Predictive value of immunoglobulin G, activated partial thromboplastin time, platelet, and indirect bilirubin for delayed viral clearance in patients infected with the Omicron variant.

Background: Omicron is the recently emerged highly transmissible severe acute respiratory syndrome coronavirus 2 variant that has caused a dramatic increase in coronavirus disease-2019 infection cases worldwide. This study was to investigate the association between demographic and laboratory findings, and the duration of Omicron viral clearance. Methods: Approximately 278 Omicron cases at the Ruijin Hospital Luwan Branch, Shanghai Jiaotong University School of Medicine were retrospectively analyzed between August 11 and August 31, 2022. Demographic and laboratory data were also collected. The association between demographics, laboratory findings, and duration of Omicron viral clearance was analyzed using Pearson correlation analysis and univariate and multivariate logistic regression. Results: Univariate logistic regression analyses showed that a prolonged viral clearance time was significantly associated with older age and lower immunoglobulin (Ig) G and platelet (PLT) levels. Using multinomial logistic regression analyses, direct bilirubin, IgG, activated partial thromboplastin time (APTT), and PLT were independent factors for longer viral shedding duration. The model combining direct bilirubin, IgG, APTT, and PLT identifies patients infected with Omicron whose viral clearance time was ≥7 days with 62.7% sensitivity and 83.4% specificity. Conclusion: These findings suggest that direct bilirubin, IgG, PLT, and APTT are significant risk factors for a longer viral shedding duration in patients infected with Omicron. Measuring levels of direct bilirubin, IgG, PLT, and APTT is advantageous to identify patients infected with Omicron with longer viral shedding duration.

Seesaw Effect Between COVID-19 and Influenza From 2020 to 2023 in World Health Organization Regions: Correlation Analysis.

BACKGROUND: Seasonal influenza activity showed a sharp decline in activity at the beginning of the emergence of COVID-19. Whether there is an epidemiological correlation between the dynamic of these 2 respiratory infectious diseases and their future trends needs to be explored. OBJECTIVE: We aimed to assess the correlation between COVID-19 and influenza activity and estimate later epidemiological trends. METHODS: We retrospectively described the dynamics of COVID-19 and influenza in 6 World Health Organization (WHO) regions from January 2020 to March 2023 and used the long short-term memory machine learning model to learn potential patterns in previously observed activity and predict trends for the following 16 weeks. Finally, we used Spearman correlation coefficients to assess the past and future epidemiological correlation between these 2 respiratory infectious diseases. RESULTS: With the emergence of the original strain of SARS-CoV-2 and other variants, influenza activity stayed below 10% for more than 1 year in the 6 WHO regions. Subsequently, it gradually rose as Delta activity dropped, but still peaked below Delta. During the Omicron pandemic and the following period, the activity of each disease increased as the other decreased, alternating in dominance more than once, with each alternation lasting for 3 to 4 months. Correlation analysis showed that COVID-19 and influenza activity presented a predominantly negative correlation, with coefficients above -0.3 in WHO regions, especially during the Omicron pandemic and the following estimated period. The diseases had a transient positive correlation in the European region of the WHO and the Western Pacific region of the WHO when multiple dominant strains created a mixed pandemic. CONCLUSIONS: Influenza activity and past seasonal epidemiological patterns were shaken by the COVID-19 pandemic. The activity of these diseases was moderately or greater than moderately inversely correlated, and they suppressed and competed with each other, showing a seesaw effect. In the postpandemic era, this seesaw trend may be more prominent, suggesting the possibility of using one disease as an early warning signal for the other when making future estimates and conducting optimized annual vaccine campaigns.

Evaluation of adverse events of bamlanivimab, bamlanivimab/etesevimab used for COVID-19 based on FAERS database.

BACKGROUND: We study the adverse events (AEs) of bamlanivimab (BAM), bamlanivimab/etesevimab (BAM/ETE) to alert risk factors during coronavirus disease 2019 (COVID-19) treatment and provide references for drug safety. RESEARCH DESIGN AND METHODS: Extract AEs from the COVID-19 Emergency Use Authorization (EUA) FDA Adverse Event Reporting System (FAERS) Public Dashboard. Disproportionality analysis was performed to discover the potential risks of BAM and BAM/ETE. RESULTS: With COVID-19 drugs as the research background, the number of BAM/ETE signals is about half that of BAM, and 80% of signals overlap with BAM. Signals such as atrial fibrillation, tachycardia, and confusional state are present in BAM but not in BAM/ETE. With BAM and BAM/ETE as the research background, potential safety signals of BAM/ETE such as acute respiratory failure, hypersensitivity, and infusion-related reaction require long-term observation, especially acute respiratory failure which is not in the label. CONCLUSIONS: The AEs report on this study confirm most of the label information of BAM and BAM/ETE. BAM/ETE is relatively safe, while the risk signals such as acute respiratory failure and infusion-related reaction require to be monitored.

Did COVID-19 affect rural households' subjective well-being? A social survey from rural China.

Improving rural households' subjective well-being is an important element of economic and social revitalization in the post-epidemic period. Based on the survey data obtained from rural households in Hubei Province, the center of the outbreak in China, and its surrounding areas, this paper explores the impact mechanisms of the COVID-19 epidemic on subjective well-being from both economic and sociological perspectives with the help of structural equation modeling. The results show that COVID-19 significantly influenced rural households' subjective well-being in China. Furthermore, COVID-19 indirectly affected their subjective well-being by influencing optimism. The negative impact is moderated by government intervention and income resilience. Therefore, strengthening the emergency management capacity of local governments and encouraging the diversification of rural households' income sources are important strategies to effectively resolve epidemic shocks and improve the level of well-being.

Quantitative annotations of T-Cell repertoire specificity.

The specificity of a T-cell receptor (TCR) repertoire determines personalized immune capacity. Existing methods have modeled the qualitative aspects of TCR specificity, while the quantitative aspects remained unaddressed. We developed a package, TCRanno, to quantify the specificity of TCR repertoires. We created deep-learning-based, epitope-aware vector embeddings to infer individual TCR specificity. Then we aggregated clonotype frequencies of TCRs to obtain a quantitative profile of repertoire specificity at epitope, antigen and organism levels. Applying TCRanno to 4195 TCR repertoires revealed quantitative changes in repertoire specificity upon infections, autoimmunity and cancers. Specifically, TCRanno found cytomegalovirus-specific TCRs in seronegative healthy individuals, supporting the possibility of abortive infections. TCRanno discovered age-accumulated fraction of severe acute respiratory syndrome coronavirus 2 specific TCRs in pre-pandemic samples, which may explain the aggressive symptoms and age-related severity of coronavirus disease 2019. TCRanno also identified the encounter of Hepatitis B antigens as a potential trigger of systemic lupus erythematosus. TCRanno annotations showed capability in distinguishing TCR repertoires of healthy and cancers including melanoma, lung and breast cancers. TCRanno also demonstrated usefulness to single-cell TCRseq+gene expression data analyses by isolating T-cells with the specificity of interest.

Secure and Efficient Smart Healthcare System Based on Federated Learning

The rapid development of smart healthcare system in the Internet of Things (IoT) has made the early detection of many chronic diseases more convenient, quick, and economical. However, when healthcare organizations collect users' health data through deployed IoT devices, there are issues of compromising users' privacy. In view of this situation, this paper introduces federated learning technology to solve the problem of data security. In this paper, we consider the two main problems of federated learning applications in IoT smart healthcare system: (1) how to reduce the time overhead of system running and (2) how to authenticate that the user device uploading data is deployed by the system itself. To solve the above problems, we propose the first federated learning scheme based on full dynamic secret sharing. First, we use a two-mask protocol to keep the user's local model parameters confidential during federated learning. Then, based on homogeneous linear recursive equation, homomorphic hash function, and elliptic curve cryptosystem, the full dynamic secret sharing and user identity authentication are realized. In addition, our scheme allows users to join or quit during training. Finally, we have carried out simulation test on this scheme. The experimental results show that the efficiency of our scheme is improved by about 60% on average in the case of no user dropping and by about 30% in the case of some users dropping.

Sustainable production of dimethyl-protected cyclic lysine over Pd/m-Al2O3-Si catalysts and its application in synthesis of antibacterial nylon‑6 copolymers

• Pd/ m- Al 2 O 3 -Si catalyst exhibited high efficiency in converting α- amino -ε- caprolactam (α- ACL) to dimethyl-protected cyclic lysine (DMCL). • The lack of Brönsted acid sites on Pd/ m- Al 2 O 3 -Si surface facilitated the formation of DMCL and suppressed undesirable reaction process. • Pd/ m- Al 2 O 3 -Si catalyst with microspherical morphology performed excellent stability and physical strength during the catalytic process. • The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited a great potential in the synthesis of self-cleaning antibacterial materials. Antibacterial monomers are prerequisites for synthesizing antibacterial polymers, especially during the current COVID-19 pandemic. Dimethyl-protected cyclic lysine (DMCL) is a promising functional monomer for nylon-6 based self-cleaning antibacterial polymers. However, the production of DMCL still faces formidable challenges, such as harsh reaction conditions and low catalyst activities. In this study, we developed a Pd/ m -Al 2 O 3 -Si catalyst, which exhibited high efficiency in converting α -amino- ε -caprolactam (α -ACL) to DMCL, affording a yield of as high as 97.1% at 100 °C and 1 MPa H 2. The lack of Brönsted acid sites on the catalyst surface facilitated the formation of DMCL and suppressed undesirable hydrolysis or cracking by-products from the lactam-based reactant. The recycled experiments showed that Pd/ m -Al 2 O 3 -Si performed excellent stability and physical strength with essentially no damage to its microspheres after the reaction. The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited similar structure and thermal stability with pure nylon-6, showing great potential in synthesizing the self-cleaning antibacterial polymers. This work provides a sustainable and efficient method for producing DMCL and other lysine-based antibacterial monomers, showing a great prospect for the utilization of bio-based chemicals in synthesizing functional polymers. [ FROM AUTHOR] Copyright of Chemical Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Dysbiosis of oropharyngeal microbiome and antibiotic resistance in hospitalized COVID-19 patients.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is ongoing and multiple studies have elucidated its pathogenesis, however, the related- microbiome imbalance caused by SARS-CoV-2 is still not clear. In this study, we have comprehensively compared the microbiome composition and associated function alterations in the oropharyngeal swabs of healthy controls and coronavirus disease 2019 (COVID-19) patients with moderate or severe symptoms by metatranscriptomic sequencing. We did observe a reduced microbiome alpha-diversity but significant enrichment of opportunistic microorganisms in patients with COVID-19 compared with healthy controls, and the microbial homeostasis was rebuilt following the recovery of COVID-19 patients. Correspondingly, less functional genes in multiple biological processes and weakened metabolic pathways such as carbohydrate metabolism, energy metabolism were also observed in COVID-19 patients. We only found higher relative abundance of limited genera such as Lachnoanaerobaculum between severe patients and moderate patients while no worthy-noting microbiome diversity and function alteration were observed. Finally, we noticed that the co-occurrence of antibiotic resistance and virulence was closely related to the microbiome alteration caused by SRAS-CoV-2. Overall, our findings demonstrate that microbial dysbiosis may enhance the pathogenesis of SARS-CoV-2 and the antibiotics treatment should be critically considered.

Global trends in the research and development of medical/pharmaceutical wastewater treatment over the half-century.

The COVID-19 pandemic has severely impacted public health and the worldwide economy. The overstretched operation of health systems around the world is accompanied by potential and ongoing environmental threats. At present, comprehensive scientific assessments of research on temporal changes in medical/pharmaceutical wastewater (MPWW), as well as estimations of researcher networks and scientific productivity are lacking. Therefore, we conducted a thorough literature study, using bibliometrics to reproduce research on medical wastewater over nearly half a century. Our primary goal is systematically to map the evolution of keyword clusters over time, and to obtain the structure and credibility of clusters. Our secondary objective was to measure research network performance (country, institution, and author) using CiteSpace and VOSviewer. We extracted 2306 papers published between 1981 and 2022. The co-cited reference network identified 16 clusters with well-structured networks (Q = 0.7716, S = 0.896). The main trends were as follows: 1) Early MPWW research prioritized sources of wastewater, and this cluster was considered to be the mainstream research frontier and direction, representing an important source and priority research area. 2) Mid-term research focused on characteristic contaminants and detection technologies. Particularly during 2000-2010, a period of rapid developments in global medical systems, pharmaceutical compounds (PhCs) in MPWW were recognized as a major threat to human health and the environment. 3) Recent research has focused on novel degradation technologies for PhC-containing MPWW, with high scores for research on biological methods. Wastewater-based epidemiology has emerged as being consistent with or predictive of the number of confirmed COVID-19 cases. Therefore, the application of MPWW in COVID-19 tracing will be of great interest to environmentalists. These results could guide the future direction of funding agencies and research groups.

Discovery and characterization of the covalent SARS-CoV-2 3CLpro inhibitors from Ginkgo biloba extract via integrating chemoproteomic and biochemical approaches.

BACKGROUND: The 3C-like proteases (3CLpros) are cysteine-rich homodimeric proteins and can be covalently modified by numerous natural and synthetic compounds, which in turn, block the proteolytic activity or the formation of enzymatically active dimeric forms. Although herbal medicines have been widely used to treat COVID-19, identification of the key herbal constituents that can covalently modify the 3CLpros in ß-coronaviruses (CoVs) remains a big challenge. AIMS: To construct a comprehensive approach for efficient discovering the covalent SARS-CoV-2 3CLpro inhibitors from herbal medicines. To decipher the key anti-SARS-CoV-2 3CLpro constituents in Ginkgo biloba extract 50 (GBE50) and to study their anti-SARS-CoV-2 3CLpro mechanisms. METHODS: SARS-CoV-2 3CLpro inhibition assay including time-dependent inhibition assays and inactivation kinetic analyses were conducted using a fluorescence-based biochemical assay. The constituents in GBE50 were analyzed by UHPLC-Q-Exactive Orbitrap HRMS. The peptides modified by herbal constituents were characterized by using nanoLC-MS/MS. RESULTS: Following testing the anti-SARS-CoV-2 3CLpro effects of 104 herbal medicines, it was found that Ginkgo biloba extract 50 (GBE50) potently inhibited SARS-CoV-2 3CLpro in dose- and time-dependent manners. A total of 38 constituents were identified from GBE50 by UHPLC-Q-Exactive Orbitrap HRMS, while 26 peptides modified by 18 constituents were identified by chemoproteomic profiling. The anti-SARS-CoV-2 3CLpro effects of 18 identified covalent inhibitors were then validated by performing time-dependent inhibition assays. The results clearly demonstrated that most tested constituents showed time-dependent inhibition on SARS-CoV-2 3CLpro, while gallocatechin and sciadopitysin displayed the most potent anti-SARS-CoV-2 3CLpro effects. CONCLUSION: Collectively, GBE50 and some constituents in this herbal product could strongly inhibit SARS-CoV-2 3CLpro in dose- and time-dependent manner. Gallocatechin and sciadopitysin were identified as potent SARS-CoV-2 3CLpro inhibitors, which offers promising lead compounds for the development of novel anti-SARS-CoV-2 drugs.

Prevalence and risk factors of post-traumatic stress disorder symptoms among Chinese health care workers following the COVID-19 pandemic

In December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan (Hubei, China) and subsequently swept the globe. In addition to the risk of infection, there is a strong possibility that post-traumatic stress disorder (PTSD) may be a secondary effect of the pandemic. Health care workers (HCWs) participating in the pandemic are highly exposed to and may bear the brunt out of stressful or traumatic events. In this cross-sectional study, we assessed the morbidity and risk factors of PTSD symptoms among Chinese HCWs. A total of 457 HCWs were recruited from March 15, 2020, to Mach 22, 2020, including HCWs in Wuhan and Hubei Province (excluding Wuhan), the areas first and most seriously impacted by COVID-19. The morbidity of PTSD symptoms was assessed by the Event Scale–Revised (IES-R). The risk factors for PTSD symptoms were explored by means of logistic regression analysis. Over 40% of the respondents experienced PTSD symptoms more than one month after the COVID-19 outbreak, and this proportion increased to 57.7% in Wuhan HCWs, especially females and HCWs on the frontline. Thus, rapid mental health assessment and effective psychological interventions need to be developed for frontline HCWs to prevent long-term PTSD-related disabilities. Moreover, Negative coping style and neuroticism personality may be regarded as high risk factors for PTSD symptoms. Improving individual coping strategies to enhance resilience should be the focus of further preventive intervention strategies.

COVID-19 infection-associated multisystem inflammatory syndrome and cytokine storms in children

Multisystem inflammatory syndrome in children(MIS-C) is a systemic inflammatory syndrome with multiorgan dysfunctions. Most of the children have evidence of severe acute respiratory syndrome-associated coronavirus(SARSCoV-2) infection or a history of exposure to patients with coronavirus disease 2019(COVID-19). Children often present with fever, gastrointestinal symptoms, cardiac dysfunctions, shock and other multi-system symptoms. Cytokine storm(CS) is an inflammatory response triggered by external stimulations. Factors causing CS include iatrogenic,pathogenic, monogenic or autoimmune diseases. The pathogenesis of MIS-C is still unclear, which may be related to the over-response of immune system caused by SARS-CoV-2 infections.In this paper, the clinical characteristics of COVID-19 infection-related MIS-C are summarized, and the relationship between MIS-C and CS is discussed, aiming to provide references for the mechanistic investigation and clinical diagnosis of MIS-C.

Discovery and characterization of the covalent SARS-CoV-2 3CLpro inhibitors from Ginkgo biloba extract via integrating chemoproteomic and biochemical approaches

Background : The 3C-like proteases (3CLpros) are cysteine-rich homodimeric proteins and can be covalently modified by numerous natural and synthetic compounds, which in turn, block the proteolytic activity or the formation of enzymatically active dimeric forms. Although herbal medicines have been widely used to treat COVID-19, identification of the key herbal constituents that can covalently modify the 3CLpros in β-coronaviruses (CoVs) remains a big challenge. Aims : To construct a comprehensive approach for efficient discovering the covalent SARS-CoV-2 3CLpro inhibitors from herbal medicines. To decipher the key anti-SARS-CoV-2 3CLpro constituents in Ginkgo biloba extract 50 (GBE50) and to study their anti-SARS-CoV-2 3CLpro mechanisms. Methods : SARS-CoV-2 3CLpro inhibition assay including time-dependent inhibition assays and inactivation kinetic analyses were conducted using a fluorescence-based biochemical assay. The constituents in GBE50 were analyzed by UHPLC-Q-Exactive Orbitrap HRMS. The peptides modified by herbal constituents were characterized by using nanoLC-MS/MS. Results : Following testing the anti-SARS-CoV-2 3CLpro effects of 104 herbal medicines, it was found that Ginkgo biloba extract 50 (GBE50) potently inhibited SARS-CoV-2 3CLpro in dose- and time-dependent manners. A total of 38 constituents were identified from GBE50 by UHPLC-Q-Exactive Orbitrap HRMS, while 26 peptides modified by 18 constituents were identified by chemoproteomic profiling. The anti-SARS-CoV-2 3CLpro effects of 18 identified covalent inhibitors were then validated by performing time-dependent inhibition assays. The results clearly demonstrated that most tested constituents showed time-dependent inhibition on SARS-CoV-2 3CLpro, while gallocatechin and sciadopitysin displayed the most potent anti-SARS-CoV-2 3CLpro effects. Conclusion : Collectively, GBE50 and some constituents in this herbal product could strongly inhibit SARS-CoV-2 3CLpro in dose- and time-dependent manner. Gallocatechin and sciadopitysin were identified as potent SARS-CoV-2 3CLpro inhibitors, which offers promising lead compounds for the development of novel anti-SARS-CoV-2 drugs. Graphical abstract Image, graphical abstract

AutoVEM: An automated tool to real-time monitor epidemic trends and key mutations in SARS-CoV-2 evolution.

With the global epidemic of SARS-CoV-2, it is important to effectively monitor the variation, haplotype subgroup epidemic trends and key mutations of SARS-CoV-2 over time. This is of great significance to the development of new vaccines, the update of therapeutic drugs, and the improvement of detection methods. The AutoVEM tool developed in the present study could complete all mutations detections, haplotypes classification, haplotype subgroup epidemic trends and candidate key mutations analysis for 131,576 SARS-CoV-2 genome sequences in 18 h on a 1 core CPU and 2 GB RAM computer. Through haplotype subgroup epidemic trends analysis of 131,576 genome sequences, the great significance of the previous 4 specific sites (C241T, C3037T, C14408T and A23403G) was further revealed, and 6 new mutation sites of highly linked (T445C, C6286T, C22227T, G25563T, C26801G and G29645T) were discovered for the first time that might be related to the infectivity, pathogenicity or host adaptability of SARS-CoV-2. In brief, we proposed an integrative method and developed an efficient automated tool to monitor haplotype subgroup epidemic trends and screen for the candidate key mutations in the evolution of SARS-CoV-2 over time for the first time, and all data could be updated quickly to track the prevalence of previous key mutations and new candidate key mutations because of high efficiency of the tool. In addition, the idea of combinatorial analysis in the present study can also provide a reference for the mutation monitoring of other viruses.

AutoVEM2: A flexible automated tool to analyze candidate key mutations and epidemic trends for virus.

In our previous work, we developed an automated tool, AutoVEM, for real-time monitoring the candidate key mutations and epidemic trends of SARS-CoV-2. In this research, we further developed AutoVEM into AutoVEM2. AutoVEM2 is composed of three modules, including call module, analysis module, and plot module, which can be used modularly or as a whole for any virus, as long as the corresponding reference genome is provided. Therefore, it's much more flexible than AutoVEM. Here, we analyzed three existing viruses by AutoVEM2, including SARS-CoV-2, HBV and HPV-16, to show the functions, effectiveness and flexibility of AutoVEM2. We found that the N501Y locus was almost completely linked to the other 16 loci in SARS-CoV-2 genomes from the UK and Europe. Among the 17 loci, 5 loci were on the S protein and all of the five mutations cause amino acid changes, which may influence the epidemic traits of SARS-CoV-2. And some candidate key mutations of HBV and HPV-16, including T350G of HPV-16 and C659T of HBV, were detected. In brief, we developed a flexible automated tool to analyze candidate key mutations and epidemic trends for any virus, which would become a standard process for virus analysis based on genome sequences in the future.

The waste ban in China: what happened next? Assessing the impact of new policies on the waste management sector in China.

The 2017 ban on the waste import and new policies for the waste management sector in mainland China had wide-spread impact. After decades of poor environmental and public health impacts from the sector, a study is needed which focuses on policies updates and waste management. This provides a direction for the survival of local waste management industries and consider similarities with the ban promulgated in China on the restriction of waste import from other countries. We review the waste management situation in China before national legislation prevented the import of waste, highlight the status of landfill mining in China, and review the dynamics of domestic policies before and after the promulgation of the ban in China. The impact of the COVID19 pandemic on the waste management system is starting to emerge, providing both challenges and opportunities for the sector in China. We see the impact of the ban on the range of imported waste and domestically generated materials. The ban results in price increases for domestic recycling that forces companies to introduce more formal recycling processes and to drive the consumption behaviours to more reasonable and environmentally friendly options. The driver in China is to reduce pollution in the environment and improve health, but a negative impact has been from increased landfill mining which has impeded the original aim of the waste ban and requires further technological development. The dynamic of domestic policies in China shows higher level of activity of updates and revisions or introduction of new policies from 2015 onwards and the concept of 'zero waste cities' brings new hope for improvement of the Chinese waste management system. The pandemic also suggests an important step to establish sustainable management systems despite evidence of increased "fly-tipping". The rebound of the waste ban may have stimulated in the short term negative impacts on local environments both in China and internationally.

Psychological symptoms and correlates of Chinese healthcare professionals in the intensive care unit before and after the COVID-19 outbreak: A comparison of two cross-sectional studies.

BACKGROUND: The outbreak of COVID-19 disarranged lives across mainland China. No study has examined changes in psychological symptoms of healthcare professionals in the intensive care unit (ICU) before and after the outbreak of COVID-19. The aim of this study was to estimate changes in psychological symptoms of ICU healthcare professionals before and after the COVID-19 outbreak, and to analyze factors related to psychological symptoms. METHODS: Two waves' administrations were implemented between December 13 and December 14, 2018, and between April 5 and April 7, 2020, respectively. The symptom checklist-90 (SCL-90) were used to evaluate psychological symptoms. Multiple logistical regression was used to reveal the risk of psychological symptoms. RESULTS: A total of 3902 and 3908 ICU healthcare professionals took part in the first and second surveys. The mean total score of the SCL-90 was 179.27 (70.02) at wave 1 and 147.75 (58.40) at wave 2, respectively. The proportion of psychological symptoms was 55.6 % (95%CI = 54.0-57.1) at wave 1. But rates of psychological symptoms decreased to 36.6 % (95%CI = 35.1-38.2) at wave 2. ICU healthcare professionals with western economic belt and 6-10 years of work were more likely to develop psychological symptoms, while ICU healthcare professionals with the later survey and doctoral degree were less likely to develop psychological symptoms. CONCLUSION: Although COVID-19 period benefited psychological symptoms of ICU healthcare professionals, psychological symptoms still had a related high prevalence. Regular screening and appropriate interventions should still be implemented to decrease the risk for psychological symptoms among Chinese ICU healthcare professionals.

Prevalence and risk factors of post-traumatic stress disorder symptoms among Chinese health care workers following the COVID-19 pandemic.

In December 2019, coronavirus disease 2019 (COVID-19) appeared in Wuhan (Hubei, China) and subsequently swept the globe. In addition to the risk of infection, there is a strong possibility that post-traumatic stress disorder (PTSD) may be a secondary effect of the pandemic. Health care workers (HCWs) participating in the pandemic are highly exposed to and may bear the brunt out of stressful or traumatic events. In this cross-sectional study, we assessed the morbidity and risk factors of PTSD symptoms among Chinese HCWs. A total of 457 HCWs were recruited from March 15, 2020, to Mach 22, 2020, including HCWs in Wuhan and Hubei Province (excluding Wuhan), the areas first and most seriously impacted by COVID-19. The morbidity of PTSD symptoms was assessed by the Event Scale-Revised (IES-R). The risk factors for PTSD symptoms were explored by means of logistic regression analysis. Over 40% of the respondents experienced PTSD symptoms more than one month after the COVID-19 outbreak, and this proportion increased to 57.7% in Wuhan HCWs, especially females and HCWs on the frontline. Thus, rapid mental health assessment and effective psychological interventions need to be developed for frontline HCWs to prevent long-term PTSD-related disabilities. Moreover, Negative coping style and neuroticism personality may be regarded as high risk factors for PTSD symptoms. Improving individual coping strategies to enhance resilience should be the focus of further preventive intervention strategies.