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1.
Zhongguo Huanjing Kexue = China Environmental Science ; 41(7):3088, 2021.
Article in English | ProQuest Central | ID: covidwho-1342758

ABSTRACT

In order to investigate the impact of COVID-19 lockdown on air quality in Nanjing, the air pollutants observed from January 25 to February 10, in 2020(COVID-19 lockdown period) in Nanjing and its surrounding cities was analyzed. During the lockdown period with poor atmospheric diffusion conditions, the concentrations of PM2.5, PM10, NO2, SO2, and CO decreased obviously, with the value of 36, 44, 5, 22μg/m3 and 1.1 mg/m3, whereasO3 increased by 4%. The net effectiveness of the emission reduction measures was calculated through comparisons of concentrations of air pollutants between and before COVID in the similar meteorological conditions. Concentrations of PM2.5, PM10, SO2, NO2 and CO decreased by 41.7%, 45.3%, 14.3%, 43.5% and 18.2%, respectively, whereasO3 increased by 4.8%. Compared to capital cities of the Yangtze River Delta in the same period, the largest decline of SO2 and the medium decline of the other pollutions were appeared in Nanjing. The diurnal variation concentration of PM2.5 and PM10 changed from double peak to single peak, due to the disappearance of nighttime sub-peak of particle. The concentration ofO3 increased significantly at night, which was resulted from that sharp reduction of traffic sources weaken the titration reaction of NO toO3. The peak ofO3 during the daytime depended on the variation of the ratio of VOCs to NOx due to the emission control.

2.
Ann Palliat Med ; 10(7): 7329-7339, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1311480

ABSTRACT

BACKGROUND: This study aimed to build a radiomics model with deep learning (DL) and human auditing and examine its diagnostic value in differentiating between coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP). METHODS: Forty-three COVID-19 patients, whose diagnoses had been confirmed with reverse-transcriptase polymerase-chain-reaction (RT-PCR) tests, and 60 CAP patients, whose diagnoses had been confirmed with sputum cultures, were enrolled in this retrospective study. The candidate regions of interest (ROIs) on the computed tomography (CT) images of the 103 patients were determined using a DL-based segmentation model powered by transfer learning. These ROIs were manually audited and corrected by 3 radiologists (with an average of 12 years of experience; range 6-17 years) to check the segmentation acceptance for the radiomics analysis. ROI-derived radiomics features were subsequently extracted to build the classification model and processed using 4 different algorithms (L1 regularization, Lasso, Ridge, and Z test) and 4 classifiers, including the logistic regression (LR), multi-layer perceptron (MLP), support vector machine (SVM), and extreme Gradient Boosting (XGboost). A receiver operating characteristic curve (ROC) analysis was conducted to evaluate the performance of the model. RESULTS: Quantitative CT measurements derived from human-audited segmentation results showed that COVID-19 patients had significantly decreased numbers of infected lobes compared to patients in the CAP group {median [interquartile range (IQR)]: 4 [3, 4] and 4 [4, 5]; P=0.031}. The infected percentage (%) of the whole lung was significantly more elevated in the CAP group [6.40 (2.77, 11.11)] than the COVID-19 group [1.83 (0.65, 4.42); P<0.001], and the same trend applied to each lobe, except for the superior lobe of the right lung [1.81 (0.09, 5.28) for COVID-19 vs. 1.32 (0.14, 7.02) for CAP; P=0.649]. Additionally, the highest proportion of infected lesions were observed in the CT value range of (-470, -370) Hounsfield units (HU) in the COVID-19 group. Conversely, the CAP group had a value range of (30, 60) HU. Radiomic model using corrected ROIs exhibited the highest area under ROC (AUC) of 0.990 [95% confidence interval (CI): 0.962-1.000] using Lasso for feature selection and MLP for classification. CONCLUSIONS: The proposed radiomics model based on human-audited segmentation made accurate differential diagnoses of COVID-19 and CAP. The quantification of CT measurements derived from DL could potentially be used as effective biomarkers in current clinical practice.


Subject(s)
COVID-19 , Deep Learning , Computers , Humans , Retrospective Studies , SARS-CoV-2
3.
Front Immunol ; 12: 708523, 2021.
Article in English | MEDLINE | ID: covidwho-1295646

ABSTRACT

Major advances have been made in understanding the dynamics of humoral immunity briefly after the acute coronavirus disease 2019 (COVID-19). However, knowledge concerning long-term kinetics of antibody responses in convalescent patients is limited. During a one-year period post symptom onset, we longitudinally collected 162 samples from 76 patients and quantified IgM and IgG antibodies recognizing the nucleocapsid (N) protein or the receptor binding domain (RBD) of the spike protein (S). After one year, approximately 90% of recovered patients still had detectable SARS-CoV-2-specific IgG antibodies recognizing N and RBD-S. Intriguingly, neutralizing activity was only detectable in ~43% of patients. When neutralization tests against the E484K-mutated variant of concern (VOC) B.1.351 (initially identified in South Africa) were performed among patients who neutralize the original virus, the capacity to neutralize was even further diminished to 22.6% of donors. Despite declining N- and S-specific IgG titers, a considerable fraction of recovered patients had detectable neutralizing activity one year after infection. However, neutralizing capacities, in particular against an E484K-mutated VOC were only detectable in a minority of patients one year after symptomatic COVID-19. Our findings shed light on the kinetics of long-term immune responses after natural SARS-CoV-2 infection and argue for vaccinations of individuals who experienced a natural infection to protect against emerging VOC.


Subject(s)
Antibodies, Neutralizing/blood , Antibodies, Viral/blood , COVID-19/immunology , Immunoglobulin G/blood , Immunoglobulin M/blood , SARS-CoV-2/immunology , Aged , Antibody Formation/immunology , COVID-19/therapy , Convalescence , Coronavirus Nucleocapsid Proteins/immunology , Female , Humans , Male , Middle Aged , Phosphoproteins/immunology , Spike Glycoprotein, Coronavirus/immunology , Time Factors
4.
BMC Infect Dis ; 21(1): 574, 2021 Jun 14.
Article in English | MEDLINE | ID: covidwho-1269872

ABSTRACT

BACKGROUND: Coronavirus disease-19 (COVID-19) has become a world health threaten. Its risk factors with death were still not known. White blood cells (WBC) count as a reflection of inflammation has played a vital role in COVID-19, however its level with death is not yet investigated. METHODS: In this retrospective, single-center study, all confirmed patients with COVID-19 at West Branch of Union Hospital from Jan 29 to Feb 28, 2020 were collected and analyzed. Demographic and clinical data including laboratory examinations were analyzed and compared between recovery and death patients. RESULTS: A total of 163 patients including 33 death cases were included in this study. Significant association was found between WBC count and death (HR = 1.14, 95%CI: 1.09-1.20, p < 0.001). The regression analysis results showed there was a significant association between WBC count and death (HR = 5.72, 95%CI: 2.21-14.82, p < 0.001) when use the second quartile as a cutoff value (> 6.16 × 10^9/L). The difference was still exist after adjusting for confounding factors (HR = 6.26, 95%CI: 1.72-22.77, p = 0.005). In addition, Kaplan-meier survival analysis showed that there was a significant decline of the cumulative survival rate (p < 0.001) in those with WBC count ≥6.16 × 10^9/L. CONCLUSION: WBC count at admission is significantly corelated with death in COVID-19 patients. Higher level of WBC count should be given more attention in the treatment of COVID-19.


Subject(s)
COVID-19/blood , COVID-19/mortality , Leukocytes , Patient Admission , SARS-CoV-2/genetics , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/virology , China/epidemiology , Female , Humans , Inflammation/blood , Inflammation/virology , Kaplan-Meier Estimate , Leukocyte Count , Male , Middle Aged , Real-Time Polymerase Chain Reaction , Retrospective Studies , Risk Factors , Survival Rate
5.
Sustainability ; 13(9):5305, 2021.
Article in English | MDPI | ID: covidwho-1224227

ABSTRACT

To analyse the prevalence of severe and critical COVID-19 cases and its determinants, a systematic review and meta-analysis were conducted using Review Manager. Four English and two Chinese databases were used to identify and explore the relationships between the severity of COVID-19 and its determinants, with no restrictions on publication date. The odds ratio and 95% CI were combined to assess the influencing level of all factors. Twenty-three articles containing a total of 15,828 cases of COVID-19 were included in this systematic review. The prevalence of severe and critical COVID-19 cases was 17.84% and 4.9%, respectively. A total of 148 factors were identified, which included behavioural, symptom, comorbidity, laboratory, radiographic, exposure, and other factors. Among them, 35 factors could be included in the meta-analysis. Specifically, for example, the male (OR 1.55, 95% CI 1.42–1.69) and elderly (OR 1.06, 95% CI 1.03–1.10) populations tended to experience severe and critical illness. Patients with cough, dyspnea, fatigue, fever, and gastrointestinal symptoms could have severe and critical diseases. Regarding laboratory results, albumin, aspartate aminotransferase, creatinine, D-dimer, fibrinogen, neutrophils, procalcitonin, platelets, and respiratory rate were potential factors that could be used to predict the severity of COVID.

6.
Virol J ; 18(1): 67, 2021 03 31.
Article in English | MEDLINE | ID: covidwho-1166917

ABSTRACT

BACKGROUND: Risk scores are needed to predict the risk of death in severe coronavirus disease 2019 (COVID-19) patients in the context of rapid disease progression. METHODS: Using data from China (training dataset, n = 96), prediction models were developed by logistic regression and then risk scores were established. Leave-one-out cross validation was used for internal validation and data from Iran (test dataset, n = 43) was used for external validation. RESULTS: A NSL model (area under the curve (AUC) 0.932) and a NL model (AUC 0.903) were developed based on neutrophil percentage and lactate dehydrogenase with and without oxygen saturation (SaO2) using the training dataset. AUCs of the NSL and NL models in the test dataset were 0.910 and 0.871, respectively. The risk scoring systems corresponding to these two models were established. The AUCs of the NSL and NL scores in the training dataset were 0.928 and 0.901, respectively. At the optimal cut-off value of NSL score, the sensitivity and specificity were 94% and 82%, respectively. The sensitivity and specificity of NL score were 94% and 75%, respectively. CONCLUSIONS: These scores may be used to predict the risk of death in severe COVID-19 patients and the NL score could be used in regions where patients' SaO2 cannot be tested.


Subject(s)
COVID-19/mortality , Hospital Mortality , L-Lactate Dehydrogenase/blood , Models, Theoretical , Neutrophils/cytology , Oxygen/blood , Aged , COVID-19/therapy , China , Disease Progression , Female , Humans , Iran , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Assessment
7.
Expert Rev Vaccines ; 20(4): 375-383, 2021 04.
Article in English | MEDLINE | ID: covidwho-1160718

ABSTRACT

INTRODUCTION: Coronavirus Disease 2019 (COVID-19) poses a substantial threat to the lives of the elderly, especially those with neurodegenerative diseases, and vaccination against viral infections is recognized as an effective measure to reduce mortality. However, elderly patients with neurodegenerative diseases often suffer from abnormal immune function and take multiple medications, which may complicate the role of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines. Currently, there is no expert consensus on whether SARS-CoV-2 vaccines are suitable for patients with neurodegenerative diseases. AREAS COVERED: We searched Pubmed to conduct a systematic review of published studies, case reports, reviews, meta-analyses, and expert guidelines on the impact of SARS-CoV-2 on neurodegenerative diseases and the latest developments in COVID-19 vaccines. We also summarized the interaction between vaccines and age-related neurodegenerative diseases. The compatibility of future SARS-CoV-2 vaccines with neurodegenerative diseases is discussed. EXPERT OPINION: Vaccines enable the body to produce immunity by activating the body's immune response. The pathogenesis and treatment of neurodegenerative diseases is complex, and these diseases often involve abnormal immune function, which can substantially affect the safety and effectiveness of vaccines. In short, this article provides recommendations for the use of vaccine candidates in patients with neurodegenerative diseases.


Subject(s)
COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/adverse effects , COVID-19/epidemiology , COVID-19/prevention & control , Neurodegenerative Diseases/epidemiology , Aged , Aged, 80 and over , COVID-19/immunology , COVID-19 Vaccines/immunology , Humans , Neurodegenerative Diseases/immunology , Neurodegenerative Diseases/therapy , Treatment Outcome , Vaccines, Inactivated/administration & dosage , Vaccines, Inactivated/adverse effects , Vaccines, Inactivated/immunology
8.
Nat Commun ; 12(1): 1813, 2021 03 22.
Article in English | MEDLINE | ID: covidwho-1147224

ABSTRACT

Long-term antibody responses and neutralizing activities in response to SARS-CoV-2 infection are not yet clear. Here we quantify immunoglobulin M (IgM) and G (IgG) antibodies recognizing the SARS-CoV-2 receptor-binding domain (RBD) of the spike (S) or the nucleocapsid (N) protein, and neutralizing antibodies during a period of 6 months from COVID-19 disease onset in 349 symptomatic COVID-19 patients who were among the first be infected world-wide. The positivity rate and magnitude of IgM-S and IgG-N responses increase rapidly. High levels of IgM-S/N and IgG-S/N at 2-3 weeks after disease onset are associated with virus control and IgG-S titers correlate closely with the capacity to neutralize SARS-CoV-2. Although specific IgM-S/N become undetectable 12 weeks after disease onset in most patients, IgG-S/N titers have an intermediate contraction phase, but stabilize at relatively high levels over the 6 month observation period. At late time points, the positivity rates for binding and neutralizing SARS-CoV-2-specific antibodies are still >70%. These data indicate sustained humoral immunity in recovered patients who had symptomatic COVID-19, suggesting prolonged immunity.


Subject(s)
COVID-19/immunology , SARS-CoV-2/immunology , Adult , Aged , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Female , Humans , Immunity, Humoral/immunology , Immunoglobulin G/immunology , Immunoglobulin M/immunology , Male , Middle Aged , Severity of Illness Index , Spike Glycoprotein, Coronavirus
9.
Journal of Cleaner Production ; : 126561, 2021.
Article in English | ScienceDirect | ID: covidwho-1104024

ABSTRACT

The urban agglomeration of Yangtze River Delta (YRD) is symbol of China's rapid urbanization during the past decades. Urbanization can significantly impact land-cover properties, surface heating, and emissions of air pollutants. To control the spread of COVID-19, China imposed very rigorous restrictions, leading to dramatic reductions in air pollutants (except O3) from satellite and ground-based data. As such, inter-transportation of air pollutants was weak during the lockdown, which was conducive to discuss the impacts of urbanization on the air quality. During the lockdown, the rates of surface PM2.5, PM10, SO2, NO2 and CO reductions in different urban types ranged from 6.6% to 62.4% in the YRD. Urbanization exerted great impacts on the pollutant variations in urban agglomerations despite such large decreases in primary pollution in YRD. Lower values of AOD and tropospheric NO2 columns were noticeably observed over large cities during the lockdown. The extents of surface PM, SO2, NO2 and CO reductions in large cities (first-tier and second-tier) were found to be larger (4.7%-10.6%) than those in small-medium cities (third-tier and fourth-tier) during the lockdown, which was also the case for the extent of the increase (33.0% - 53.0%) in O3. PCA analysis revealed that the PM decreases in large cities made greater improvement in the air quality compared with the small cities during lockdown, while the urbanization had non-obvious influence on the photochemical reactions. It is imperative to adopt policies and programs to mitigate the air pollution in urban agglomerations in the fast urbanization process.

10.
Front Psychiatry ; 12: 554435, 2021.
Article in English | MEDLINE | ID: covidwho-1100067

ABSTRACT

Context: Since December 2019, more than 80,000 patients have been diagnosed with coronavirus disease 2019 (COVID-19) in China. Social support status of COVID-19 patients, especially the impact of social support on their psychological status and quality of life, needs to be addressed with increasing concern. Objectives: In this study, we used social support rating scale (SSRS) to investigate the social support in COVID-19 patients and nurses. Methods: The present study included 186 COVID-19 patients at a Wuhan mobile cabin hospital and 234 nurses at a Wuhan COVID-19 control center. Responses to a mobile phone app-based questionnaire about social support, anxiety, depression, and quality of life were recorded and evaluated. Results: COVID-19 patients scored significantly lower than nurses did on the Social Support Rating Scale (SSRS). Among these patients, 33.9% had anxiety symptoms, while 23.7% had depression symptoms. Overall SSRS, subjective social support scores and objective support scores of patients with anxiety were lower than those of patients without anxiety. This result was also found in depression. In addition, all dimensions of social support were positively correlated with quality of life. Interestingly, in all dimensions of social support, subjective support was found to be an independent predictive factor for anxiety, depression, and quality of life, whereas objective support was a predictive factor for quality of life, but not for anxiety and depression via regression analysis. Conclusion: Medical staffs should pay attention to the subjective feelings of patients and make COVID-19 patients feel respected, supported, and understood from the perspective of subjective support, which may greatly benefit patients, alleviate their anxiety and depression, and improve their quality of life.

14.
Ann Med ; 53(1): 181-188, 2021 12.
Article in English | MEDLINE | ID: covidwho-922329

ABSTRACT

OBJECTIVE: To illustrate the effect of corticosteroids and heparin, respectively, on coronavirus disease 2019 (COVID-19) patients' CD8+ T cells and D-dimer. METHODS: In this retrospective cohort study involving 866 participants diagnosed with COVID-19, patients were grouped by severity. Generalized additive models were established to explore the time-course association of representative parameters of coagulation, inflammation and immunity. Segmented regression was performed to examine the influence of corticosteroids and heparin upon CD8+ T cell and D-dimer, respectively. RESULTS: There were 541 moderate, 169 severe and 156 critically ill patients involved in the study. Synchronous changes of levels of NLR, D-dimer and CD8+ T cell in critically ill patients were observed. Administration of methylprednisolone before 14 DFS compared with those after 14 DFS (ß = 0.154%, 95% CI=(0, 0.302), p=.048) or a dose lower than 40 mg per day compared with those equals to 40 mg per day (ß = 0.163%, 95% CI=(0.027, 0.295), p=.020) significantly increased the rising rate of CD8+ T cell in 14-56 DFS. CONCLUSIONS: The parameters of coagulation, inflammation and immunity were longitudinally correlated, and an early low-dose corticosteroid treatment accelerated the regaining of CD8+ T cell to help battle against SARS-Cov-2 in critical cases of COVID-19.


Subject(s)
CD8-Positive T-Lymphocytes/drug effects , COVID-19/drug therapy , Glucocorticoids/administration & dosage , Inflammation/drug therapy , Adult , Aged , Aged, 80 and over , Blood Coagulation/drug effects , Blood Coagulation/immunology , CD8-Positive T-Lymphocytes/immunology , COVID-19/blood , COVID-19/diagnosis , COVID-19/immunology , Dose-Response Relationship, Drug , Female , Fibrin Fibrinogen Degradation Products/analysis , Fibrin Fibrinogen Degradation Products/immunology , Heparin/administration & dosage , Humans , Inflammation/blood , Inflammation/diagnosis , Inflammation/immunology , Linear Models , Longitudinal Studies , Lymphocyte Count , Male , Methylprednisolone/administration & dosage , Middle Aged , Models, Biological , Retrospective Studies , SARS-CoV-2/immunology , SARS-CoV-2/isolation & purification , Severity of Illness Index , Time Factors , Time-to-Treatment , Young Adult
15.
Journal of Data Science ; 18(3):409-432, 2020.
Article in English | Airiti Library | ID: covidwho-918465

ABSTRACT

We develop a health informatics toolbox that enables timely analysis and evaluation of the time-course dynamics of a range of infectious disease epidemics. As a case study, we examine the novel coronavirus (COVID-19) epidemic using the publicly available data from the China CDC. This toolbox is built upon a hierarchical epidemiological model in which two observed time series of daily proportions of infected and removed cases are generated from the underlying infection dynamics governed by a Markov Susceptible-Infectious-Removed (SIR) infectious disease process. We extend the SIR model to incorporate various types of time-varying quarantine protocols, including government-level 'macro' isolation policies and community-level 'micro' social distancing (e.g. self-isolation and self-quarantine) measures. We develop a calibration procedure for underreported infected cases. This toolbox provides forecasts, in both online and offline forms, as well as simulating the overall dynamics of the epidemic. An R software package is made available for the public, and examples on the use of this software are illustrated. Some possible extensions of our novel epidemiological models are discussed.

16.
J Environ Sci (China) ; 102: 110-122, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-779238

ABSTRACT

To control the spread of COVID-19, rigorous restrictions have been implemented in China, resulting in a great reduction in pollutant emissions. In this study, we evaluated the air quality in the Yangtze River Delta during the COVID-19 lockdown period using satellite and ground-based data, including particle matter (PM), trace gases, water-soluble ions (WSIs) and black carbon (BC). We found that the impacts of lockdown policy on air quality cannot be accurately assessed using MODIS aerosol optical depth (AOD) data, whereas the tropospheric nitrogen dioxide (NO2) vertical column density can well reflect the influences of these restrictions on human activities. Compared to the pre-COVID period, the PM2.5, PM10, NO2, carbon monoxide (CO), BC and WSIs during the lockdown in Suzhou were observed to decrease by 37.2%, 38.3%, 64.5%, 26.1%, 53.3% and 58.6%, respectively, while the sulfur dioxide (SO2) and ozone (O3) increased by 1.5% and 104.7%. The WSIs ranked in the order of NO3- > NH4+ > SO42- > Cl- > Ca2+ > K+ > Mg2+ > Na+ during the lockdown period. By comparisons with the ion concentrations during the pre-COVID period, we found that the ions NO3-, NH4+, SO42-, Cl-, Ca2+, K+ and Na+ decreased by 66.3%, 48.8%, 52.9%, 56.9%, 57.9% and 76.3%, respectively, during the lockdown, in contrast to Mg2+, which increased by 30.2%. The lockdown policy was found to have great impacts on the diurnal variations of Cl-, SO42-, Na+ and Ca2+.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Aerosols/analysis , Air Pollutants/analysis , Air Pollution/analysis , China , Communicable Disease Control , Environmental Monitoring , Humans , Particulate Matter/analysis , Rivers , SARS-CoV-2
17.
EBioMedicine ; 55: 102763, 2020 May.
Article in English | MEDLINE | ID: covidwho-72300

ABSTRACT

BACKGROUND: The dynamic changes of lymphocyte subsets and cytokines profiles of patients with novel coronavirus disease (COVID-19) and their correlation with the disease severity remain unclear. METHODS: Peripheral blood samples were longitudinally collected from 40 confirmed COVID-19 patients and examined for lymphocyte subsets by flow cytometry and cytokine profiles by specific immunoassays. FINDINGS: Of the 40 COVID-19 patients enrolled, 13 severe cases showed significant and sustained decreases in lymphocyte counts [0·6 (0·6-0·8)] but increases in neutrophil counts [4·7 (3·6-5·8)] than 27 mild cases [1.1 (0·8-1·4); 2·0 (1·5-2·9)]. Further analysis demonstrated significant decreases in the counts of T cells, especially CD8+ T cells, as well as increases in IL-6, IL-10, IL-2 and IFN-γ levels in the peripheral blood in the severe cases compared to those in the mild cases. T cell counts and cytokine levels in severe COVID-19 patients who survived the disease gradually recovered at later time points to levels that were comparable to those of the mild cases. Moreover, the neutrophil-to-lymphocyte ratio (NLR) (AUC=0·93) and neutrophil-to-CD8+ T cell ratio (N8R) (AUC =0·94) were identified as powerful prognostic factors affecting the prognosis for severe COVID-19. INTERPRETATION: The degree of lymphopenia and a proinflammatory cytokine storm is higher in severe COVID-19 patients than in mild cases, and is associated with the disease severity. N8R and NLR may serve as a useful prognostic factor for early identification of severe COVID-19 cases. FUNDING: The National Natural Science Foundation of China, the National Science and Technology Major Project, the Health Commission of Hubei Province, Huazhong University of Science and Technology, and the Medical Faculty of the University of Duisburg-Essen and Stiftung Universitaetsmedizin, Hospital Essen, Germany.


Subject(s)
Betacoronavirus/immunology , Coronavirus Infections/immunology , Cytokines/blood , Leukocyte Count , Lymphocyte Subsets/immunology , Pneumonia, Viral/immunology , Adult , Aged , CD8-Positive T-Lymphocytes/immunology , COVID-19 , China/epidemiology , Comorbidity , Coronavirus Infections/blood , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Cytokine Release Syndrome/etiology , Cytokine Release Syndrome/immunology , Female , Flow Cytometry , Humans , Lymphocyte Count , Lymphopenia/etiology , Male , Middle Aged , Neutrophils/immunology , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Prognosis , SARS-CoV-2 , Time Factors
18.
Brain Behav Immun ; 88: 916-919, 2020 08.
Article in English | MEDLINE | ID: covidwho-6139

ABSTRACT

Since December 2019, more than 79,000 people have been diagnosed with infection of the Corona Virus Disease 2019 (COVID-19). A large number of medical staff was sent to Wuhan city and Hubei province to aid COVID-19 control. Psychological stress, especially vicarious traumatization caused by the COVID-19 pandemic, should not be ignored. To address this concern, the study employed a total of 214 general public and 526 nurses (i.e., 234 front-line nurses and 292 non-front-line nurses) to evaluate vicarious traumatization scores via a mobile app-based questionnaire. Front-line nurses are engaged in the process of providing care for patients with COVID-19. The results showed that the vicarious traumatization scores for front-line nurses including scores for physiological and psychological responses, were significantly lower than those of non-front-line nurses (P < 0.001). Interestingly, the vicarious traumatization scores of the general public were significantly higher than those of the front-line nurses (P < 0.001); however, no statistical difference was observed compared to the scores of non-front-line nurses (P > 0.05). Therefore, increased attention should be paid to the psychological problems of the medical staff, especially non-front-line nurses, and general public under the situation of the spread and control of COVID-19. Early strategies that aim to prevent and treat vicarious traumatization in medical staff and general public are extremely necessary.


Subject(s)
Compassion Fatigue/epidemiology , Coronavirus Infections/epidemiology , Nurses/statistics & numerical data , Pneumonia, Viral/epidemiology , Adult , Betacoronavirus , COVID-19 , China/epidemiology , Compassion Fatigue/psychology , Coronavirus Infections/nursing , Female , Humans , Male , Nurses/psychology , Pandemics , Pneumonia, Viral/nursing , SARS-CoV-2 , Surveys and Questionnaires , Young Adult
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