each other and the Internet. Reliance on the IoMT is increasing with the increase in epidemics and chronic diseases such as COVID-19 and diabetes;with the increase in the number of IoMT users and the need for electronic data sharing and virtual services, cyberattacks in the healthcare sector for accessing confidential patient data has been increasing in the recent years. The healthcare applications and their infrastructures have special requirements for handling sensitive users' data and the need for high availability. Therefore, securing healthcare applications and data has attracted special attention from both industry and researchers. In this paper, we propose a Federated Transfer Learning-based Intrusion Detection System (IDS) to secure the patient's healthcare-connected devices. The model uses Deep Neural Network (DNN) algorithm for training the network and transferring the knowledge from the connected edge models to build an aggregated global model and customizing it for each one of the connected edge devices without exposing data privacy. CICIDS2017 dataset has been used to evaluate the performance in terms of accuracy, detection rate, and average training time. In addition to preserving data privacy of edge devices and achieving better performance, our comparison indicates that the proposed model can be generalized better and learns incrementally compared to other baseline ML/DL algorithms used in the traditional centralized learning schemes. © 2021 IEEE.

Ethnic disparities in hospitalisation and hospital-outcomes during the second wave of COVID-19 infection in east London.

It is unclear if changes in public behaviours, developments in COVID-19 treatments, improved patient care, and directed policy initiatives have altered outcomes for minority ethnic groups in the second pandemic wave. This was a prospective analysis of patients aged ≥ 16 years having an emergency admission with SARS-CoV-2 infection between 01/09/2020 and 17/02/2021 to acute NHS hospitals in east London. Multivariable survival analysis was used to assess associations between ethnicity and mortality accounting for predefined risk factors. Age-standardised rates of hospital admission relative to the local population were compared between ethnic groups. Of 5533 patients, the ethnic distribution was White (n = 1805, 32.6%), Asian/Asian British (n = 1983, 35.8%), Black/Black British (n = 634, 11.4%), Mixed/Other (n = 433, 7.8%), and unknown (n = 678, 12.2%). Excluding 678 patients with missing data, 4855 were included in multivariable analysis. Relative to the White population, Asian and Black populations experienced 4.1 times (3.77-4.39) and 2.1 times (1.88-2.33) higher rates of age-standardised hospital admission. After adjustment for various patient risk factors including age, sex, and socioeconomic deprivation, Asian patients were at significantly higher risk of death within 30 days (HR 1.47 [1.24-1.73]). No association with increased risk of death in hospitalised patients was observed for Black or Mixed/Other ethnicity. Asian and Black ethnic groups continue to experience poor outcomes following COVID-19. Despite higher-than-expected rates of hospital admission, Black and Asian patients also experienced similar or greater risk of death in hospital since the start of the pandemic, implying a higher overall risk of COVID-19 associated death in these communities.

Impact of SARS-CoV-2 on training and mental wellbeing of surgical gynaecological oncology trainees

Introduction/Background*The SARS-CoV-2 global-pandemic has caused a crisis disrupting health systems worldwide. Whilst efforts are afoot to determine the extent of disruption, impact on gynaecological oncology trainees/training has not been explored. We present data from an international survey on impact of SARS-CoV-2 on clinical practice, medical education, and mental wellbeing of surgical gynaecological oncology trainees.MethodologyIn our prospective cohort study, a customised web-based-survey was circulated to surgical gynaecological oncology trainees from national/international organisations (May-November 2020). Validated questionnaires assessed mental wellbeing. Wilcoxon rank sum test and Fisher’s exact test tested hypothesis about differences in means and proportions. Multiple linear regression evaluated effect of variables on psychological/mental wellbeing outcomes. Outcomes included clinical practice, medical education, anxiety & depression, distress, mental wellbeingResult(s)*127 trainees from 34 countries responded. 52% (66/127) were from countries with national training programmes (UK/USA/Netherlands/Canada/Australia) and 48% (61/127) from non-national training programme countries. 28% had suspected/confirmed COVID19;28% experienced drop in household income;20% self-isolated from households;45% had to re-use personal protective equipment and 22% purchased their own. 32.3% (41/127) trainees (national training programme trainees=16.6% (11/66);non national training programme trainees=49.1% (30/61), p=0.02) require additional time to complete their training fellowship. The additional training time anticipated did not differ between trainees from countries with/without national training programmes (p=0.11). Surgical training was detrimentally impacted for 50% trainees, with more national training programme trainees (62.3% (38/61) than non national training programme trainees (38.5% (25/65), p=0.01) reporting a detrimental impact despite a greater reduction in mean surgical exposure reported by non national training programme trainees. Departmental teaching continued throughout the pandemic for 69% (87/126) trainees, albeit at reduced frequency for 16.1% (14/87), and virtually for 88.5% (77/87). Trainees reporting adequate pastoral support had better mental wellbeing with lower-levels of anxiety/depression (p=0.02) and distress (p<0.001). National training programme trainees experienced higher levels of distress (p=0.01). Mean mental wellbeing scores were significantly higher pre-pandemic (8.3 (SD=1.6) versus post-pandemic (7 (SD=1.8);p=<0.01).Conclusion*SARS-CoV-2 has negatively impacted surgical training, household income and psychological/mental wellbeing of surgical gynaecological oncology trainees. Overall clinical impact was worse for non national training programme versus national training programme-trainees, though national-training-programme-trainees reported greater distress. COVID19-sickness increased anxiety/depression. The recovery-phase must focus on improving mental-wellbeing and addressing lost training opportunities.

Dynamic Analysis of an Epidemic Model With Infectivity in the Incubation Period

A transmission model for infectious diseases with infectivity in the latent periods was established. According to the law of disease transmission, the basic regeneration number, as the threshold of disease disappearance and spread, was solved. The stability of the system was discussed and the stability condition for the system was obtained. With the COVID-19 pandemic as an example, the effects of various measures for disease control were studied. The spread of the pandemic was discussed and predicted. The work makes a reference for epidemic disease control. © Editorial Office of Applied Mathematics and Mechanics.

Resource requirements for reintroducing elective surgery during the COVID-19 pandemic: modelling study.

BACKGROUND: The COVID-19 response required the cancellation of all but the most urgent surgical procedures. The number of cancelled surgical procedures owing to Covid-19, and the reintroduction of surgical acivirt, was modelled. METHODS: This was a modelling study using Hospital Episode Statistics data (2014-2019). Surgical procedures were grouped into four urgency classes. Expected numbers of surgical procedures performed between 1 March 2020 and 28 February 2021 were modelled. Procedure deficit was estimated using conservative assumptions and the gradual reintroduction of elective surgery from the 1 June 2020. Costs were calculated using NHS reference costs and are reported as millions or billions of euros. Estimates are reported with 95 per cent confidence intervals. RESULTS: A total of 4 547 534 (95 per cent c.i. 3 318 195 to 6 250 771) patients with a pooled mean age of 53.5 years were expected to undergo surgery between 1 March 2020 and 28 February 2021. By 31 May 2020, 749 247 (513 564 to 1 077 448) surgical procedures had been cancelled. Assuming that elective surgery is reintroduced gradually, 2 328 193 (1 483 834 - 3 450 043) patients will be awaiting surgery by 28 February 2021. The cost of delayed procedures is €5.3 (3.1 to 8.0) billion. Safe delivery of surgery during the pandemic will require substantial extra resources costing €526.8 (449.3 to 633.9) million. CONCLUSION: As a consequence of the Covid-19 pandemic, provision of elective surgery will be delayed and associated with increased healthcare costs.

Virus shedding dynamics in asymptomatic and mildly symptomatic patients infected with SARS-CoV-2.

OBJECTIVES: Asymptomatic patients, together with those with mild symptoms of coronavirus disease 2019 (COVID-19), may play an important role in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. However, the dynamics of virus shedding during the various phases of the clinical course of COVID-19 remains unclear at this stage. METHODS: A total of 18 patients found to be positive for SARS-CoV-2 infection by real-time reverse transcription PCR (RT-PCR) assay and admitted to Chongqing University Central Hospital between 29 January and 5 February 2020 were enrolled into this study. Medical data, pulmonary computed tomographic (CT) scan images and RT-PCR results were periodically collected during the patients' hospital stay. All participants were actively followed up for 2 weeks after discharge. RESULTS: A total of nine (50%) asymptomatic patients and nine (50%) patients with mild symptoms of COVID-19 were identified at admission. Six patients (66.7%) who were asymptomatic at admission developed subjective symptoms during hospitalization and were recategorized as being presymptomatic. The median duration of virus shedding was 11.5, 28 and 31 days for presymptomatic, asymptomatic and mildly symptomatic patients, separately. Seven patients (38.9%) continued to shed virus after hospital discharge. During the convalescent phase, detectable antibodies to SARS-CoV-2 and RNA were simultaneously observed in five patients (27.8%). CONCLUSIONS: Long-term virus shedding was documented in patients with mild symptoms and in asymptomatic patients. Specific antibody production to SARS-CoV-2 may not guarantee virus clearance after discharge. These observations should be considered when making decisions regarding clinical and public health, and when considering strategies for the prevention and control of SARS-CoV-2 infection.