A review of current effective COVID-19 testing methods and quality control.

COVID-19 is a highly infectious disease caused by the SARS-CoV-2 virus, which primarily affects the respiratory system and can lead to severe illness. The virus is extremely contagious, early and accurate diagnosis of SARS-CoV-2 is crucial to contain its spread, to provide prompt treatment, and to prevent complications. Currently, the reverse transcriptase polymerase chain reaction (RT-PCR) is considered to be the gold standard for detecting COVID-19 in its early stages. In addition, loop-mediated isothermal amplification (LMAP), clustering rule interval short palindromic repeats (CRISPR), colloidal gold immunochromatographic assay (GICA), computed tomography (CT), and electrochemical sensors are also common tests. However, these different methods vary greatly in terms of their detection efficiency, specificity, accuracy, sensitivity, cost, and throughput. Besides, most of the current detection methods are conducted in central hospitals and laboratories, which is a great challenge for remote and underdeveloped areas. Therefore, it is essential to review the advantages and disadvantages of different COVID-19 detection methods, as well as the technology that can enhance detection efficiency and improve detection quality in greater details.

The Actual Status of Hospitals as COVID-19 Vaccination Clinics in China and Safety Monitoring of Inactivated Vaccine: A Cross-Sectional Study.

BACKGROUND: The outbreak has had a devastating impact, and efforts are underway to speed up vaccination. The study's objective was to describe the clinical characteristics of the coronavirus disease 2019 (COVID-19) vaccination clinic in the Second People's Hospital of Fujian Province, China. Meanwhile, we monitored all the vaccine recipients to evaluate adverse reactions. METHODS: A cross-sectional study was done at the COVID-19 Vaccination Clinic, the Second People's Hospital of Fujian Province, China. We systematically collected Clinical data from the COVID-19 vaccination clinic between March 11 and November 11, 2021, including the type of vaccine, number of doses, gender, age, educational level, occupational category, adverse reactions, etc. Investigators will contact vaccine recipients by means of phone call or WeChat message to record the negative responses. Last, this report covers data through 8 mo, so it will be better to Evaluate the Safety of 2 inactivated COVID-19 vaccines from China (BBIBP-CorV [Beijing Institute of Biological Products, Beijing, China] and CoronaVac [Sinovac Life Sciences, Beijing, China]). RESULTS: The results indicated that the Second People's Hospital of Fujian Province received a total of 64,602 COVID-19 vaccines from March 11 to November 11, 2021, including 34,331 (53.14%) first doses, 29,245 (45.27%) second doses, and 1026 (1.59%) third doses. This study found the highest proportion in other personnel (38.69% at the first dose, 38.75% at the second dose, and 2.44% at the third dose), who were mainly retirees. People with higher levels of education are more likely to be vaccinated against COVID-19 during the early stages of vaccine rollout. In terms of age stratification, the highest proportion was found among people aged 18-49 (BBIBP-CorV: first dose 61%, second dose 62.6%, and third dose 76.8%; CoronaVac: first dose 66.1%, double dose 63.6%, and third dose 75.5%), followed by those over 60. The common adverse reactions were mainly local and systemic, and there were some differences between the 2 inactivated vaccines (P < 0.05). CONCLUSIONS: This is the first study to analyze the actual status of hospitals as COVID-19 vaccination clinics in China. The hospital has focused on vaccinating citizens and the initial rollout of vaccines to ensure any safety issues are identified. More citizens are willing to vaccinate in hospitals because of the uncertain safety of the available vaccines and adverse reactions. The good news is that vaccine-related severe adverse events have not been found in the hospital vaccination clinic. The Safety of BBIBP-CorV and CoronaVac is relatively high.

Knowledge graph of wastewater-based epidemiology development: A data-driven analysis based on research topics and trends.

Wastewater-based epidemiology (WBE) has contributed significantly to the monitoring of drug use and transmission of viruses that has been published in numerous research papers. In this paper, we used LitStraw, a self-developed text extraction tool, to extract, analyze, and construct knowledge graphs from nearly 900 related papers in PDF format collected in Web of Science from 2000 to 2021 to analyze the research hotspots and development trends of WBE. The results showed a growing number of WBE publications in multidisciplinary cross-collaboration, with more publications and close collaboration between the USA, Australia, China, and European countries. The keywords of illicit drugs and pharmaceuticals still maintain research hotness, but the specific research hotspots change significantly, among which the research hotspots of new psychoactive substances, biomarkers, and stability show an increasing trend. In addition, judging the spread of COVID-19 by the presence of SARS-CoV-2 RNA in sewage has become the focus since 2020. This work can show the development of WBE more clearly by constructing a knowledge graph and also provide new ideas for the paper mining analysis methods in different fields.

IL-4 receptor blockade is a global repressor of naïve B cell development and responses in a dupilumab-treated patient.

Here, we report a case of atopic dermatitis (AD) in a patient who received biweekly doses of dupilumab, an antibody against the IL-4 receptor α chain (IL-4Rα). Single cell RNA-sequencing showed that naïve B cells expressed the highest levels of IL4R compared to other B cell subpopulations. Compared to controls, the dupilumab-treated patient exhibited diminished percentages of IL4R+IGHD+ naïve B cells and down-regulation of IL4R, FCER2 (CD23), and IGHD. Dupilumab treatment resulted in upregulation of genes associated with apoptosis and inhibition of B cell receptor signaling and down-regulation of class-switch and memory B cell development genes. The dupilumab-treated patient exhibited a rapid decline in COVID-19 anti-spike and anti-receptor binding domain antibodies between 4 and 8 and 11 months post COVID-19 vaccination. Our data suggest that intact and persistent IL-4 signaling is necessary for maintaining robust survival and development of naïve B cells, and maintaining a long term vaccine response.

Associations of BMI with COVID-19 vaccine uptake, vaccine effectiveness, and risk of severe COVID-19 outcomes after vaccination in England: a population-based cohort study.

BACKGROUND: A high BMI has been associated with a reduced immune response to vaccination against influenza. We aimed to investigate the association between BMI and COVID-19 vaccine uptake, vaccine effectiveness, and risk of severe COVID-19 outcomes after vaccination by using a large, representative population-based cohort from England. METHODS: In this population-based cohort study, we used the QResearch database of general practice records and included patients aged 18 years or older who were registered at a practice that was part of the database in England between Dec 8, 2020 (date of the first vaccination in the UK), to Nov 17, 2021, with available data on BMI. Uptake was calculated as the proportion of people with zero, one, two, or three doses of the vaccine across BMI categories. Effectiveness was assessed through a nested matched case-control design to estimate odds ratios (OR) for severe COVID-19 outcomes (ie, admission to hospital or death) in people who had been vaccinated versus those who had not, considering vaccine dose and time periods since vaccination. Vaccine effectiveness against infection with SARS-CoV-2 was also investigated. Multivariable Cox proportional hazard models estimated the risk of severe COVID-19 outcomes associated with BMI (reference BMI 23 kg/m2) after vaccination. FINDINGS: Among 9 171 524 participants (mean age 52 [SD 19] years; BMI 26·7 [5·6] kg/m2), 566 461 tested positive for SARS-CoV-2 during follow-up, of whom 32 808 were admitted to hospital and 14 389 died. Of the total study sample, 19·2% (1 758 689) were unvaccinated, 3·1% (287 246) had one vaccine dose, 52·6% (4 828 327) had two doses, and 25·0% (2 297 262) had three doses. In people aged 40 years and older, uptake of two or three vaccine doses was more than 80% among people with overweight or obesity, which was slightly lower in people with underweight (70-83%). Although significant heterogeneity was found across BMI groups, protection against severe COVID-19 disease (comparing people who were vaccinated vs those who were not) was high after 14 days or more from the second dose for hospital admission (underweight: OR 0·51 [95% CI 0·41-0·63]; healthy weight: 0·34 [0·32-0·36]; overweight: 0·32 [0·30-0·34]; and obesity: 0·32 [0·30-0·34]) and death (underweight: 0·60 [0·36-0·98]; healthy weight: 0·39 [0·33-0·47]; overweight: 0·30 [0·25-0·35]; and obesity: 0·26 [0·22-0·30]). In the vaccinated cohort, there were significant linear associations between BMI and COVID-19 hospitalisation and death after the first dose, and J-shaped associations after the second dose. INTERPRETATION: Using BMI categories, there is evidence of protection against severe COVID-19 in people with overweight or obesity who have been vaccinated, which was of a similar magnitude to that of people of healthy weight. Vaccine effectiveness was slightly lower in people with underweight, in whom vaccine uptake was also the lowest for all ages. In the vaccinated cohort, there were increased risks of severe COVID-19 outcomes for people with underweight or obesity compared with the vaccinated population with a healthy weight. These results suggest the need for targeted efforts to increase uptake in people with low BMI (<18·5 kg/m2), in whom uptake is lower and vaccine effectiveness seems to be reduced. Strategies to achieve and maintain a healthy weight should be prioritised at the population level, which could help reduce the burden of COVID-19 disease. FUNDING: UK Research and Innovation and National Institute for Health Research Oxford Biomedical Research Centre.

An agile discovery method of drugs for infectious diseases and tentative exploration of its application in drug discovery for COVID-19

OBJECTIVE: To establish an agile discovery method of drugs or natural products for epidemics (aCODE) for the development of anti-infectious disease drugs. METHODS: Five infectious diseases (HIV infection, human influenza, Paramyxoviridae infections, bacterial infections and whooping cough) involving more than 40 drugs approved by the United States Food and Drug Administration (FDA) were selected. An experimental group and two negative control groups (A and B) for each disease were set up. The experimental group randomly selected (500 times) M FDA-approved indications as seed drugs for the disease, while negative control group A used all FDA-approved infectious drugs for non-current diseases instead of seed drugs, and negative control group B used all non-infectious disease drugs for non-infectious diseases instead of seed drugs. M ranged from 2 to 20, the target gene information of the seed drug was input, and the feature vector of the seed drug set was calculated. Candidate compounds were predicted through similarity search of drug feature vectors. The size of the inter- section between the predicted drug and the positive set of drugs approved by the FDA for the disease, and the significance of the intersection were calculated. After the establishment of the aCODE method, four drugs (lopinavir, ribavirin, ritonavir and chloroquine) were selected as seed drugs for COVlD-19 to predict the composition of natural products. Using natural products with known anti-coronavirus activities as the verification set, the significance of the prediction results was calculated. RESULTS: In the case of the five infectious diseases, the proportion of positive drugs in the results of prediction in the experimental group increased with the number of seed drugs, while the positive rate of the two negative control groups remained basically unchanged or somewhat trended down. The aCODE method, when applied to COVlD-19 drug screening, could effectively predict drugs with potential anti-SARS-Cov-2 activity (P=0.0046). CONCLUSION: With the aCODE method, the more the seed drugs, the more accu- rate the characteristics of the disease-related gene modules calculated from this group of seed drugs, and the higher the proportion of positive drugs in the prediction result. This method may contribute to the discovery of drugs for COVID-19.

Associations between body composition, fat distribution and metabolic consequences of excess adiposity with severe COVID-19 outcomes: observational study and Mendelian randomisation analysis.

BACKGROUND: Higher body mass index (BMI) and metabolic consequences of excess weight are associated with increased risk of severe COVID-19, though their mediating pathway is unclear. METHODS: A prospective cohort study included 435,504 UK Biobank participants. A two-sample Mendelian randomisation (MR) study used the COVID-19 Host Genetics Initiative in 1.6 million participants. We examined associations of total adiposity, body composition, fat distribution and metabolic consequences of excess weight, particularly type 2 diabetes, with incidence and severity of COVID-19, assessed by test positivity, hospital admission, intensive care unit (ICU) admission and death. RESULTS: BMI and body fat were associated with COVID-19 in the observational and MR analyses but muscle mass was not. The observational study suggested the association with central fat distribution was stronger than for BMI, but there was little evidence from the MR analyses than this was causal. There was evidence that strong associations of metabolic consequences with COVID-19 outcomes in observational but not MR analyses. Type 2 diabetes was strongly associated with COVID-19 in observational but not MR analyses. In adjusted models, the observational analysis showed that the association of BMI with COVID-19 diminished, while central fat distribution and metabolic consequences of excess weight remained strongly associated. In contrast, MR showed the reverse, with only BMI retaining a direct effect on COVID-19. CONCLUSIONS: Excess total adiposity is probably casually associated with severe COVID-19. Mendelian randomisation data do not support causality for the observed associations of central fat distribution or metabolic consequences of excess adiposity with COVID-19.

Robust Mutation Profiling of SARS-CoV-2 Variants from Multiple Raw Illumina Sequencing Data with Cloud Workflow.

Several variants of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are emerging all over the world. Variant surveillance from genome sequencing has become crucial to determine if mutations in these variants are rendering the virus more infectious, potent, or resistant to existing vaccines and therapeutics. Meanwhile, analyzing many raw sequencing data repeatedly with currently available code-based bioinformatics tools is tremendously challenging to be implemented in this unprecedented pandemic time due to the fact of limited experts and computational resources. Therefore, in order to hasten variant surveillance efforts, we developed an installation-free cloud workflow for robust mutation profiling of SARS-CoV-2 variants from multiple Illumina sequencing data. Herein, 55 raw sequencing data representing four early SARS-CoV-2 variants of concern (Alpha, Beta, Gamma, and Delta) from an open-access database were used to test our workflow performance. As a result, our workflow could automatically identify mutated sites of the variants along with reliable annotation of the protein-coding genes at cost-effective and timely manner for all by harnessing parallel cloud computing in one execution under resource-limitation settings. In addition, our workflow can also generate a consensus genome sequence which can be shared with others in public data repositories to support global variant surveillance efforts.

Association between smoking, e-cigarette use and severe COVID-19: a cohort study.

BACKGROUND: Smoking is a risk factor for most respiratory infections, but it may protect against SARS-CoV-2 infection. The objective was to assess whether smoking and e-cigarette use were associated with severe COVID-19. METHODS: This cohort ran from 24 January 2020 until 30 April 2020 at the height of the first wave of the SARS-CoV-2 epidemic in England. It comprised 7 869 534 people representative of the population of England with smoking status, demographic factors and diseases recorded by general practitioners in the medical records, which were linked to hospital and death data. The outcomes were COVID-19-associated hospitalization, intensive care unit (ICU) admission and death. The associations between smoking and the outcomes were assessed with Cox proportional hazards models, with sequential adjustment for confounding variables and indirect causal factors (body mass index and smoking-related disease). RESULTS: Compared with never smokers, people currently smoking were at lower risk of COVID-19 hospitalization, adjusted hazard ratios (HRs) were 0.64 (95% confidence intervals 0.60 to 0.69) for <10 cigarettes/day, 0.49 (0.41 to 0.59) for 10-19 cigarettes/day, and 0.61 (0.49 to 0.74) for ≥20 cigarettes/day. For ICU admission, the corresponding HRs were 0.31 (0.24 to 0.40), 0.15 (0.06 to 0.36), and 0.35 (0.17 to 0.74) and death were: 0.79 (0.70 to 0.89), 0.66 (0.48 to 0.90), and 0.77 (0.54 to 1.09) respectively. Former smokers were at higher risk of severe COVID-19: HRs: 1.07 (1.03 to 1.11) for hospitalization, 1.17 (1.04 to 1.31) for ICU admission, and 1.17 (1.10 to 1.24) for death. All-cause mortality was higher for current smoking than never smoking, HR 1.42 (1.36 to 1.48). Among e-cigarette users, the adjusted HR for e-cigarette use and hospitalization with COVID-19 was 1.06 (0.88 to 1.28), for ICU admission was 1.04 (0.57 to 1.89, and for death was 1.12 (0.81 to 1.55). CONCLUSIONS: Current smoking was associated with a reduced risk of severe COVID-19 but the association with e-cigarette use was unclear. All-cause mortality remained higher despite this possible reduction in death from COVID-19 during an epidemic of SARS-CoV-2. Findings support investigating possible protective mechanisms of smoking for SARS-CoV-2 infection, including the ongoing trials of nicotine to treat COVID-19.

Orchestrating an Optimized Next-Generation Sequencing-Based Cloud Workflow for Robust Viral Identification during Pandemics.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has recently become a novel pandemic event following the swine flu that occurred in 2009, which was caused by the influenza A virus (H1N1 subtype). The accurate identification of the huge number of samples during a pandemic still remains a challenge. In this study, we integrate two technologies, next-generation sequencing and cloud computing, into an optimized workflow version that uses a specific identification algorithm on the designated cloud platform. We use 182 samples (92 for COVID-19 and 90 for swine flu) with short-read sequencing data from two open-access datasets to represent each pandemic and evaluate our workflow performance based on an index specifically created for SARS-CoV-2 or H1N1. Results show that our workflow could differentiate cases between the two pandemics with a higher accuracy depending on the index used, especially when the index that exclusively represented each dataset was used. Our workflow substantially outperforms the original complete identification workflow available on the same platform in terms of time and cost by preserving essential tools internally. Our workflow can serve as a powerful tool for the robust identification of cases and, thus, aid in controlling the current and future pandemics.

Association between pre-existing respiratory disease and its treatment, and severe COVID-19: a population cohort study.

BACKGROUND: Previous studies suggested that the prevalence of chronic respiratory disease in patients hospitalised with COVID-19 was lower than its prevalence in the general population. The aim of this study was to assess whether chronic lung disease or use of inhaled corticosteroids (ICS) affects the risk of contracting severe COVID-19. METHODS: In this population cohort study, records from 1205 general practices in England that contribute to the QResearch database were linked to Public Health England's database of SARS-CoV-2 testing and English hospital admissions, intensive care unit (ICU) admissions, and deaths for COVID-19. All patients aged 20 years and older who were registered with one of the 1205 general practices on Jan 24, 2020, were included in this study. With Cox regression, we examined the risks of COVID-19-related hospitalisation, admission to ICU, and death in relation to respiratory disease and use of ICS, adjusting for demographic and socioeconomic status and comorbidities associated with severe COVID-19. FINDINGS: Between Jan 24 and April 30, 2020, 8 256 161 people were included in the cohort and observed, of whom 14 479 (0·2%) were admitted to hospital with COVID-19, 1542 (<0·1%) were admitted to ICU, and 5956 (0·1%) died. People with some respiratory diseases were at an increased risk of hospitalisation (chronic obstructive pulmonary disease [COPD] hazard ratio [HR] 1·54 [95% CI 1·45-1·63], asthma 1·18 [1·13-1·24], severe asthma 1·29 [1·22-1·37; people on three or more current asthma medications], bronchiectasis 1·34 [1·20-1·50], sarcoidosis 1·36 [1·10-1·68], extrinsic allergic alveolitis 1·35 [0·82-2·21], idiopathic pulmonary fibrosis 1·59 [1·30-1·95], other interstitial lung disease 1·66 [1·30-2·12], and lung cancer 2·24 [1·89-2·65]) and death (COPD 1·54 [1·42-1·67], asthma 0·99 [0·91-1·07], severe asthma 1·08 [0·98-1·19], bronchiectasis 1·12 [0·94-1·33], sarcoidosis 1·41 [0·99-1·99), extrinsic allergic alveolitis 1·56 [0·78-3·13], idiopathic pulmonary fibrosis 1·47 [1·12-1·92], other interstitial lung disease 2·05 [1·49-2·81], and lung cancer 1·77 [1·37-2·29]) due to COVID-19 compared with those without these diseases. Admission to ICU was rare, but the HR for people with asthma was 1·08 (0·93-1·25) and severe asthma was 1·30 (1·08-1·58). In a post-hoc analysis, relative risks of severe COVID-19 in people with respiratory disease were similar before and after shielding was introduced on March 23, 2020. In another post-hoc analysis, people with two or more prescriptions for ICS in the 150 days before study start were at a slightly higher risk of severe COVID-19 compared with all other individuals (ie, no or one ICS prescription): HR 1·13 (1·03-1·23) for hospitalisation, 1·63 (1·18-2·24) for ICU admission, and 1·15 (1·01-1·31) for death. INTERPRETATION: The risk of severe COVID-19 in people with asthma is relatively small. People with COPD and interstitial lung disease appear to have a modestly increased risk of severe disease, but their risk of death from COVID-19 at the height of the epidemic was mostly far lower than the ordinary risk of death from any cause. Use of inhaled steroids might be associated with a modestly increased risk of severe COVID-19. FUNDING: National Institute for Health Research Oxford Biomedical Research Centre and the Wellcome Trust.

Associations between body-mass index and COVID-19 severity in 6·9 million people in England: a prospective, community-based, cohort study.

BACKGROUND: Obesity is a major risk factor for adverse outcomes after infection with SARS-CoV-2. We aimed to examine this association, including interactions with demographic and behavioural characteristics, type 2 diabetes, and other health conditions. METHODS: In this prospective, community-based, cohort study, we used de-identified patient-level data from the QResearch database of general practices in England, UK. We extracted data for patients aged 20 years and older who were registered at a practice eligible for inclusion in the QResearch database between Jan 24, 2020 (date of the first recorded infection in the UK) and April 30, 2020, and with available data on BMI. Data extracted included demographic, clinical, clinical values linked with Public Health England's database of positive SARS-CoV-2 test results, and death certificates from the Office of National Statistics. Outcomes, as a proxy measure of severe COVID-19, were admission to hospital, admission to an intensive care unit (ICU), and death due to COVID-19. We used Cox proportional hazard models to estimate the risk of severe COVID-19, sequentially adjusting for demographic characteristics, behavioural factors, and comorbidities. FINDINGS: Among 6 910 695 eligible individuals (mean BMI 26·78 kg/m2 [SD 5·59]), 13 503 (0·20%) were admitted to hospital, 1601 (0·02%) to an ICU, and 5479 (0·08%) died after a positive test for SARS-CoV-2. We found J-shaped associations between BMI and admission to hospital due to COVID-19 (adjusted hazard ratio [HR] per kg/m2 from the nadir at BMI of 23 kg/m2 of 1·05 [95% CI 1·05-1·05]) and death (1·04 [1·04-1·05]), and a linear association across the whole BMI range with ICU admission (1·10 [1·09-1·10]). We found a significant interaction between BMI and age and ethnicity, with higher HR per kg/m2 above BMI 23 kg/m2 for younger people (adjusted HR per kg/m2 above BMI 23 kg/m2 for hospital admission 1·09 [95% CI 1·08-1·10] in 20-39 years age group vs 80-100 years group 1·01 [1·00-1·02]) and Black people than White people (1·07 [1·06-1·08] vs 1·04 [1·04-1·05]). The risk of admission to hospital and ICU due to COVID-19 associated with unit increase in BMI was slightly lower in people with type 2 diabetes, hypertension, and cardiovascular disease than in those without these morbidities. INTERPRETATION: At a BMI of more than 23 kg/m2, we found a linear increase in risk of severe COVID-19 leading to admission to hospital and death, and a linear increase in admission to an ICU across the whole BMI range, which is not attributable to excess risks of related diseases. The relative risk due to increasing BMI is particularly notable people younger than 40 years and of Black ethnicity. FUNDING: NIHR Oxford Biomedical Research Centre.

International policies and challenges on the legalization of traditional medicine/herbal medicines in the fight against COVID-19.

The coronavirus disease 2019 (COVID-19) has now rapidly spread around the world, causing an outbreak of acute infectious pneumonia. To develop effective and safe therapies for the prevention and treatment of COVID-19 has become the major global public health concern. Traditional medicine (TM)/herbal medicines (HMs) have been used to treat multiple epidemics in human history, which brings hope for the fight against COVID-19 in some areas. For example, in China, India, and South Korea with traditional medication history and theory, the governments issued a series of guidelines to support TM/HMs in the medication of COVID-19. In contrast, other countries e.g. North American and European governments are typically silent on these practices, unless to warn of possible harm and overselling. Such difference is due to the discrepancy in culture, history and philosophical views of health care and medication, as well as unharmonized policies and standards in the regulation and legalization of TM/HMs among different areas. Herein, we reviewed the responses and scientific researches from seven selected countries on the policies and legalization of TM/HMs to treat COVID-19, and also analyzed the major challenges and concerns to utilize the traditional knowledge and resource.

Protocol for a systematic review and meta-analysis of respiratory rehabilitation following intensive care unit discharge for COVID-19 survivors.

INTRODUCTION: Both physical and mental disorders may be exacerbated in patients with COVID-19 due to the experience of receiving intensive care; undergoing prolonged mechanical ventilation, sedation, proning and paralysis. Pulmonary rehabilitation is aimed to improve dyspnoea, relieve anxiety and depression, reduce the incidence of related complications, as well as prevent and improve dysfunction. However, the impact of respiratory rehabilitation on discharged patients with COVID-19 is currently unclear, especially on patients who have been mechanically ventilated over 24 hours. Therefore, we aim to investigate the efficacy of respiratory rehabilitation programmes, initiated after discharge from the intensive care unit, on the physical and mental health and health-related quality of life in critical patients with COVID-19. METHODS AND ANALYSIS: We have registered the protocol on PROSPERO and in the process of drafting it, we strictly followed the checklist of Preferred Reporting Items for Systematic Review and Meta-Analysis Potocols. We will search the PubMed, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, WanFang, VIP information databases and Chinese Biomedical Literature Database. Additionally, ongoing trials in the WHO International Clinical Trials Registry Platform, ClinicalTrials.gov and ISRCTN registry will be searched as well. Studies in English or Chinese and from any country will be accepted regardless of study design. Two review authors will independently extract data and assess the quality of included studies. Continuous data are described as standard mean differences (SMDs) with 95% CIs. Dichotomous data from randomised controlled trials are described as risk ratio(RR) with 95% CIs; otherwise, it is described as odds ratio(OR) with 95% CIs. I2 and the Cochrane's Q statistic will be used to conduct heterogeneity assessment. The quality of evidence of main outcomes will be evaluated according to the Grading of Recommendations, Assessment, Development and Evaluation(GRADE) criteria. When included studies are sufficient, we will conduct subgroup analysis and sensitivity analysis; the publication bias will be statistically analysed using a funnel plot analysis and Egger's test. ETHICS AND DISSEMINATION: Our review, planning to include published studies, does not need the request to the ethical committee. The final results of this review will be published in a peer-reviewed journal after completion. PATIENT AND PUBLIC INVOLVEMENT: No patient involved. PROSPERO REGISTRATION NUMBER: CRD42020186791.

3D Printed and Electrospun, Transparent, Hierarchical Polylactic Acid Mask Nanoporous Filter.

Face masks are becoming one of the most useful personal protective equipment with the outbreak of the coronavirus (CoV) pandemic. The entire world is experiencing shortage of disposable masks and melt-blown non-woven fabrics, which is the raw material of the mask filter. Recyclability of the discarded mask is also becoming a big challenge for the environment. Here, we introduce a facile method based on electrospinning and three-dimensional printing to make changeable and biodegradable mask filters. We printed polylactic acid (PLA) polymer struts on a PLA nanofiber web to fabricate a nanoporous filter with a hierarchical structure and transparent look. The transparent look overcomes the threatening appearance of the masks that can be a feasible way of reducing the social trauma caused by the current CoV disease-19 pandemic. In this study, we investigated the effects of nozzle temperature on the optical, mechanical, and morphological and filtration properties of the nanoporous filter.

Effects of respiratory rehabilitation on patients with novel coronavirus (COVID-19) pneumonia in the rehabilitation phase: protocol for a systematic review and meta-analysis.

INTRODUCTION: The recent viral pneumonia caused by the COVID-19 has gained the attention of the people all over the world. We aim to investigate the effects of respiratory rehabilitation therapy on patients infected with the novel coronavirus by conducting a systematic review and meta-analysis. METHODS AND ANALYSIS: This systematic review and meta-analysis have been registered in the International Prospective Register of Systematic Reviews (PROSPERO). The PubMed, Embase, Web of Science, the Cochrane Central Register of Controlled Trials, Chinese Biomedical Literature Database, China National Knowledge Infrastructure, Wanfang Data and Viper information databases will be searched from inception time to date without restricting research types to find relevant studies. We will also look into reference lists of relevant trials and reviews, and manually search grey literature, such as trial registries. Two reviewers will independently extract data and perform quality assessment of included studies. Review Manager V.5.3 (Cochrane Collaboration) and Stata V.16.0 software will be used to conduct this meta-analysis. The mean difference or standardised mean difference with 95% CIs is used in the computation of continuous variables to synthesise data. ETHICS AND DISSEMINATION: Ethical approval is not required due to the nature of this meta-analysis, which is based on published papers. The results of this systematic review and meta-analysis will be published in a peer-reviewed journal once we finish this study. PROSPERO REGISTRATION NUMBER: CRD42020180214.