Etiological analysis of acute respiratory infections in hospitalized children after the relaxation of COVID-19 non-pharmacological interventions in Quzhou, China (preprint)

Background: Acute respiratory infections (ARIs) can cause morbidity and mortality in children. This study was to determine the characteristics of pathogens in hospitalized children with ARIs after the relaxation of COVID-19 non-pharmacological interventions (NPIs) in Quzhou, China. Methods: Hospitalized children with ARIs were enrolled between May and October 2023, and thirteen common respiratory pathogens were tested by fluorescent quantitative polymerase chain reaction. Mono- and co-infections were assessed, and the association between pathogens and age was explored using restricted cubic spline analysis. Results: A total of 1225 children were included, 820 of them detected one pathogen and 238 of them detected two or more pathogens. Children aged 1-3 years had the highest positive detection rates. The dominant pathogen varied monthly. Mycoplasma pneumoniae (Mp) was the most common pathogen in monoinfection, followed by respiratory syncytial virus (RSV) and human rhinovirus (HRV), while influenza virus was detected at a lower rate. Mp+HRV was the most common combination of coinfections. The detection rates of Mp and HRV were higher in coinfections than in monoinfection, but there was no difference in the detection rate of RSV. In the restricted cubic spline models, a J-shaped association was consistently observed between age and Mp infection, the risk of HRV first increased and then decreased, the risk of RSV was relatively flat until 1.5 years and then decreased raplidly. Conclusion: Our study revealed the epidemiological characteristics of ARIs pathogens after the relaxation of NPIs. There is still a need to enhanced pathogen surveillance, especially for Mp.

Modeling particulate nitrate in China: Current findings and future directions.

Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.

New-Onset Arthritis Following COVID-19 Vaccination: A Systematic Review of Case Reports.

Coronavirus disease 2019 (COVID-19) vaccine has effectively suppressed the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and alleviated its symptoms, but there are also many adverse events. Joint diseases caused by COVID-19 vaccine have been reported in many studies. Some are well-controlled arthritis patients who developed arthritis after COVID-19 vaccination, while others are new-onset joint pain and swelling problems after COVID-19 vaccination. The purpose of this systematic review is to examine the literature reports in existing databases and analyze the incidence of new-onset arthritis after COVID-19 vaccination. We included 31 eligible articles and described 45 patients, ranging in age from 17 to over 90, with more females than males. The majority (84.4%) of patients received the adenovirus vector vaccine (ChAdOx1) and the mRNA-based vaccine (BNT126b2 and mRNA-1273). Most (64.4%) patients developed joint-related symptoms after the first dose of vaccine, and 66.7% developed symptoms within the first week of vaccination. The joint symptoms involved were mainly joint swelling, joint pain, limited range of motion, and so on. A total of 71.1% of the patients involved multiple joints, both large and small; 28.9% of patients involved only a single joint. Some (33.3%) patients were confirmed by imaging, and the most common diagnoses were bursitis and synovitis. Two nonspecific inflammatory markers, erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), were monitored in almost all cases, and all patients showed varying degrees of increase in these two markers. Most of the patients received the treatment of glucocorticoid drugs or nonsteroidal anti-inflammatory drugs (NSAIDs). Clinical symptoms markedly improved in most patients, with 26.7% making a full recovery and no relapse after a few months of follow-up. To determine whether there is a causal relationship between COVID-19 vaccination and the triggering of arthritis, large-scale and well-controlled research studies are needed in the future to verify this relationship and to further study its pathogenesis in detail. Clinicians should raise awareness of this complication with a view to early diagnosis and appropriate treatment.

Multi-criteria decision making for determining best teaching method using fuzzy analytical hierarchy process.

During the outbreak of COVID-19, information technology played a critical role in promoting education all around the world. Online teaching boosts students' learning processes and has a good impact on their learning during the epidemic. Big data technology transforms traditional teaching approaches and learning processes by providing a rich learning resource for diverse teaching elements and improving teachers' teaching techniques. Due to the COVID-19 epidemic, online education spread quickly, and traditional instruction was abruptly switched to online mode, posing a number of issues for students and management. Choosing a decent teaching technique is not an easy option, and it is even more difficult when it comes to selecting the approach. We used the Fuzzy Analytical Hierarchy Process (Fuzzy AHP) method to evaluate four instructional methods based on seven criteria to solve this challenge. Fuzzy AHP is a powerful, simple, and direct way for determining which approach is the most efficient and effective. To simplify the selection process and address the issue of uncertainty, the Fuzzy AHP technique employs the geometric mean method. The Fuzzy AHP approach was found to be efficient and successful in the decision-making process in this study.

Psychotherapy and Follow-Up in Health Care Workers After the COVID-19 Epidemic: A Single Center's Experience.

Objective: The present study aims to analysis the mental health of high-risk health care workers (HHCWs) and low-risk HCWs (LHCWs) who were respectively exposed to COVID-19 wards and non-COVID-19 wards by following up on mental disorders in HCWs in China for 6 months. Methods: A multi-psychological assessment questionnaire was used to follow up on the psychological status of HCWs in the Affiliated Hospital of Xuzhou Medical University in Xuzhou City (a non-core epidemic area) at 6 months after the first evaluation conducted during the COVID-19 epidemic. Based on the risk of exposure to COVID-19 patients, the HCWs were divided into two groups: high-risk HCWs, who worked in COVID-19 wards, and low-risk HCWs, who worked in non-COVID-19 wards. Results: A total of 198 HCWs participated in the study, and 168 questionnaires were selected for evaluation. Among them, 93 (55.4%) were in the HHCW group and 75 (44.5%) were in the LHCW group. Significant differences were observed in salary, profession, and altruistic behavior between the two groups (P < 0.05). There were no significant differences in the anxiety, depression, insomnia, or posttraumatic stress disorder (PTSD) scores between the two groups. Logistic regression revealed that work stress was a major joint risk factor for mental disorders in HCWs. Among all the HCWs, a total of 58 voluntarily participated in psychotherapy; the analysis showed a significant decrease in anxiety, depression, PTSD, work stress, and work risk after attending psychotherapy. There were also significant differences in positive and negative coping styles before and after psychotherapy. Conclusion: In the present follow-up, work stress was the major contributing factor to mental disorders in HCWs. Psychotherapy is helpful in terms of stress management and should be provided to first-line COVID-19 HCWs.

Global evidence of the exposure-lag-response associations between temperature anomalies and food markets

Recent years have witnessed a landmark shift in global food prices due to the frequency of extreme weather events caused by temperature anomalies as well as the overlapping risks of COVID-19. Notably, the threat posed by temperature anomalies has spread beyond agricultural production to all aspects across food supply and demand channels, further amplifying volatility in food markets. Exploring trends in global food prices will give nations early warning signs to ensure the stability of food market. Accordingly, we utilize the Distributed Lag Non-Linear Model (DLNM) to simultaneously establish the exposure-lag-response associations between global temperature anomalies and food price returns in two dimensions: “Anomaly Degree” and “Response Time”. Meanwhile, we also examine the cumulative lagged effects of temperature anomalies in terms of different quantiles and lag times. Several conclusions have been drawn. First, global food price returns will continue to decrease when the average temperature drops or rises slightly. While it turns up once the average temperature rises more than 1.1 °C. Second, major food commodities are more sensitive to temperature changes, and their price returns may also trend in a directional shift at different lags, with the trend in meat price being more particular. Third, food markets are more strongly affected in the case of extreme temperature anomalies. Many uncertainties still exist regarding the impact of climate change on food markets, and our work serves as a valuable reference for international trade regulation as well as the creation of dynamic climate risk hedging strategies.

2D Zn‐Porphyrin‐Based Co(II)‐MOF with 2‐Methylimidazole Sitting Axially on the Paddle–Wheel Units: An Efficient Electrochemiluminescence Bioassay for SARS‐CoV‐2

High electrocatalytic activity with tunable luminescence is crucial for the development of electrochemiluminescence (ECL) luminophores. In this study, a porphyrin‐based heterobimetallic 2D metal organic framework (MOF), [(ZnTCPP)Co2(MeIm)] (1), is successfully self‐assembled from the zinc(II) tetrakis(4‐carboxyphenyl)porphine (ZnTCPP) linker and cobalt(II) ions in the presence of 2‐methylimidazole (MeIm) by a facile one‐pot reaction in methanol at room temperature. On the basis of the experimental results and the theoretical calculations, the MOF 1 contains paddle–wheel [Co2(‐CO2)4] secondary building units (SBUs) axially coordinated by a MeIm ligand, which is very beneficial to the electron transfer between the Co(II) ions and oxygen. Combining the photosensitizers ZnTCPP and the electroactive [Co2(‐CO2)4] SBUs, the 2D MOF 1 possesses an excellent ECL performance, and can be used as a novel ECL probe for rapid nonamplified detection of the RdRp gene of SARS‐CoV‐2 with an extremely low limit of detection (≈30 aM). A novel porphyrin‐based heterobimetallic 2D MOF, [(ZnTCPP)Co2(MeIm)] (1) is constructed to act as an excellent electrochemiluminescence probe for rapid nonamplified detection of SARS‐CoV‐2.

Case report: Green nail syndrome in an epidemic prevention volunteer during the outbreak of the Omicron in Shanghai

Green nail syndrome (GNS) is an infectious disorder characterized by greenish discoloration of the nail plate. Pseudomonas aeruginosa is the most common organism that causes GNS. It is an opportunistic human pathogen that preferentially colonizes moist environments, and thus, it usually affects patients with a history of prolonged exposure to moist environments. Here, we describe a case of GNS in an epidemic prevention volunteer that was caused by wearing personal protective equipment for prolonged durations. The case was reported during the outbreak caused by the SARS-CoV-2 Omicron variant in Shanghai. After receiving information about his condition and proper treatment, the patient was cured.

COVID-19 infection with keratitis as the first clinical manifestation

AIM To report a case which keratitis is the first clinical manifestation of COVID-19 that occurred 3d earlier than the common COVID-19 symptoms. METHODS Regular slit lamp examination, corneal scraping test, and chest computed tomography (CT) were performed for patients with COVID-19 infection. The ophthalmologic treatment included ganciclovir eye drop (50 mg/mL, 6 times/d). The treatment for diarrhea included Guifu Lizhong pills (TID). The antiviral therapy consisted of oseltamivir (75 mg capsule Q12H);therapy preventing bacterial infection consisted of azithromycin (250 mg tablet QD) and moxifloxacin (0.4 g tablet Q12H);and therapy for cough relief and fever prevention consisted of Chinese herbal decoction. RESULTS A 35-year-old male suddenly suffered pain, photophobia, and tears in his right eye for one day without systemic COVID-19 symptoms. Patient was diagnosed with keratitis, which was seemingly different from common keratitis. Ganciclovir eye drop was initiated. The corneal scraping test for COVID-19 was positive. The chest CT images were abnormal confirming the diagnosis of COVID-19 infection. The antiviral and antibacterial therapies were initiated. Chinese herbal therapy was used for cough relief and fever prevention. After roughly two weeks, patient recovered from COVID-19. CONCLUSION A new type of keratitis, atypical keratitis, is a clinical manifestation of COVID-19, and this clinical manifestation could appear 3d earlier than fever and cough. The earlier a COVID-19 clinical manifestation is identified, the earlier can a patient be directed to stay at home, and significantly fewer people would be infected.

Customer sovereignty, algorithmic management, economic precarity and networked support: A Job Demands-Resources analysis of stress and response among Chinese couriers (preprint)

The COVID-19 pandemic has given the global e-commerce market a strong boost, of which China has the largest share and is growing rapidly. Concerns have been raised about intensified work stress and its consequences on health and safety among Chinese couriers. Sociological research of work and occupations has offered important insights into the labour process and politics of the gig economy, although how exactly the workers perceive and respond to technology-driven structural changes remains less clear. We conducted 14 semi-structured interviews with frontline couriers in May-June 2021 in China and interpreted the emerged themes following the Job Demands-Resources (JD-R) model. Four major work-stressor themes were identified: customer sovereignty, algorithmic management, economic precarity and networked support. These work conditions rarely worked alone. Technological, managerial and customer controlling mechanisms reinforced each other and increased work stress. In the absence of adequate organizational support, workers found support and resources through personal networks.

Early detection of circulating tumor DNA and successful treatment with osimertinib in thr790met-positive leptomeningeal metastatic lung cancer: A case report.

BACKGROUND: Patients diagnosed with non-small-cell lung cancer with activated epidermal growth factor receptor mutations are more likely to develop leptomeningeal (LM) metastasis than other types of lung cancers and have a poor prognosis. Early diagnosis and effective treatment of leptomeningeal carcinoma can improve the prognosis. CASE SUMMARY: A 55-year-old female with a progressive headache and vomiting for one month was admitted to Peking University First Hospital. She was diagnosed with lung adenocarcinoma with osseous metastasis 10 months prior to admittance. epidermal growth factor receptor (EGFR) mutation was detected by genomic examination, so she was first treated with gefitinib for 10 months before acquiring resistance. Cell-free cerebrospinal fluid (CSF) circulating tumor DNA detection by next-generation sequencing was conducted and indicated the EGFR-Thr790Met mutation, while biopsy and cytology from the patient's CSF and the first enhanced cranial magnetic resonance imaging (MRI) showed no positive findings. A month later, the enhanced MRI showed linear leptomeningeal enhancement, and the cytology and biochemical examination in CSF remained negative. Therefore, osimertinib (80 mg/d) was initiated as a second-line treatment, resulting in a good response within a month. CONCLUSION: This report suggests clinical benefit of osimertinib in LM patients with positive detection of the EGFR-Thr790Met mutation in CSF and proposes that the positive findings of CSF circulating tumor DNA as a liquid biopsy technology based on the detection of cancer-associated gene mutations may appear earlier than the imaging and CSF findings and may thus be helpful for therapy. Moreover, the routine screening of chest CT with the novel coronavirus may provide unexpected benefits.

Dust events affect the occurrence of influenza: A case-crossover study in an arid city of China (preprint)

Background Air aerosol is believed to be an important pathway for infectious disease transmission like COVID-19 as well as influenza. Therefore, we hypothesized that there might be a strong association between dust events and influenza, especially in semi-arid areas. This study aims to explore the effects of ambient particulate matter (PM) and dust events on laboratory-confirmed influenza cases in a semi-arid city.Methods A descriptive analysis of daily laboratory-confirmed influenza (influenza) cases, PM (PM10 and PM2.5), meteorological parameters and dust events were conducted from 2014 to 2019 in Lanzhou, China. The Case-crossover design combined with conditional Poisson regression models was used to estimate the lagging effects of PM and dust events on influenza. In addition, a hierarchical model was used to quantitatively evaluate the interactive effect of PM with ambient temperature and absolute humidity on influenza.Results We found that PM and dust events had a significant effect on influenza. The effects of PM10 and PM2.5 on influenza became stronger as the cumulative lag days increased, the greatest estimated relative risks (RRs) were 1.018 (1.011,1.024) and 1.06 1(1.034,1.087), respectively. Compared with the non-dust days, the effects of dust events with duration ≥ 1 day and with duration ≥ 2 days on influenza were the strongest at lag0 day, with the estimated RRs of 1.245 (95% CI: 1.061–1.463) and 1.483 (95% CI: 1.232–1.784), respectively. Subgroup analysis showed that pre-school children and school-aged children were more sensitive to PM and dust events exposure. Besides, we also found the low humidity and temperature had an interaction with PM, which could aggravate the risk of influenza.Conclusions Ambient PM and dust events exposure may increase the risk of laboratory-confirmed influenza, and the risk of laboratory-confirmed influenza increased with the dust events duration. These findings will provide additional epidemiological evidence for future influenza prevention and environmental protection.

Prognostic Value of Coronary CT Angiography-Derived Fractional Flow Reserve in Non-obstructive Coronary Artery Disease: A Prospective Multicenter Observational Study

Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Myocardial ischemia may occur in patients with normal or non-obstructive CAD on invasive coronary angiography (ICA). The comprehensive evaluation of coronary CT angiography (CCTA) integrated with fractional flow reserve derived from CCTA (CT-FFR) to CAD may be essential to improve the outcomes of patients with non-obstructive CAD. China CT-FFR Study-2 (ChiCTR2000031410) is a large-scale prospective, observational study in 29 medical centers in China. The primary purpose is to uncover the relationship between the CCTA findings (including CT-FFR) and the outcome of patients with non-obstructive CAD. At least 10,000 patients with non-obstructive CAD but without previous revascularization will be enrolled. A 5-year follow-up will be performed. The primary endpoint is the occurrence of major adverse cardiovascular events (MACE), including all-cause mortality, non-fatal myocardial infarct, unplanned revascularization, and hospitalization for unstable angina. Clinical characteristics, laboratory and imaging examination results will be collected to analyze their prognostic value.

Features of capsule endoscopy in COVID-19 patients with a six-month follow-up: A prospective observational study.

Recently, the coronavirus disease 2019 (COVID-19) has caused a global pandemic. Several studies indicate that the digestive system can also be affected by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Therefore, patients with digestive symptoms should have a capsule endoscopy (CE). COVID-19 patients with gastrointestinal (GI) symptoms who underwent CE were recruited from March 2020 to April 2020. We collected patients' data and performed a prospective follow-up study for 6 months. All 11 COVID-19 cases with GI symptoms who underwent CE presented gastritis. Eight cases (72.7%) had intestinal mucosa inflammation. Among them, two cases showed intestinal ulcers or erosions. Moreover, two cases displayed colonic mucositis. One case was lost during follow-up. At 3-6 months after hospital discharge, five patients underwent CE again, presenting gastrointestinal lesions. Five of the 10 cases had GI symptoms, such as abdominal pain, diarrhea, constipation, and others. Among these five cases, the GI symptoms of three patients disappeared at the last follow-up and two patients still presented diarrhea symptoms. Overall, we observed damaged digestive tract mucosa that could be caused by SARS-CoV-2. Moreover, after discharge, some patients still presented intestinal lesions and GI symptoms.

UMLF-COVID: an unsupervised meta-learning model specifically designed to identify X-ray images of COVID-19 patients.

BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international researchers. Recently, many deep learning-based Computed Tomography (CT) image/X-ray image fast screening models for potential COVID-19 patients have been proposed. However, the existing models still have two main problems. First, most of the existing supervised models are based on pre-trained model parameters. The pre-training model needs to be constructed on a dataset with features similar to those in COVID-19 X-ray images, which limits the construction and use of the model. Second, the number of categories based on the X-ray dataset of COVID-19 and other pneumonia patients is usually imbalanced. In addition, the quality is difficult to distinguish, leading to non-ideal results with the existing model in the multi-class classification COVID-19 recognition task. Moreover, no researchers have proposed a COVID-19 X-ray image learning model based on unsupervised meta-learning. METHODS: This paper first constructed an unsupervised meta-learning model for fast screening of COVID-19 patients (UMLF-COVID). This model does not require a pre-trained model, which solves the limitation problem of model construction, and the proposed unsupervised meta-learning framework solves the problem of sample imbalance and sample quality. RESULTS: The UMLF-COVID model is tested on two real datasets, each of which builds a three-category and four-category model. And the experimental results show that the accuracy of the UMLF-COVID model is 3-10% higher than that of the existing models. CONCLUSION: In summary, we believe that the UMLF-COVID model is a good complement to COVID-19 X-ray fast screening models.

Prevalence of and risk factors for burnout and occupational stress among couriers: A systematic review (preprint)

Objective To estimate the prevalence of burnout and occupational stress (OS) among couriers and to identify the main risk factors. Method We followed PRISMA guidelines to search studies published in English and Chinese databases before February 2022. Results The search yielded 15 (7 English and 8 Chinese) papers, 12 of which studied Chinese couriers, and three studied French, Israeli and Malaysian couriers. Twelve studies reported OS using various validated measurement tools, and six reported burnout using adapted versions of Maslach Burnout Inventory. Only four included studies suggested cut-off points to define the condition, hence we used the midpoint of the scales to estimate the prevalence (the proportion of the cases that were above the midpoint). The estimated prevalence of burnout (or a dimension of burnout) among couriers ranged from 20% to 73% (median=33%). The prevalence of OS (or a dimension of OS) ranged from 7% to 90% (median=40%). Twelve studies reported risk factors for burnout or OS; the main ones were physical demands, customer behaviour and a range of working and employment conditions, such as employment precarity and financial insecurity. Job resources (i.e. social support and decision latitude) and organizational support had mitigating effects. Conclusions Burnout and OS are relatively high among couriers. Interventions to prevent or reduce burnout in this occupation are currently limited. The use of platform technology to shift risks, intensify work and tighten managerial controls could be a potential work-related stressor for app-based couriers but remains a knowledge gap.

The Bilingual Home Language Boost Through the Lens of the COVID-19 Pandemic.

Usage-based accounts of language acquisition suggest that bilingual language proficiency is dynamic and susceptible to changes in language use. The COVID-19 pandemic led to unprecedented modifications in the language learning environment of developing bilinguals. Drawing on this unique opportunity, we analyzed existing data of two matched groups of Mandarin-English bilingual children (ages 4 to 8 years, n = 38), one tested before (pre-COVID group) and the other during (COVID group) the pandemic. The dataset comprises responses to a language environment questionnaire, and scores on a sentence comprehension task and a sentence recall task in the bilinguals' two languages. Questionnaire data revealed a richer Mandarin language environment for children in the COVID group compared to peers in the pre-COVID group. On both comprehension and production tasks, the two groups performed comparably in English but the COVID group showed better performance in Mandarin than the pre-COVID group. Within the pre-COVID group, English was stronger than Mandarin in both comprehension and production. Within the COVID group, the two languages were balanced in comprehension and Mandarin was stronger than English in production. Moreover, language use variables were correlated with production performance in both languages. These patterns illustrate the intimate relationships between language use and bilingual language proficiency through the lens of COVID-19 induced language environment modification.

Viewpoint of a WHO Advisory Group Tasked to Consider Establishing a Closely-monitored Challenge Model of Coronavirus Disease 2019 (COVID-19) in Healthy Volunteers.

WHO convened an Advisory Group (AG) to consider the feasibility, potential value, and limitations of establishing a closely-monitored challenge model of experimental severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) in healthy adult volunteers. The AG included experts in design, establishment, and performance of challenges. This report summarizes issues that render a COVID-19 model daunting to establish (the potential of SARS-CoV-2 to cause severe/fatal illness, its high transmissibility, and lack of a "rescue treatment" to prevent progression from mild/moderate to severe clinical illness) and it proffers prudent strategies for stepwise model development, challenge virus selection, guidelines for manufacturing challenge doses, and ways to contain SARS-CoV-2 and prevent transmission to household/community contacts. A COVID-19 model could demonstrate protection against virus shedding and/or illness induced by prior SARS-CoV-2 challenge or vaccination. A limitation of the model is that vaccine efficacy in experimentally challenged healthy young adults cannot per se be extrapolated to predict efficacy in elderly/high-risk adults.

Safe reopening of university campuses is possible with COVID-19 vaccination (preprint)

We construct an agent-based SEIR model to simulate COVID-19 spread at a 16000-student mostly non-residential urban university during the Fall 2021 Semester. We find that mRNA vaccine coverage above 80% makes it possible to safely reopen to in-person instruction. If vaccine coverage is 100%, then our model indicates that facemask use is not necessary. Our simulations with vaccine coverage below 70% exhibit a right-skew for total infections over the semester, which suggests that high levels of infection are not exceedingly rare with campus social connections the main transmission route. Less effective vaccines or incidence of new variants may require additional intervention such as screening testing to reopen safely.

Effects of group psychological intervention combined with pulmonary rehabilitation exercises on anxiety and sleep disorders in patients with mild coronavirus disease 2019 (COVID-19) infections in a Fangcang hospital.

Fangcang hospitals, as tentative hospitals built to treat a huge turnover of patients with mild coronavirus disease 2019 (COVID-19) infections, have played a pivotal role to slow down the pandemic spread in China in 2020. However, anxiety and sleep disorders remain tough to address during the treatments. In this study, group psychological intervention in combination with pulmonary rehabilitation exercises were conducted in the trial group for the patients with mild COVID-19 infections in a Fangcang Hospital to mitigate the patients' anxiety and sleep disorders, while conventional nursing methods were done in the control group, with 70 randomly picked patients in each group. Effects were assessed through questionnaire method using state anxiety questionnaire (SAI) and Pittsburgh sleep quality index scale (PQSI) rating investigation. Results showed that both SAI and PSQI scores of the trial group were significantly lower than those of the control group (P < 0.05). The SAI scores of the trial group and the control group were 38.5 ± 13.2 and 45.8 ± 10.4 points (t = 3.600, P < 0.001), respectively, and the PSQI scores were 5.6 ± 3.0 and 7.1 ± 3.0 points (t = 2.982, P < 0.01), respectively. Our methods have significant advantages over conventional nursing methods to mitigate anxiety and sleep disorders for the patients with mild COVID-19 infections in the Fangcang Hospital.