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2.
Viruses ; 14(5):974, 2022.
Article in English | MDPI | ID: covidwho-1820426

ABSTRACT

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, SARS2) remains a great global health threat and demands identification of more effective and SARS2-targeted antiviral drugs, even with successful development of anti-SARS2 vaccines. Viral replicons have proven to be a rapid, safe, and readily scalable platform for high-throughput screening, identification, and evaluation of antiviral drugs against positive-stranded RNA viruses. In the study, we report a unique robust HIV long terminal repeat (LTR)/T7 dual-promoter-driven and dual-reporter firefly luciferase (fLuc) and green fluorescent protein (GFP)-expressing SARS2 replicon. The genomic organization of the replicon was designed with quite a few features that were to ensure the replication fidelity of the replicon, to maximize the expression of the full-length replicon, and to offer the monitoring flexibility of the replicon replication. We showed the success of the construction of the replicon and expression of reporter genes fLuc and GFP and SARS structural N from the replicon DNA or the RNA that was in vitro transcribed from the replicon DNA. We also showed detection of the negative-stranded genomic RNA (gRNA) and subgenomic RNA (sgRNA) intermediates, a hallmark of replication of positive-stranded RNA viruses from the replicon. Lastly, we showed that expression of the reporter genes, N gene, gRNA, and sgRNA from the replicon was sensitive to inhibition by Remdesivir. Taken together, our results support use of the replicon for identification of anti-SARS2 drugs and development of new anti-SARS strategies targeted at the step of virus replication.

4.
Med Phys ; 2022 Apr 09.
Article in English | MEDLINE | ID: covidwho-1782646

ABSTRACT

PURPOSE: COVID-19 has become a global pandemic and is still posing a severe health risk to the public. Accurate and efficient segmentation of pneumonia lesions in CT scans is vital for treatment decision-making. We proposed a novel unsupervised approach using cycle consistent generative adversarial network (cycle-GAN) which automates and accelerates the process of lesion delineation. METHOD: The workflow includes lung volume segmentation, healthy lung image synthesis, infected and healthy image subtraction, and binary lesion mask creation. The lung volume was first delineated using a pre-trained U-net and worked as the input for the following network. A cycle-GAN was developed to generate synthetic healthy lung CT images from infected lung images. After that, the pneumonia lesions are extracted by subtracting the synthetic healthy lung CT images from the infected lung CT images. A median filter and K-means clustering were then applied to contour the lesions. The auto segmentation approach was validated on three different datasets. RESULTS: The average Dice coefficient reached 0.666±0.178 on the three datasets. Especially, the dice reached 0.748±0.121 and 0.730±0.095, respectively, on two public datasets Coronacases and Radiopedia. Meanwhile, the average precision and sensitivity for lesion segmentation on the three datasets were 0.679±0.244 and 0.756±0.162. The performance is comparable to existing supervised segmentation networks and outperforms unsupervised ones. CONCLUSION: The proposed label-free segmentation method achieved high accuracy and efficiency in automatic COVID-19 lesion delineation. The segmentation result can serve as a baseline for further manual modification and a quality assurance tool for lesion diagnosis. Furthermore, due to its unsupervised nature, the result is not influenced by physicians' experience which otherwise is crucial for supervised methods. This article is protected by copyright. All rights reserved.

5.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-332273

ABSTRACT

ABSTRACT Background Identification of shared and divergent predictors of clinical severity across respiratory viruses may support clinical decision-making and resource planning in the context of a novel or re-emergent respiratory pathogen. Methods We conducted a retrospective cohort study to identify predictors of 30-day all-cause mortality following hospitalization with influenza (N=45,749;2011-09 to 2019-05), respiratory syncytial virus (RSV;N=24,345;2011-09 to 2019-04), or SARS-CoV-2 (N=8,988;2020-03 to 2020-12;pre-vaccine) using population-based health administrative data from Ontario, Canada. Multivariable modified Poisson regression was used to assess associations between potential predictors and mortality. We compared the direction, magnitude and confidence intervals of risk ratios to identify shared and divergent predictors of mortality. Results 3,186 (7.0%), 697 (2.9%) and 1,880 (20.9%) patients died within 30 days of hospital admission with influenza, RSV, and SARS-CoV-2, respectively. Common predictors of increased mortality included: older age, male sex, residence in a long-term care home, and chronic kidney disease. Positive associations between age and mortality were largest for patients with SARS-CoV-2. Few comorbidities were associated with mortality among patients with SARS-CoV-2 as compared to those with influenza or RSV. Conclusions Our findings may help identify patients at highest risk of illness secondary to a respiratory virus, anticipate hospital resource needs, and prioritize local preventions and therapeutics to communities with high prevalence of risk factors. Summary In this study of patients hospitalized with influenza, respiratory syncytial virus, and SARS-CoV-2, common predictors of mortality included: older age, male sex, residence in long-term care homes and chronic kidney disease. These predictors may support clinical- and systems-level decision making.

6.
BMC Infect Dis ; 22(1): 296, 2022 Mar 28.
Article in English | MEDLINE | ID: covidwho-1765439

ABSTRACT

BACKGROUND: The global pandemic of coronavirus disease 2019 (COVID-19) has attracted great public health efforts across the world. Few studies, however, have described the potential impact of these measures on other important infectious diseases. METHODS: The incidence of 19 major infectious diseases in Zhejiang Province was collected from the National Notifiable Infectious Disease Surveillance System from January 2017 to October 2020. The entire epidemic control phase was divided into three stages. The government deployed the first level response from 24 January to 2 March (the most rigorous measures). When the outbreak of COVID-19 was under control, the response level changed to the second level from 3 to 23 March, and then the third level response was implemented after 24 March. We compared the epidemiological characteristics of 19 major infectious diseases during different periods of the COVID-19 epidemic and previous years. RESULTS: A total of 1,814,881 cases of 19 infectious diseases were reported in Zhejiang from January 2017 to October 2020, resulting in an incidence rate of 8088.30 cases per 1,000,000 person-years. After the non-pharmaceutical intervention, the incidence of 19 infectious diseases dropped by 70.84%, from 9436.32 cases per 1,000,000 person-years to 2751.51 cases per 1,000,000 person-years, with the large decrease in the first response period of influenza. However, we observed that the daily incidence of severe fever with thrombocytopenia syndrome (SFTS) and leptospirosis increased slightly (from 1.11 cases per 1,000,000 person-years to 1.82 cases per 1,000,000 person-years for SFTS and 0.30 cases per 1,000,000 person-years to 1.24 cases per 1,000,000 person-years for leptospirosis). There was no significant difference in the distribution of epidemiological characteristic of most infectious diseases before and during the implementation of COVID-19 control measures. CONCLUSION: Our study summarizes the epidemiological characteristics of 19 infectious diseases and indicates that the rigorous control measures for COVID-19 are also effective for majority of infectious diseases.


Subject(s)
COVID-19 , Communicable Diseases , Epidemics , COVID-19/epidemiology , Communicable Diseases/epidemiology , Disease Outbreaks/prevention & control , Epidemics/prevention & control , Humans , Incidence
7.
Foods ; 11(7):908, 2022.
Article in English | MDPI | ID: covidwho-1762754

ABSTRACT

Since the outbreak of the coronavirus disease 2019 (COVID-19), political and academic circles have focused significant attention on stopping the chain of COVID-19 transmission. In particular outbreaks related to cold chain food (CCF) have been reported, and there remains a possibility that CCF can be a carrier. Based on CCF consumption and trade matrix data, here, the 'source';of COVID-19 transmission through CCF was analyzed using a complex network analysis method, informing the construction of a risk assessment model reflecting internal and external transmission dynamics. The model included the COVID-19 risk index, CCF consumption level, urbanization level, CCF trade quantity, and others. The risk level of COVID-19 transmission by CCF and the dominant risk types were analyzed at national and global scales as well as at the community level. The results were as follows. (1) The global CCF trade network is typically dominated by six core countries in six main communities, such as Indonesia, Argentina, Ukraine, Netherlands, and the USA. These locations are one of the highest sources of risk for COVID-19 transmission. (2) The risk of COVID-19 transmission by CCF in specific trade communities is higher than the global average, with the Netherlands–Germany community being at the highest level. There are eight European countries (i.e., Netherlands, Germany, Belgium, France, Spain, Britain, Italy, and Poland) and three American countries (namely the USA, Mexico, and Brazil) facing a very high level of COVID-19 transmission risk by CCF. (3) Of the countries, 62% are dominated by internal diffusion and 23% by external input risk. The countries with high comprehensive transmission risk mainly experience risks from external inputs. This study provides methods for tracing the source of virus transmission and provides a policy reference for preventing the chain of COVID-19 transmission by CCF and maintaining the security of the global food supply chain.

8.
J Travel Med ; 2022 Mar 09.
Article in English | MEDLINE | ID: covidwho-1735606

ABSTRACT

Our review found the effective reproduction number and basic reproduction number of the Omicron variant elicited 3.8 and 2.5 times higher transmissibility than the Delta variant respectively. The Omicron variant has an average basic and effective reproduction number of 8.2 and 3.6.

9.
Front Psychiatry ; 13: 804538, 2022.
Article in English | MEDLINE | ID: covidwho-1731852

ABSTRACT

Introduction: The B.1.617.2 (Delta) variant of SARS-COV-2 has caused a surge in COVID-19 cases worldwide, placing a great burden on the health care system under the zero-tolerance epidemic prevention policy in China. The present study aimed to investigate the prevalence of anxiety among health care workers during the spread of the SARS-CoV-2 Delta variant, and to discuss the mediating role of positive coping style between resilience and anxiety, and the moderating role of general self-efficacy. Method: Connor-Davidson Resilience scale (CD-RISC), Generalized Anxiety Disorder Scale (GAD-7), General Self-efficacy Scale (GSES) and Simplified Coping Style Questionnaire (SCSQ) were used in this cross-sectional study among 390 healthcare workers in Jiangsu Province, China. Mackinnon's four-step procedure was applied to test the mediation effect, and Hayes PROCESS macro was conducted to examine the moderated mediation model. Results: The prevalence of anxiety among Chinese healthcare workers during the spread of the SARS-CoV-2 Delta variant was 41.8%. Male, unmarried, childless and younger subjects reported higher levels of anxiety. Positive coping partially mediated the effect of resilience on anxiety among healthcare workers and the indirect effect was stronger with the increase of general self-efficacy. Conclusions: Anxiety was prevalent among healthcare workers during the spread of SARS-CoV-2 Delta variant. This research sheds new light on the potential mechanism underlying the association between resilience and anxiety and provides new insight into the prevention of anxiety among healthcare workers during the spread of the SARS-CoV-2 Delta variant.

10.
Academic Journal of Second Military Medical University ; 42(12):1449-1454, 2021.
Article in Chinese | GIM | ID: covidwho-1727026

ABSTRACT

Objective: To investigate the influence of negative emotions on risk perception in frontline medical staff at the early stage of coronavirus disease 2019 (COVID-19) outbreak.

12.
Atmosphere ; 13(2):174, 2022.
Article in English | ProQuest Central | ID: covidwho-1704199

ABSTRACT

In recent years, air pollution has received serious concerns from researchers, media, and the public sectors, but air pollution from agricultural production activities has not received enough attention. This paper focuses on agricultural air pollution in central China, which is aggravated by the ongoing rural labor migration trend. With a set of panel data released from Hubei and Hunan provinces in China, we adopt the mediating effect model to explore the relationship between rural labor migration and air pollution caused by agricultural activity in China. First, we use the inventory analysis method and principal component analysis method to calculate the comprehensive index of the air pollution of agriculture in 152 counties and districts from Hubei and Hunan provinces, and we empirically test the impact of labor migration on air pollution with a mediating effect model as well as carry out regional heterogeneity analysis on the pollution effect of these two provinces mentioned above. The analysis above indicates that the increase of labor migration has intensified the comprehensive index of air pollution caused by agricultural activity by changing the supply of labor force in the agricultural sector, the budget line of rural residents, and the scale of agricultural production and crop planting structure, but there is a difference in the indirect total effect between the two provinces mentioned above according to our regional heterogeneity analysis. This study is a necessary extension to studies on alleviating and controlling air pollution in China.

13.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315979

ABSTRACT

The COVID-19 outbreak greatly limited human activities and reduced primary emissions particularly from urban on-road vehicles, but coincided with Beijing experiencing pandemic haze, raising the public concerns of the validity and effectiveness of the imposed traffic policies to improve the air pollution. Here, we explored the relationship between local vehicle emissions and the winter haze in Beijing before and during the COVID-19 lockdown period based on an integrated analysis framework, which combines a real-time on-road emission inventory, in-situ air quality observations and a localized chemical transport modeling system. We found that traffic emissions decreased substantially affected by the pandemic, with a higher reduction for NOx (75.9%, 125.3 Mg/day) compared to VOCs (53.1%, 52.9 Mg/day). Unexpectedly, our results show that the imbalanced emission abatement of NOx and VOCs from vehicles led to a significant rise of the atmospheric oxidizing capacity in urban areas, but only resulting in modest increases in secondary aerosols due to the inadequate precursors. However, the enhanced oxidizing capacity in the surrounding regions greatly increased the secondary particles with relatively abundant precursors, which is mainly responsible for Beijing haze during the lockdown period. Our results indicate that the winter haze in Beijing was insensitive to the local vehicular emissions reduction due to the complicated nonlinear response of the fine particle and air pollutant emissions. We suggest mitigation policies should focus on accelerating VOC and NH3 emissions reduction and synchronously controlling regional sources to release the benefits on local traffic emission control.

14.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-313605

ABSTRACT

Objective: to analyze the early transmission dynamics, the government measures, and current situation of diagnosis and treatment for novel coronavirus infection pneumonia in Zhejiang province, china. Methods: We collected the daily number of newly confirmed novel coronavirus infection pneumonia (NCP) patients and the number of discharge patients by February 8 in Zhejiang province. We analyzed the characteristics, exposure history, and the clinical symptoms of NCP patients. Results: there were 1075 confirmed NCP patients and 173 discharge patients in Zhejiang province by February 8. The daily number of newly confirmed NCP patients got decreased since January 29 (27 patients on February 8), while the daily number of newly discharge NCP patients was increasing (46 patients on February 8). Before February 1, the imported NCP patients contained the most significant part of total NCP patients. And the local infection of NCP patients occupied the main reason. 77 patients needed to stay in ICU. 26 of 77 patients had greater life danger. Fortunately, no patient was dead, and no health care worker got the infection. At the same time, the government of Zhejiang province strictly restricted the movement of people to prevent the NCP from further spread. Conclusion: The early spread of NCP in Zhejiang province was speedy. After the government of Zhejiang province took strict measures to restrict the movement of people, the difficult situation of NCP got noticeable relief in Zhejiang province since February 1.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312582

ABSTRACT

Background: Health care workers (HCWs) fighting Coronavirus Disease 2019 (COVID-19) are not immune to fatigue. Self-efficacy has been suggested as a protective factor for fatigue. Nonetheless, less is known regarding the underlying mechanisms behind the association. This research aimed to explore the prevalence of fatigue among HCWs during the pandemic, investigate the mediating effect of posttraumatic stress disorder (PTSD) symptoms and moderating effect of negative coping in the association between self-efficacy and fatigue.Methods. The cross-sectional study employed a sample of 527 HCWs from Anhui Province, China. Self-efficacy, PTSD symptoms, negative coping and fatigue were measured by General Self-Efficacy Scale (GSES), PTSD Checklist-Civilian Version (PCL-C), Simplified Coping Style Questionnaire (CSCQ) and 14-item Fatigue Scale (FS-14) respectively.Results. The prevalence of fatigue among HCWs was 56.7%. The effect of self-efficacy on fatigue was partially mediated by PTSD symptoms. Additionally, negative coping moderated both the direct effect of self-efficacy on fatigue and the mediating effect of PTSD symptoms. As revealed by Johnson-Neyman technique, when the standard score of negative coping enhanced to 1.49 and over, the direct association between self-efficacy and fatigue was not significant. Likewise, the effect of self-efficacy on PTSD symptoms had no statistical significance when the standard score of negative coping was − 1.40 and lower.Conclusions. More than half HCWs suffer from fatigue during the COVID-19. For HCWs during the COVID-19 epidemic, especially those with higher levels of negative coping, it might be crucial to design program combining the enhancement of self-efficacy and interventions for PTSD to reduce fatigue.

16.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308265

ABSTRACT

Background: Since December 2019, the outbreak of COVID-19 has spread quickly and thumped many countries and regions. The epidemic of central China was under the spotlight and attracted much more attentions. However, there are few reports describing COVID-19 patients in the regions outside of Wuhan, which are undergoing the change from sporadic imported cases to community-acquired transmission. Methods: : The electronic medical records of 74 laboratory-confirmed patients of COVID-19 were retrospectively reviewed and analyzed. Their epidemiological, demographic, clinical and radiological characteristics were systematically summarized. The difference between severe patients and non-severe patients were also analyzed statistically. Results: : The 74 COVID-19 patients were composed of 4 (5.4%) mild patients, 56 (75.7%) common patients, 13 (17.6%) severe patients and 1 (1.4%) critical patient. 43 were male, and 31 were female, with the average age 48.1±17.5. No significant difference of susceptibility was observed between genders, and almost people with all age were susceptible to SARS-CoV-2 infection. Before Jan 26, only imported sporadic cases were observed. However, from that day onward, family cluster infection cases increased dramatically, up to 70.3% (52/74), which were mainly from 15 family. The incubation period spanned from 0 to 19 days, with the median 5, and 81.4% had symptom onset within 7 days. At admission, 31.1% of patients had underlying diseases and the most common underlying diseases were hypertension (13.5%) and diabetes (5.4%). The most common symptoms were fever (90.5%), cough (75.7%), fatigue (36.5%) and chest distress (32.4%). 36.5% and 16.2% of patients had leukopenia and lymphocytopenia. 43.2% of patients had increased C reactive protein (CRP), and 40.5% had higher erythrocyte sedimentation rate (ESR) and 21.6% had higher calcitonin. 74.3% of patients had obvious lesions in both lung lobes and 56.8% of lesions manifested as ground glass opacity. Compared with non-severe group, the severe/critical group were significantly older and had more underlying diseases. After treatment, all patients improved and were discharged. No medical professional infection and death case were reported. Conclusion: The epidemic of COVID-19 in Nanjing were mainly caused by family cluster infection. The entire prevalence and illness were much milder than those of Wuhan. The disease of COVID-19 could be controlled and cured.

17.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-326152

ABSTRACT

Background: Triage of patients is important to control the pandemic of coronavirus disease 2019 (COVID-19), especially during the peak of the pandemic when clinical resources become extremely limited. Purpose: To develop a method that automatically segments and quantifies lung and pneumonia lesions with synthetic chest CT and assess disease severity in COVID-19 patients. Materials and Methods: In this study, we incorporated data augmentation to generate synthetic chest CT images using public available datasets (285 datasets from "Lung Nodule Analysis 2016"). The synthetic images and masks were used to train a 2D U-net neural network and tested on 203 COVID-19 datasets to generate lung and lesion segmentations. Disease severity scores (DL: damage load;DS: damage score) were calculated based on the segmentations. Correlations between DL/DS and clinical lab tests were evaluated using Pearson's method. A p-value < 0.05 was considered as statistical significant. Results: Automatic lung and lesion segmentations were compared with manual annotations. For lung segmentation, the median values of dice similarity coefficient, Jaccard index and average surface distance, were 98.56%, 97.15% and 0.49 mm, respectively. The same metrics for lesion segmentation were 76.95%, 62.54% and 2.36 mm, respectively. Significant (p << 0.05) correlations were found between DL/DS and percentage lymphocytes tests, with r-values of -0.561 and -0.501, respectively. Conclusion: An AI system that based on thoracic radiographic and data augmentation was proposed to segment lung and lesions in COVID-19 patients. Correlations between imaging findings and clinical lab tests suggested the value of this system as a potential tool to assess disease severity of COVID-19.

19.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-325144

ABSTRACT

Background: Increasing evidence revealed that kidney was one of the targets of SARS-CoV-2. However, the incidences of kidney abnormalities were significantly different, from 0.5 to 75.4% in coronavirus disease 2019 (COVID-19) patients. The association of kidney injury with prognosis remain controversial. Methods: : In this retrospective cohort study, laboratory confirmedCOVID-19inpatients with severe type were enrolled. Demographic, clinicaland laboratory data were collected. Association of estimated glomerular fifiltration rate (eGFR)with 28-days mortality was analyzed. Results: : The total 28-days mortality of hospitalizationwas 22.3% (79/354). Non-survivors had a significantly declined eGFR levels than survivors (75.95 [IQR: 47.22,92.84] ml/min/1.73m 2 vs. 96.43 [IQR: 84.11,108.47] ml/min/1.73m 2 , P <0.001). The 28-days mortality in declined eGFR group (<90 ml/min/1.73m 2 ) was significantly higher than that in normal eGFR group (38.5% vs. 10.7%, P <0.001). Multivariate logistic regression revealed that the independent risk factors of 28-days outcome included lower eGFR (OR: 3.97, 95%CI: 1.42-11.11), elevated WBC (OR: 7.08, 95%CI: 3.15-15.90), lymphopenia (OR: 2.58, 95%CI: 1.21-5.49)andIL-6 (OR: 7.90, 95%CI: 2.19-28.49). Kaplan-Meier analysis indicated the survival disadvantage in patients with declined eGFR. ROC curve showed the eGFR cut-off value for predicting 28-days death was 82.2 μmol/L, with the sensitivity of 76.7% and speciality of 66.3%. Conclusion: Declined eGFR was associated with poor prognosis and could be used an independent risk factor of 28-days mortality in COVID-19 patients. Early detection and surveillance for eGFR may benefit to identify patients with high-risk ofprogression.

20.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325143

ABSTRACT

Objectives: Although the respiratory and immune systems are the major targets of SARS-CoV-2, increasing evidence revealed that kidney injury was not rare in coronavirus disease 2019 (COVID-19). However, the incidences of kidney abnormalities were significantly different, from 0.5 to 75.4% in several reports. The association of kidney injury with prognosis remain controversial. Methods: : In this retrospective single center cohort study, laboratory confirmedCOVID-19inpatients with severe type were enrolled. Demographic, clinicaland laboratory data were collected. Association ofserum creatinine (SCr)with 28-days mortality in severe COVID-19 patients was analyzed. Results: : 18.79% (48/304) patients died during the first 28-days of hospitalization.Non-survivors had a significantly higher SCr levels than survivors (109.27μmol/L vs. 69.99μmol/L, P <0.001). The 28-days mortality in high SCr group (>76μmol/L) was significantly higher than that in low SCr group (31.7% vs. 7.5%, P <0.001). Multivariate logistic regression revealed that the independent risk factors of 28-days outcome included age(OR: 2.95, 95%CI: 1.08-8.05), WBC (OR: 6.09, 95%CI: 2.27-6.39), lymphopenia (OR: 3.49, 95%CI: 1.55-7.92), IL-6 (OR: 4.44, 95%CI: 1.64-11.99) and SCr (OR: 2.69, 95%CI: 1.18-6.11). Kaplan-Meier analysis demonstrated the survival disadvantage in patients with high SCr levels (>76μmol/L). ROC curve showed the SCr cut-off value for predicting 28-days death was 77.5 μmol/L, with the sensitivity of 68.8% and speciality of 74.1%. Conclusion: SCr was associated with poor prognosis and might be an independent risk factor for in-hospital death. The cut-off value of SCr for prognosis prediction was 77.5 μmol/L, with the sensitivity of 68.8% and speciality of 74.1%.

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