Using innovative population-level data to understand the mental health impact of community-level events on young people: An example from the COVID-19 pandemic in Victoria

Aims: Since the onset of the COVID-19 pandemic, a significant rise in mental ill-health has been observed globally in young people, particularly amongst those in their final years of secondary school. The students' negative experiences coincide with a critical transitional period, which can subsequently disrupt milestones in social and educational development. This study aims to use innovative population-level data to map the impact of the pandemic on students entering higher education. Method(s): Tertiary education application data for Victorian students were obtained from the Victorian Tertiary Admissions Centre both pre-pandemic (2019/2020) and pandemic (2020/2021). Prevalence of mental health special considerations were compared between cohorts across geographical areas and applicant demographic subgroups. Relative risk regression models were used to understand the role of different risk factors. Result(s): The rate of mental health special considerations increased by 38% amongst all applications (pre-pandemic: 7.8%, n = 56 916;pandemic: 10.8%, n = 58 260). The highest increases were observed amongst students in areas with severe lockdown experiences and areas impacted by 2019/2020 black summer bushfires. The increases were higher amongst year 12 students and students with other preexisting risk factors (e.g., physical condition, learning disability). However, interestingly slightly higher increases were observed in areas with higher socioeconomic status, which is potentially related to inequality in mental health service access. Conclusion(s): As the consequences of mental health difficulties and academic disruption in youth can be long-lasting, it is critical to establish a mental health supportive framework both in and outside of higher education to facilitate young people's recovery from the pandemic.

Particulate matter air pollution and COVID-19 risk: A systematic review

Introduction/Aim: Ecological studies indicate ambient particulate matter >=2.5 mm (PM 2.5) air pollution is associated with poorer COVID-19 outcomes. However, these studies cannot account for individual heterogeneity and often lack precision in estimates of PM 2.5 exposure. We summarise evidence relating on individual-level data to determine whether PM 2.5 exposure increases the risk of COVID-19 infection, severe disease and death. Method(s): We conducted a systematic review of relevant case-control and cohort studies, searching Medline, Embase and the WHO COVID-19 databases. Study quality was evaluated using the Newcastle-Ottawa Scale. Result(s): N = 18 studies met the inclusion criteria. Generally, PM 2.5 exposure was significantly associated with higher rates of COVID-19 infection (all 7 studies positive) and severe COVID-19 disease (8 of 9 studies positive, 1 null). The effects on mortality were mixed but indicative of a positive association (4 of 6 studies positive, 2 null). Most studies were rated 'good' quality (13 of 18 studies), though there were still methodological issues;few used individual-level data to adjust for important confounders like socioeconomic status (3 of 18 studies), instead using area-based indicators (12 of 18 studies) or not adjusting for it at all (3 of 18 studies). Most studies with severe disease (9 of 10 studies) and mortality outcomes (5 of 6 studies) were based on people already diagnosed COVID-19, potentially introducing collider bias. Conclusion(s): There is strong evidence that ambient particulate matter air pollution increases the risk of COVID-19 infection, and weaker evidence of increases in risk of severe disease and mortality.

Antithrombotic strategies in COVID-19 patients: a systematic review and Bayesian network meta-analysis

Introduction: COVID-19 is a public health emergency of international concern. Clinicians are likely to adopt various antithrombotic strategies to prevent embolic events, but the optimal antithrombotic strategy remains uncertain. We performed a Bayesian network meta-analysis to evaluate various antithrombotic strategies comprehensively. Method(s): We systematically searched PubMed, Cochrane Library, Web of Science, EMBASE and Clinical trials. gov to screen trials comparing different antithrombotic strategies. The primary outcome is 28-day mortality, and the secondary outcomes include major thrombotic event, major bleeding and in-hospital mortality, etc. We assessed the risk of bias using the Cochrane Collaboration's tool and the quality of evidence according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. We successively performed traditional pairwise and Bayesian network meta-analysis using R v4.2.1 software. Result(s): Twenty-six eligible randomized controlled trials were included, giving a total of 35 paired comparisons with 32,041 patients randomized to 7 antithrombotic strategies. In comparison to standard of care (SoC) strategy, therapeutic anticoagulation (TA) (RR 0.36, 95% CrI 0.13-0.86) and prophylactic anticoagulation (PA) (RR 0.35, 95% CrI 0.12-0.85) strategy significantly reduced the mortality of COVID-19 patients (Fig. 1). The antiplatelet (AP) strategy was associated with high risk of major bleeding when compared with SoC strategy (RR 2.5, 95% CrI 1.1-8.9), and the TA (RR 0.43, 95% CrI 0.17-0.98), PA (RR 0.27, 95% CrI 0.10-0.63) and PA with Fibrinolytic agents (FA) strategy (RR 0.12, 95% CrI 0.01-0.81) was associated with low risk of major thrombotic event. Conclusion(s): This network meta-analysis indicates that the TA and PA strategies probably reduce mortality and confer other important benefits in COVID-19 patients. These findings provide guidance on how to choose optimal antithrombotic strategies for COVID-19 patients.

Dynamic correlations of renewable-energy companies: Evidence from a multilayer network model

Against the background of seeking to achieve carbon neutrality, relationships among renewable-energy companies around the world have become multiple and complex. In this work, the Pearson, Kendall, tail, and partial correlation coefficients were applied to 51 global companies - including solar and wind firms, independent power plants, and utilities - to explore the linear, nonlinear, extreme-risk, and direct relations between them. Sample data from 7 August 2015 to 6 August 2021 were considered, and three sub-periods were extracted from these sample data by analysis of the evolution of multiple correlations combined with event analysis. A four-layer correlation network model was then constructed. The main results are as follows. (1) The multiple relations among the selected firms underwent dramatic changes during two external shocks (the China-US trade war and the COVID-19 pandemic). (2) The extreme-risk network layer verified that the trade war mainly affected the relationships among companies in the solar industries of China and the US. (3) During the COVID-19 pandemic period, the linear and direct relationships among wind firms from Canada, Spain, and Germany were significantly increased. In this sub-period, edge-weight distributions of the four different layers were heterogeneous and varied from power-law features to Gaussian distributions. (4) During all the sub-periods, most companies had similar numbers of neighbors, while the numbers of neighbors of a few companies varied greatly in the four different layers. These findings provide a useful reference for stakeholders and may help them understand the connectedness and evolution of global renewable-energy markets. © 2023 Author(s).

Pathways, manifestations, and mechanisms of nerve injury in patients with COVID-19.

COVID-19 is the latest and most severe epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Besides the respiratory system, the effects of SARS-CoV-2 on central and peripheral nervous systems have been recognized by more and more people. Clinically, patients with COVID-19 have been reported from mild anosmia and hypoesthesia to acute necrotizing hemorrhagic encephalopathy and Guillain-Barre syndrome. In order to facilitate clinicians to recognize the nerve injury of COVID-19 patients and give timely treatment to these patients, this paper reviews the latest research progress on the possible pathways of nerve injury, clinical manifestations and pathogenesis of COVID-19 patients.Copyright © 2020 by the Chinese Medical Association.

Meta Analysis of the Efficacy and Safety of Rennin-angiotensin-aldosterone System Iinhibitors in Patients with COVID-19 Associated with Hypertension

Background The spreading epidemic of novel coronavirus (corona virus disease 2019, COVID-19) pneumonia poses a serious challenge to global life health and disease control, with significantly higher mortality rates among individuals infected with COVID-19 comorbid underlying disease. Inhibitors of the rennin-angiotensin-aldosterone system (RAASi), an important class of anti-hypertensive drugs, have been found to increase the morbidity and mortality of COVID-19. This study aimed to clarify the efficacy and safety of RAASi treatment in COVID-19 patients with hypertension. Objective To systematically evaluate the efficacy and safety of RAASi therapy in COVID-19 patients with hypertension. Methods PubMed, Embase, Cochrane Library and China National Knowledge Infrastructure (CNKI) were searched from inception to January 2022. A publicly available case-control studies of COVID-19 patients with hypertension treated with RAASi versus non RAASi therapy were included, and outcome measures were overall mortality, incidence of critical illness, incidence of acute respiratory distress syndrome (ARDS), incidence of myocardial injury, and incidence of renal injury, with meta-analysis performed using Revman 5.3. Results Seventeen studies with a total of 5 689 patients were included, of whom 2 168 received RAASi therapy and 3 521 did not. Meta analysis showed that overall mortality was lower in COVID-19 comorbid hypertensive patients treated with RAASi compared with non RAASi treated patients 〔OR=0.54, 95%CI (0.41, 0.72), P<0.000 1〕;Between RAASi treated and non RAASi treated COVID-19 patients associated with hypertension, the incidence of critical illness 〔OR=0. 92, 95%CI (0.79, 1.08), P=0.30〕, the incidence of ARDS 〔OR=0.81, 95%CI (0.57, 1.13, P=0.22〕, the incidence of myocardial injury 〔OR=1.03, 95%CI (0.83, 1.27), P=0.82〕, and the incidence of kidney injury 〔OR=1.13, 95%CI (0.78, 1.66), P=0.52〕, differences were not statistically significant. Conclusion Treatment with RAASi in COVID-19 patients with hypertension reduced the overall mortality rate, and did not increase the incidence of critical illness, ARDS, myocardial injury, and renal injury in COVID-19 patients with hypertension. RAASi therapy is effective and safe in treating patients with COVID-19 combined with hypertension. © 2022 Chinese General Practice. All rights reserved.

Infrared Thermal Imaging Face Recognition Method Based on Temperature Block Feature

In order to prevent COVID-19 effectively, non-contact body temperature measurement and human identification are required in public places, but face recognition based on visible light cannot meet the requirements. Therefore, this paper proposes a thermal imaging face recognition method based on temperature block feature extraction. Histogram equalization and median filter are used to preprocess the face image, and Sobel operator is used for face detection;Six dimensional features including temperature mean, standard deviation and adjacent difference are extracted from each temperature block in the average poolinged temperature matrix, and classified by max-correlation-coefficient method. The experimental results show that the recognition rate of this method is 6.1% higher than that of PCA method with the temperature block size of boldsymbol{2times 2}. When using the same hardware to execute the program, if the two recognition rates are very close, the average test time of the proposed method is 22.2% less than the one of deep learning models such as Alexnet. Furthermore, the proposed method has strong robustness for small training sample set. For example, the recognition rate of single training sample model can reach 0.7, while in the deep learning model, except Mobilenet can reach 0.6, all of the others are less than 0.4. © 2022 IEEE.

Locating Multi-Sources in Social Networks With a Low Infection Rate

With the development of modern technology, numerous economic losses are incurred by various spreading phenomena. Thus, it is of great significance to identify the initial sources triggering such phenomena. The investigation of source localization in social networks has gained substantial attention and become a popular topic of study. For practical spreading phenomena on social networks, the infection rates are relatively low. Hence, a high uncertainty of spreading trace might be incurred, which further incurs the reduction of localization accuracy obtained through existed source localization methods, especially the observer-based ones. Aiming to solve the source localization problem with a low infection rate, we propose a novel localization algorithm, i.e., path-based source identification (PBSI). First, a small number of nodes are selected and designated as observers. After the propagation process triggered by sources, we can obtain a snapshot. Later, a label is assigned to represent whether a node is infected or not, and observers are supposed to record the paths through which nodes are successfully infected. Based on source centrality theory, observers make the labels flow in the direction recorded during the label iteration process, which ensures the labels of nodes in the direction of the source increase gradually. Extensive experiments indicate that the proposed PBSI can handle source localization problems for both single and multi-source scenarios with better performance than that of state-of-the-art algorithms under different propagation models.

ONLINE EDUCATION OF REMOTE SENSING IN CHINA DURING THE COVID-19 PANDEMIC: A CASE OF STUDY IN JIANGSU NORMAL UNIVERSITY

Affected by the Coronavirus Disease (COVID-19) pandemic, almost all students in China have to study online at home from February to June, 2020. In this paper, we discussed the forms of online courses and took Jiangsu Normal University as an example to introduce the online courses of remote sensing in China. The results of the satisfaction survey show that more than 90% of the respondents agree with online courses and believe that online courses can at least meet basic learning needs in the age of COVID-19, and more than 60% of respondents claimed that they had met or exceeded their learning expectations. The major advantages of online course include reducing the gathering of people and thus the risk of infection. However, there are still some problems with online courses, and we hope that these problems can be solved well in the future. © 2021 IEEE

[Consensus of experts on the oral health management and medical risk prevention for the patients with chronic airway diseases (2022 edition)].

Today, there is greater awareness on the association between oral diseases and respiration diseases after the outbreak of COVID-19. However, confusion regarding the oral health management and medical risk prevention for patients with chronic airway diseases has been remained among dental clinicians. Therefore, the dental experts of the Fifth General Dentistry Special Committee, Chinese Stomatological Association, combined with the experts of respiratory and critical care medicine, undertook the formation of consensus on the oral health management of patients with chronic airway diseases in order to help dental clinicians to evaluate medical risks and make better treatment decision in clinical practice. In the present consensus report, the relationship of oral diseases and chronic airway diseases, the oral health management and the treatment recommendations of patients with chronic airway diseases are provided.

Characteristics and 30-day outcomes for urological cancer patients operated on during the COVID-19 pandemic

Introduction & Objectives: Coronavirus disease (COVID-19) has caused significant disruption to the management of urological cancers and significant cancellation or delay to elective cancer surgeries. Guidelines have been rapidly developed to facilitate optimal triaging, however, they are largely based on expert opinion and observational studies of small retrospective cohorts. This international, multicentre, prospective observational study aimed to evaluate the impact of the COVID-19 pandemic on the 30-day outcomes of patients with kidney, bladder and prostate cancer who underwent elective cancer surgery. Materials & Methods: The COVIDSurg-Cancer Study is a global collaborative observational study that includes urological (prostate, bladder and renal) cancer patients managed between March 2020 and June 2020 who were planned for elective surgery during the COVID-19 pandemic. The primary outcome was mortality within 30 days. The secondary outcomes were COVID-19 infections, respiratory complications and post-operative complications within 30 days. Results: Between 11th March and 19th April 2020, prospective data on 436 consecutive patients were collected from centres (Figure 1). Patients with SARS-CoV-2 were significantly more likely to die and experience post-operative respiratory complications including adult respiratory distress syndrome (3/14, 21.4%) (p<0.01), pneumonia (4/14, 28.6%) (p<0.01), oxygen therapy (10/14, 71.4%) (p<0.01) and pulmonary embolism (1/13, 7.1%) (p<0.01) within 30 days. 2/412 (0.5%) COVID-negative patients died within 30 days of operation, compared to 3/14 (21.4%) COVID positive patients, (p<0.01). The rates of 30-day post-operative Clavien-Dindo Grade III+ complications for nephrectomy, cystectomy and prostatectomy were 1.7% (2/119), 7.6% (4/53) and 3.3% (2/61,) respectively. (Figure Presented) Conclusions: This prospective multicentre study demonstrates that patients with COVID-19 undergoing elective cancer surgery were more likely to experience respiratory complications and die than patients who did not develop COVID-19. To continue elective cancer surgery throughout future waves of the pandemic, it would be sensible to take precautions to minimise the risk of patients developing COVID-19 peri-operatively.

Re-imagining Corporate Community Involvement during the COVID-19 Pandemic: A Case Study of Pharmaceutical Companies in Guangdong Province, China

In this paper, we examine the participation of commercial firms in the fight against COVID-19 through the lens of Corporate Community Involvement (CCI). To display CCI as part of ethical and responsible corporate behavior, CCI studies often use a business-centered approach while paying less attention to the role of the state. Based on the stories of some pharmaceutical companies in Guangdong province joining China's fight against the COVID-19 pandemic, we argue that the state may play a crucial role in shaping CCI activities and in making companies partner with the government under a state of emergency. We also point out that it is likely for these companies to translate their involvement in solving public health problems into profit-seeking opportunities. As such, this paper contributes to CCI studies by introducing a state-led approach and suggesting a form of "state-led and market-driven"CCI. Moreover, this study provides fresh information about the effects of corporations on social life and the practice of socially responsible corporate behavior in a state of public health emergency to anthropologists in the new subfields of anthropology of corporate social responsibility and anthropology of business corporations. Copyright © 2021 by the Society for Applied Anthropology.

Adaptive scheme for crowd counting using off-the-shelf wireless routers

Since the outbreak of the world-wide novel coronavirus pandemic, crowd counting in public areas, such as in shopping centers and in commercial streets, has gained popularity among public health administrations for preventing the crowds from gathering. In this paper, we propose a novel adaptive method for crowd counting based on Wi-Fi channel state information (CSI) by using common commercial wireless routers. Compared with previous researches on device-free crowd counting, our proposed method is more adaptive to the change of environment and can achieve high accuracy of crowd count estimation. Because the distance between access point (AP) and monitor point (MP) is typically non-fixed in real-world applications, the strength of received signals varies and makes the traditional amplitude-related models to perform poorly in different environments. In order to achieve adaptivity of the crowd count estimation model, we used convolutional neural network (ConvNet) to extract features from correlation coefficient matrix of subcarriers which are insensitive to the change of received signal strength. We conducted experiments in university classroom settings and our model achieved an overall accuracy of 97.79% in estimating a variable number of participants. © 2022 CRL Publishing. All rights reserved.

The local and systemic response to SARS-CoV-2 infection in children and adults

T1 Figure 1ConclusionsOverall, this largest paediatric single cell COVID-19 study to date showed significant differences in response to SARS-CoV-2 between children and adults, reflecting the changes of the immune landscape over developmental time, which in children are dominated by naïve and innate responses.

Reshaping the diagnostic pathways for investigation of haematuria during and after the COVID-19 pandemic: Diagnostic accuracy of strategies for the detection of bladder cancer from the IDENTIFY cohort study

Background: Haematuria often requires investigation with an imaging test and flexible cystoscopy to rule out urinary tract cancers. With a reduction in diagnostic services due to the COVID-19 pandemic there is a risk of compromise in the care of patients referred with haematuria. We aimed to provide a pragmatic strategy that optimises the use of scarce resources by reducing patient visits to hospital and allocating the appropriate diagnostic tests according to risk of bladder cancer. Methods: The IDENTIFY study was an international, prospective, multicentre cohort study of over 11,000 patients referred to secondary care for investigation of newly suspected urinary tract cancer. Patients underwent cystoscopy, imaging tests, urine cytology and transurethral resection of bladder tumour (TURBT), where indicated. We developed strategies using combinations of imaging and cytology as triage tests to flexible cystoscopy. These strategies aimed to maximise cancer detection within a pragmatic pathway in a resource-limited environment. Findings: 8112 patients (74 4%) received an ultrasound or a CT urogram, with or without cytology. 5737 (70 7%) patients had visible haematuria (VH) and 2375 (29 3%) had non-visible haematuria (NVH). Amongst all patients, 1474 (18 2%) had bladder cancer;1333 (23 2%) in VH group and 141 (5 94%) in NVH group. Diagnostic test performance was used to determine optimal age cut-offs for each proposed strategy. We recommended proceeding directly to TURBT for patients of any age with positive triage tests for cancer. Patients with negative triage tests under 35-years-old with VH, or under 50-years-old with NVH can safely be discharged without undergoing flexible cystoscopy. The remaining patients may undergo flexible cystoscopy, with a greater priority for older patients (threshold of 60-years-old with VH, or 70-years-old with NVH) to capture high risk bladder cancer. Interpretation: We suggest diagnostic strategies in patients with haematuria, which focus on detection of bladder cancer, whilst reducing the burden to healthcare services in a resource-limited setting.