Multi-scenario surveillance of respiratory viruses in aerosols with a sub-single molecule spatial resolution (preprint)

Highly sensitive airborne virus monitoring is critical for preventing and containing epidemics. However, the detection of airborne viruses at ultra-low concentrations remains challenging due to the lack of ultra-sensitive methods and easy-to-deployment equipment. Here, we present an integrated microfluidic cartridge that can accurately detect SARS-CoV-2 and various respiratory viruses with a sensitivity of 10 copies/mL. When seamlessly integrated with a high-flow aerosol sampler, our microdevice can achieve a sub-single molecule spatial resolution of 0.83 copies/m3 for airborne virus surveillance. We then designed a series of virus-in-aerosols monitoring systems (RIAMs), including versions of a multi-site sampling RIAMs (M-RIAMs), a stationary real-time RIAMs (S-RIAMs), and a roaming real-time RIAMs (R-RIAMs) for different application scenarios. Using M-RIAMs, we performed a comprehensive evaluation of 210 environmental samples from COVID-19 patient wards, including 30 aerosol samples. The highest positive detection rate of aerosol samples (60%) proved the aerosol-based SARS-CoV-2 monitoring represents an effective method for spatial risk assessment. The detection of 78 aerosol samples in real-world settings via S-RIAMs confirmed its reliability for ultra-sensitive and continuous airborne virus monitoring. Therefore, RIAMs shows the potential as an effective solution for mitigating the risk of airborne virus transmission.

Intelligent operation, maintenance, and control system for public building: towards infection risk mitigation and energy efficiency

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control system by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different number of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% with number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Psychological status of infertile men during the Coronavirus Disease 2019 Pandemic in China: a cross-sectional investigation.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak has had a widespread and profound impact on people's mental health. The factors associated with mental symptoms among men diagnosed with infertility, a disease closely related to psychological conditions, remain unclear. The aim of this study is to investigate the risk factors associated with mental symptoms among infertile Chinese men during the pandemic. RESULTS: A total of 4,098 eligible participants were recruited in this cross-sectional, nationwide study, including 2,034 (49.6%) with primary infertility and 2,064 (50.4%) with secondary infertility. The prevalence of mental health conditions was 36.3%, 39.6%, and 6.7% for anxiety, depression, and post-pandemic stress, respectively. Sexual dysfunction is associated with a higher risk with adjusted odds ratios (ORs) of 1.40 for anxiety, 1.38 for depression, and 2.32 for stress. Men receiving infertility drug therapy displayed a higher risk for anxiety (adjusted OR, 1.31) and depression (adjusted OR, 1.28) symptoms, while those receiving intrauterine insemination had a lower risk of anxiety (adjusted OR, 0.56) and depression (adjusted OR, 0.55) symptoms. CONCLUSION: The COVID-19 pandemic has had a significant psychological impact on infertile men. Several psychologically vulnerable populations were identified, including individuals with sexual dysfunction, respondents receiving infertility drug therapy, and those experiencing control measures for COVID-19. The findings provide a comprehensive profile of the mental health status of infertile Chinese men during the COVID-19 outbreak and provide potential psychological intervention strategies.

RéSUMé: CONTEXTE: L'épidémie de maladie à coronavirus 2019 (COVID-19) a eu un impact étendu et profond sur la santé mentale des gens. Les facteurs associés aux symptômes mentaux chez les hommes diagnostiqués comme infertiles, une maladie étroitement liée aux conditions psychologiques, restent flous. L'objectif de cette étude est d'étudier les facteurs de risque associés aux symptômes mentaux chez les hommes chinois infertiles pendant la pandémie. RéSULTATS: Au total, 4 098 participants admissibles ont été recrutés dans cette étude transversale à l'échelle nationale, dont 2 034 (49,6%) présentaient une infertilité primaire et 2 064 (50,4%) une infertilité secondaire. La prévalence des problèmes de santé mentale était respectivement de 36,3 %, 39,6 % et 6,7 % pour l'anxiété, la dépression, et le stress postpandémique. La dysfonction sexuelle est associée à un risque plus élevé avec des odds ratios ajustés (OR) de 1,40 pour l'anxiété, 1,38 pour la dépression et 2,32 pour le stress. Les hommes recevant un traitement médicamenteux contre l'infertilité présentaient un risque plus élevé de symptômes d'anxiété (OR ajusté, 1,31) et de dépression (OR ajusté, 1,28), alors que ceux dont le traitement consistait à faire des inséminations intra-utérines présentaient un risque plus faible de symptômes d'anxiété (OR ajusté, 0,56) et de dépression (OR ajusté, 0,55). CONCLUSIONS: La pandémie de COVID-19 a eu un impact psychologique important sur les hommes infertiles. Plusieurs populations psychologiquement vulnérables ont été identifiées, notamment les personnes souffrant de dysfonction sexuelle, les hommes recevant un traitement médicamenteux contre l'infertilité, et ceux subissant des mesures de contrôle de la COVID-19. Les résultats fournissent un profil complet de l'état de santé mentale des hommes Chinois infertiles pendant l'épidémie de COVID-19 et fournissent des stratégies potentielles d'intervention psychologique.

Intelligent operation, maintenance, and control system for public building: Towards infection risk mitigation and energy efficiency.

During the post-COVID-19 era, it is important but challenging to synchronously mitigate the infection risk and optimize the energy savings in public buildings. While, ineffective control of ventilation and purification systems can result in increased energy consumption and cross-contamination. This paper is to develop intelligent operation, maintenance, and control systems by coupling intelligent ventilation and air purification systems (negative ion generators). Optimal deployment of sensors is determined by Fuzzy C-mean (FCM), based on which CO2 concentration fields are rapidly predicted by combing the artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators. Optimal ventilation rates and number of negative ion generators are decided. A visualization platform is established to display the effects of ventilation control, epidemic prevention, and pollutant removal. The rapid prediction error of LLM-based ANN for CO2 concentration was below 10% compared with the simulation. Fast decision reduced CO2 concentration below 1000 ppm, infection risk below 1.5%, and energy consumption by 27.4%. The largest removal efficiency was 81% when number of negative ion generators was 10. This work can promote intelligent operation, maintenance, and control systems considering infection prevention and energy sustainability.

Impact of human capital and social capital on employability of Chinese college students under COVID-19 epidemic-Joint moderating effects of perception reduction of employment opportunities and future career clarity.

This research constructed a relationship model between human capital, social capital, and the employability of college students. With two moderating variables introduced, the perception reduction of employment opportunities under the COVID-19 epidemic and future career clarity, this research studied the direct impact of human capital and social capital on the employability of college students and boundary conditions. Research data from 810 employed Chinese college graduates shows that both human capital and social capital have a positive and significant impact on the employability; the perception reduction of employment opportunities under the COVID-19 epidemic negatively regulates the relationship between human capital and the employability of college students; the future career clarity positively regulates the relationship between human capital and the employability of college students; the perception reduction of employment opportunities under COVID-19 epidemic and the future career clarity jointly regulate the relationship between human capital, social capital and the employability of college students. These conclusions enrich the relevant theoretical and practical research on the employability of college students under the COVID-19 epidemic.

High Frequency of COVID-19 Vaccine Hesitancy among Canadians Immunized for Influenza: A Cross-Sectional Survey.

We assessed the frequency and correlates of COVID-19 vaccine hesitancy before Canada's vaccine rollout. A cross-sectional vaccine hesitancy survey was completed by consecutive patients/family members/staff who received the influenza vaccine at McGill University affiliated hospitals. Based on the self-reported likelihood of receiving a future vaccine (scale 0-10), the following three groups were defined: non-hesitant (score 10), mildly hesitant (7.1-9.9), and significantly hesitant (0-7). Factors associated with vaccine hesitancy were assessed with multivariate logistic regression analyses and binomial logistic regression machine learning modelling. The survey was completed by 1793 people. Thirty-seven percent of participants (n = 669) were hesitant (mildly: 315 (17.6%); significantly: 354 (19.7%)). Lower education levels, opposition and uncertainty about vaccines being mandatory, feelings of not receiving enough information about COVID-19 prevention, perceived social pressure to get a future vaccine, vaccine safety concerns, uncertainty regarding the vaccine risk-benefit ratio, and distrust towards pharmaceutical companies were factors associated with vaccine hesitancy. Vaccine safety concerns and opposition to mandatory vaccinations were the strongest correlates of vaccine hesitancy in both the logistic regressions and the machine learning model. In conclusion, in this study, over a third of people immunized for influenza before the COVID-19 vaccine rollout expressed some degree of vaccine hesitancy. Effectively addressing COVID-19 vaccine safety concerns may enhance vaccine uptake.

Management of hip fracture in COVID-19 infected patients.

Given that the global population of elderly individuals is expanding and the difficulty of recovery, hip fractures will be a huge challenge and a critical health issue for all of humanity. Although people have spent more time at home during the coronavirus disease 2019 (COVID-19) pandemic, hip fractures show no sign of abating. Extensive studies have shown that patients with hip fracture and COVID-19 have a multifold increase in mortality compared to those uninfected and a more complex clinical condition. At present, no detailed research has systematically analyzed the relationship between these two conditions and proposed a comprehensive solution. This article aims to systematically review the impact of COVID-19 on hip fracture and provide practical suggestions. We found that hip fracture patients with COVID-19 have higher mortality rates and more complicated clinical outcomes. Indirectly, COVID-19 prevents hip fracture patients from receiving regular medical treatment. With regard to the problems we encounter, we provide clinical recommendations based on existing research evidence and a clinical flowchart for the management of hip fracture patients who are COVID-19 positive. Our study will help clinicians adequately prepare in advance when dealing with such patients and optimize treatment decisions.

Corrigendum to: Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

[This corrects the article DOI: 10.1093/ofid/ofaa442.].

Ventilation Strategies for Mitigation of Infection Disease Transmission in an Indoor Environment: A Case Study in Office

During the normalization phase of the COVID-19 epidemic, society has gradually reverted to using building space, especially for public buildings, e.g., offices. Prevention of airborne pollutants has emerged as a major challenge. Ventilation strategies can contribute to mitigating the spread of airborne disease in an indoor environment, including increasing supply air rate, modifying ventilation mode, etc. The larger ventilation rate can inevitably lead to high energy consumption, which may be also ineffective in reducing infection risk. As a critical factor affecting the spread of viral contaminant, the potential of ventilation modes for control of COVID-19 should be explored. This study compared several ventilation strategies in the office, including mixing ventilation (MV), zone ventilation (ZV), stratum ventilation (SV) and displacement ventilation (DV), through analyzing ventilation performance and infection risk for the optimal one. By using ANSYS Fluent, the distributions of airflow and pollutant were simulated under various ventilation modes and infected occupants. The SV showed greater performance in mitigating infection disease spread than MV, ZV and DV, with an air distribution performance index (ADPI) of 90.5% and minimum infection risk of 13%. This work can provide a reference for development of ventilation strategies in public space oriented the prevention of COVID-19.

GaVe: A Webcam-Based Gaze Vending Interface Using One-Point Calibration (preprint)

Even before the Covid-19 pandemic, beneficial use cases for hygienic, touchless human-machine interaction have been explored. Gaze input, i.e., information input via eye-movements of users, represents a promising method for contact-free interaction in human-machine systems. In this paper, we present the GazeVending interface (GaVe), which lets users control actions on a display with their eyes. The interface works on a regular webcam, available on most of today's laptops, and only requires a one-point calibration before use. GaVe is designed in a hierarchical structure, presenting broad item cluster to users first and subsequently guiding them through another selection round, which allows the presentation of a large number of items. Cluster/item selection in GaVe is based on the dwell time of fixations, i.e., the time duration that users look at a given Cluster/item. A user study (N=22) was conducted to test optimal dwell time thresholds and comfortable human-to-display distances. Users' perception of the system, as well as error rates and task completion time were registered. We found that all participants were able to use the system with a short time training, and showed good performance during system usage, selecting a target item within a group of 12 items in 6.76 seconds on average. Participants were able to quickly understand and know how to interact with the interface. We provide design guidelines for GaVe and discuss the potentials of the system.

First-principles DFT investigations of the vibrational spectra of chloro-quine and hydroxychloroquine

Since the COVID-19 pandemic began, two drugs, chloroquine (CQ) and hydroxychloroquine (HCQ), have received renewed attention. Using the density functional theory method in the CASTEP and DMol3 packages, we calculated both molecules’ infrared spectra and the partial phonon density of states of the hydroxyl group to identify the origin of the differences between the two spectra. Some characteristic vibrational modes of the hydroxyl group in HCQ were analysed individually. We also compared their Fukui functions and found that the oxygen atom in HCQ possesses electrophilic properties. This finding may be related to the large difference in toxicity between these two drugs. The method herein presents a new pathway to investigate organic molecules from the view of physics.

Assessment and Management on the Risk of Glucocorticoid-Induced Osteonecrosis After COVID-19 (preprint)

Background: Coronavirus disease 2019 (COVID-19) is an emerging global medical challenge and glucocorticoids remain the most promising therapy. Osteonecrosis (ON) is a disease caused by reduced blood flow to bones in the joints, which will rapidly induce joint destroy. ON had been frequently identified among convalescent patients after Severe Acute Respiratory Syndrome (SARS). Considering the similarity of SARS and COVID-19 on their pathogen, clinical characteristics and therapeutic strategies, it is particularly worrying whether ON will be a common sequela among convalescent COVID-19 patient.Methods: This multi-strategy study integrating different research methods, such as meta-analysis, systematic review and cross-sectional investigation. At first, two meta-analyses were performed on the incidence of osteonecrosis among SARS patients and the clinical data of glucocorticoid exposure among COVID-19 patients. Then, a systematic review of low-dosage glucocorticoid associated osteonecrosis and a real-world cross-sectional investigation of glucocorticoid exposure of COVID-19 patients in China Wuhan were also provided. Moreover, the pathogenesis, diagnosis, prevention, and treatment options for osteonecrosis after COVID-19 infection were further described.Findings: Our meta-analysis showed that 32% of SARS patients had developed ON after receiving glucocorticoid treatment with high dose, and our system review also supported that low level glucocorticoid exposure may lead to the occurrence of ON. Similarly, 40% of COVID-19 patients had undergone glucocorticoid treatment according to our meta-analysis. The cross-sectional investigation in China Wuhan found that the average of cumulative glucocorticoid exposure level was 504 mg calculated by the dosage of methylprednisolone. Notably, a confirmed osteonecrosis case after COVID-19 was identified during our investigation. Preventive management of ON shall better start with regular clinical followup observation.Interpretation: Growing evidence of the glucocorticoid therapy for COVID-19 patients prompts us to put forward the risk-classification-based early screening and early prevention protocol of ON, which may be of clinical significance in favorable prognosis of this disease.Registration Details: PROSPERO, registration number CRD42020203536.Funding Information: This study was supported by the Special Project For COVID-19 Prevention and Management of Ministry of Education of China (2020-JYB-YJ-023), the National Key Research and Development Program of China (2019ZX09731-002) and the State Key Program of National Natural Science Foundation of China (82030122).Declaration of Interests: The authors declare no competing interests.Ethics Approval Statement: The protocol for the investigation study has been registered in the Chinese Clinical Trial Registry (ChiCTR), (URL: http://www.chictr.org.cn/showproj.aspx?proj=61769, No. ChiCTR2000038333). This study was approved by the Ethics Institutional Review Board of the Third Affiliated Hospital of Beijing University of Chinese Medicine (No. BZYSY-2020KYKTPJ-06), and informed consent was obtained from every participant patient.

Domain-Specific Pretraining for Vertical Search: Case Study on Biomedical Literature (preprint)

Information overload is a prevalent challenge in many high-value domains. A prominent case in point is the explosion of the biomedical literature on COVID-19, which swelled to hundreds of thousands of papers in a matter of months. In general, biomedical literature expands by two papers every minute, totalling over a million new papers every year. Search in the biomedical realm, and many other vertical domains is challenging due to the scarcity of direct supervision from click logs. Self-supervised learning has emerged as a promising direction to overcome the annotation bottleneck. We propose a general approach for vertical search based on domain-specific pretraining and present a case study for the biomedical domain. Despite being substantially simpler and not using any relevance labels for training or development, our method performs comparably or better than the best systems in the official TREC-COVID evaluation, a COVID-related biomedical search competition. Using distributed computing in modern cloud infrastructure, our system can scale to tens of millions of articles on PubMed and has been deployed as Microsoft Biomedical Search, a new search experience for biomedical literature: https://aka.ms/biomedsearch.

Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

BACKGROUND: Public health interventions have been implemented to contain the outbreak of coronavirus disease 2019 (COVID-19) in New York City. However, the assessment of those interventions-for example, social distancing and cloth face coverings-based on real-world data from published studies is lacking. METHODS: The Susceptible-Exposed-Infectious-Removed (SEIR) compartmental model was used to evaluate the effect of social distancing and cloth face coverings on the daily culminative laboratory confirmed cases in New York City (NYC) and COVID-19 transmissibility. The latter was measured by Rt reproduction numbers in 3 phases that were based on 2 interventions implemented during this timeline. RESULTS: Transmissibility decreased from phase 1 to phase 3. The initial R0 was 4.60 in phase 1 without any intervention. After social distancing, the Rt value was reduced by 68%, while after the mask recommendation, it was further reduced by ~60%. CONCLUSIONS: Interventions resulted in significant reduction of confirmed case numbers relative to predicted values based on the SEIR model without intervention. Our findings highlight the effectiveness of social distancing and cloth face coverings in slowing down the spread of severe acute respiratory syndrome coronavirus 2 in NYC.

Era of molecular diagnosis for pathogen identification of unexplained pneumonia, lessons to be learned.

Unexplained pneumonia (UP) caused by a novel coronavirus SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) emerged in China in late December 2019 and has infected more than 9000 cases by 31 January 2020. Shanghai reported the first imported case of COVID-19 (Coronavirus Disease 2019) in 20 January 2020. A combinative approach of real-time RT-PCR, CRISPR-based assay and metagenomic next-generation sequencing (mNGS) were used to diagnose this unexplained pneumonia patient. Real-time RT-PCR and CRISPR-based assay both reported positive. This sample belonged to Betacoronavirus and shared a more than 99% nucleotide (nt) identity with the Wuhan SARS-CoV-2 isolates. We further compared pros and cons of common molecular diagnostics in UP. In this study, we illustrated the importance of combining molecular diagnostics to rule out common pathogens and performed mNGS to obtain unbiased potential pathogen result for the diagnosis of UP.

Optimizing diagnostic strategy for novel coronavirus pneumonia, a multi-center study in Eastern China (preprint)

COVID-19 caused by a novel coronavirus SARS-CoV-2 emerged in Wuhan, Hubei province since December 2019, and caused a rapid outbreak throughout China and globally. Cities outside Hubei are also facing great challenge and require implementing of effective and feasible strategy in precision diagnosing novel coronavirus pneumonia (NCP). We described a multicenter prospective study on diagnostic strategy of suspected NCP patients from January 22nd to February 9th, 2020 in Eastern China cities. Nasopharyngeal swabs were collected from the patients. The epidemiological characteristics, clinical symptoms, laboratory assessments, and computed tomographic (CT) scans were obtained. Pathogen screen were performed including RT-PCR, multiplex PCR, rapid flu antigen tests and mNGS. We enrolled 53 suspected NCP patients, among whom 20 were laboratory-confirmed. Fourteen (70%) and 3 (15%) patients were positive for the first and second SARS-CoV-2 RT-PCR test, respectively. All NCP patients were positive for mNGS. Chest CT images and the symptoms of early stage NCP patients were similar to other viral pneumonia patients. We identified 11 of 20 co-infections in NCP cases, including regular respiratory virus, fungi and bacteria synchronously. Genomic analysis showed that 8 of 10 cases had no mutation in virus genome, while 2 cases had only one single mutation in N gene. Our study discovered that a combination of chest CT, SARS-CoV-2 RT-PCR and multi-plex PCR is recommended in regions outside Hubei province. Co-infection of other pathogens with SARS-CoV-2 exists and should be acknowledged. Repeated sampling, change of specimen type or metagenomics sequencing could further facilitate during critical clinical cases.