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1.
Northwest Pharmaceutical Journal ; 37(2):36-43, 2022.
Article in Chinese | CAB Abstracts | ID: covidwho-1897787

ABSTRACT

Objective: To explore the active components and potential mechanism of Fangfeng Tongsheng Pills by using network pharmacology and molecular docking in the treatment of coronavirus disease 19(COVID-19). Methods The main chemical constituents and action targets of various medicines in Fangfeng Tongsheng Pills were collected via traditional Chinese medicine system pharmacology database and online analysis platform(TCMSP). The related targets of COVID-19 were collected by using GeneCards database, and the repeating parts with Fangfeng Tongsheng Pills were taken as the research targets. Cytoscape software was used to create a drug-target-disease network. The common target was imported into STRING database, and the protein-protein interaction network diagram was constructed by Cytoscape software. The GO(gene ontology) function enrichment analysis and Kyoto encyclopedia of genes and genomes(KEGG) pathway enrichment analysis were performed by DAVID to predict their mechanism. The core components of Fangfeng Tongsheng Pills were docked with the therapeutic target of COVID-19 by AutoDock software. Results A total of 224 active compounds and 696 active targets were screened from Fangfeng Tongsheng Pills, including 79 targets coincided with COVID-19, and 10 active compounds, i.e. quercetin, luteolin, kaempferol,beta-sitosterol, naringenin, etc., 23 effective targets, i.e. PTGS2, PTGS1, NOS2, F10, DPP4, etc. A total of 65 GO function enrichment analysis results and 101 KEGG pathway enrichment results were obtained, including inflammatory response, tumor necrosis factor(TNF) signaling pathway, hypoxia inducible factor-1(HIF-1) signaling pathway, vascular endothelial growth factors(VEGF) signaling pathway, toll-like receptors(TLRs) signaling pathway, phosphatidylinositol 3-kinase-protein kinase B(PI3K-Akt) signaling pathway, and mitogen-activated protein kinase(MAPK) signaling pathway. Conclusion The active components in Fangfeng Tongsheng Pills, such as beta-sitosterol, quercetin, luteolin, kaempferol and naringenin, can combine with SARS-Co V2-3CL hydrolase and ACE2, act on the key target [TNF, Caspase-3, mitogen-activated protein kinase(MAPK1), interleukin-6(IL-6), prostaglandin-endoperoxide synthase 2(PGTS2)] of TNF, HIF-1, VEGF, MAPK and toll-like receptor signaling pathway, and play the roles of anti-inflammation, immune regulation, anti-hypoxic stress and anti-virus infection, thus play a role in the treatment of COVID-19.

2.
J Med Virol ; 94(7): 3121-3132, 2022 Jul.
Article in English | MEDLINE | ID: covidwho-1750404

ABSTRACT

Growing evidence has shown that anti-COVID-19 nonpharmaceutical interventions (NPIs) can support prevention and control of various infectious diseases, including intestinal diseases. However, most studies focused on the short-term mitigating impact and neglected the dynamic impact over time. This study is aimed to investigate the dynamic impact of anti-COVID-19 NPIs on hand, foot, and mouth disease (HFMD) over time in Xi'an City, northwestern China. Based on the surveillance data of HFMD, meteorological and web search data, Bayesian Structural Time Series model and interrupted time series analysis were performed to quantitatively measure the impact of NPIs in sequent phases with different intensities and to predict the counterfactual number of HFMD cases. From 2013 to 2021, a total number of 172,898 HFMD cases were reported in Xi'an. In 2020, there appeared a significant decrease in HFMD incidence (-94.52%, 95% CI: -97.54% to -81.95%) in the first half of the year and the peak period shifted from June to October by a small margin of 6.74% compared to the previous years of 2013 to 2019. In 2021, the seasonality of HFMD incidence gradually returned to the bimodal temporal variation pattern with a significant average decline of 61.09%. In particular, the impact of NPIs on HFMD was more evident among young children (0-3 years), and the HFMD incidence reported in industrial areas had an unexpected increase of 51.71% in 2020 autumn and winter. Results suggested that both direct and indirect NPIs should be implemented as effective public health measures to reduce infectious disease and improve surveillance strategies, and HFMD incidence in Xi'an experienced a significant rebound to the previous seasonality after a prominent decline influenced by the anti-COVID-19 NPIs.


Subject(s)
COVID-19 , Communicable Diseases , Hand, Foot and Mouth Disease , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Child , Child, Preschool , China/epidemiology , Hand, Foot and Mouth Disease/epidemiology , Hand, Foot and Mouth Disease/prevention & control , Humans , Incidence , Seasons
3.
Chaos ; 32(3): 033104, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1747110

ABSTRACT

Mobility restriction is a crucial measure to control the transmission of the COVID-19. Research has shown that effective distance measured by the number of travelers instead of physical distance can capture and predict the transmission of the deadly virus. However, these efforts have been limited mainly to a single source of disease. Also, they have not been tested on finer spatial scales. Based on prior work of effective distances on the country level, we propose the multiple-source effective distance, a metric that captures the distance for the virus to propagate through the mobility network on the county level in the U.S. Then, we estimate how the change in the number of sources impacts the global mobility rate. Based on the findings, a new method is proposed to locate sources and estimate the arrival time of the virus. The new metric outperforms the original single-source effective distance in predicting the arrival time. Last, we select two potential sources and quantify the arrival time delay caused by the national emergency declaration. In doing so, we provide quantitative answers on the effectiveness of the national emergency declaration.


Subject(s)
COVID-19 , COVID-19/epidemiology , Humans
4.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325112

ABSTRACT

Objective: To investigate the prevalence of sleep quality and mental disturbances of medical staff and identify the effects of region, epidemic stage, and demographic characteristics during the COVID-19 outbreak in China. Method: Self-administered questionnaire were sent to health care workers (HCWs) in China from 30 Jan to 2 March, 2020. The Pittsburgh Sleep Quality Index, the Patient Health Questionare-9, the Generalized Anxiety Disorder-7 and the Impact of Event Scale were used to assess sleep quality, depression symptoms, anxiety symptoms and Post-traumatic stress disorder (PTSD) of HCWs, respectively. The influencing factors of psychological and sleep disturbances were identified by univariate analysis and multiple regression. Result The incidence of people getting depression, anxiety or PTSD symptoms were 11.6%,13.3%, 14.3%, respectively. HCWs in Hubei province experienced significantly poorer sleep quality (t=5.034, P<0.001). The predictors of sleep quality among HCWs were COVID-19 stage 2 (β=.135, p=.014) and 3 (β=.184, p=.001), female (β=.141, p=.003) and older age (β=.160, p=.001).Not working in Hubei province (β=-.264, P<0.001) showed to be a protective factor of sleep quality. The risk factors of depression symptoms were not working in Hubei province (OR=4.318, P<0.001), administrative and logistic staff and others (OR=3.538, p=.011), and higher PSQI score (OR=1.282, P<0.001). Having children (under-age: OR=.292, p=.001, grown-up: OR=.293, p=.042) was identified as a protective factor of having depression symptoms. Poor sleep quality showed to be the risk factor of anxiety and PTSD symptoms as well (both p<.001). Furthermore, administrative and logistic staff and others (OR=3.399, p=.006) were found to be the risk factor of PTSD symptoms among HCWs. Conclusion: HCWs had poorer sleep quality on stage 2and 3 of the outbreak. HCWs in Hubei had poorer sleep quality but lighter depression condition. gender, age, occupation and status of having children were associated with sleep and mental health. Mental health programs should be considered for HCWs especially those with specific characteristics. Key words COVID-19, Depression, Anxiety, PTSD, Sleep quality, Health care workers

5.
Sustainability ; 14(3):1856, 2022.
Article in English | ProQuest Central | ID: covidwho-1687025

ABSTRACT

Overwhelming remote communication episodes have become critical daily work demands for employees. On the basis of affective event theory, this study explores the effect of daily remote communication autonomy on positive affect and proactive work behaviors. We conducted a multilevel path analysis using a general survey, followed by experience sampling methodology, with a sample of 80 employees in China who completed surveys thrice daily over a two-week period. The results showed that daily remote communication autonomy increased positive affective reactions, which, in turn, enhanced proactive work behaviors on the same workday. Furthermore, positive day-level relationships leading to employee proactivity were only significant when the employees’ person-level general techno-workload was not high. The findings provide a new perspective for managing employees working under continuous techno-workload and demands for remote interactions.

7.
Open forum infectious diseases ; 8(Suppl 1):257-257, 2021.
Article in English | EuropePMC | ID: covidwho-1564251

ABSTRACT

Background Patients who are hospitalized with Coronavirus 2019 (COVID-19) are known to have increased risk for thrombosis. Several mechanisms have been proposed for increased thrombogenesis, including antiphospholipid antibodies (APLs). We sought to better understand the relationship between a commonly used marker of thrombosis, D-dimer, and antiphospholipid antibodies in relation to thrombosis in COVID-19. Methods This was a single-center prospective cohort study. Participants were adults admitted to the hospital with COVID-19 between March and December of 2020. Included patients required a positive COVID-19 nasopharyngeal nucleic acid amplification testing (NAAT), coagulation studies, and regular assessment of D-dimer levels. Patients who were excluded were pregnant adults, use of oral anticoagulants prior to admission, and absence of a positive COVID-19 nasopharyngeal NAAT. We tested 52 patients for antiphospholipid antibodies (APLs), including lupus anticoagulant (LA), anti-beta-2 glycoprotein antibodies (B2GP), and anti-cardiolipin antibodies (aCL). The endpoint for analysis was hospital discharge or development of a confirmed thrombosis. Results Twenty-nine of fifty-two patients (55.7%) with COVID-19 had non-negative APLs. Of these patients, twenty-seven (93.1%) had non-negative aCLs, the majority of which were IgM antibodies. There was a total of 7 thrombotic events in our cohort. The sensitivity of D-dimer alone was 85% and the sensitivity of APLs alone was 71%. In patients with an intermediate D-dimer level (i.e., greater than 2 milligrams per liter (mg/L) but less than 5 mg/L), the addition of non-negative APLs increased the sensitivity of D-dimer to 100%. In patients with a high D-dimer (i.e., greater than 5), the combined sensitivity of D-dimer and APLs was 60%. Out of the 7 thrombotic events in our cohort, two patients had negative APLs, however both patients had a D-dimer of greater than 5 mg/L. Conclusion The use of APLs can assist in risk-stratifying patients in an intermediate-risk D-dimer group to consider prophylactic anticoagulation if APLs are negative and to consider therapeutic anticoagulation if APLs are non-negative. In the high-risk group (i.e., a D-dimer greater than 5 mg/dL), a therapeutic anticoagulation approach may be more appropriate. Disclosures All Authors: No reported disclosures

8.
PLoS One ; 16(11): e0258868, 2021.
Article in English | MEDLINE | ID: covidwho-1505861

ABSTRACT

Human mobility is crucial to understand the transmission pattern of COVID-19 on spatially embedded geographic networks. This pattern seems unpredictable, and the propagation appears unstoppable, resulting in over 350,000 death tolls in the U.S. by the end of 2020. Here, we create the spatiotemporal inter-county mobility network using 10 TB (Terabytes) trajectory data of 30 million smart devices in the U.S. in the first six months of 2020. We investigate the bond percolation process by removing the weakly connected edges. As we increase the threshold, the mobility network nodes become less interconnected and thus experience surprisingly abrupt phase transitions. Despite the complex behaviors of the mobility network, we devised a novel approach to identify a small, manageable set of recurrent critical bridges, connecting the giant component and the second-largest component. These adaptive links, located across the United States, played a key role as valves connecting components in divisions and regions during the pandemic. Beyond, our numerical results unveil that network characteristics determine the critical thresholds and the bridge locations. The findings provide new insights into managing and controlling the connectivity of mobility networks during unprecedented disruptions. The work can also potentially offer practical future infectious diseases both globally and locally.


Subject(s)
COVID-19/mortality , COVID-19/transmission , Communicable Diseases/mortality , Communicable Diseases/transmission , Computer Simulation , Humans , Phase Transition , SARS-CoV-2/pathogenicity
9.
Front Psychiatry ; 12: 696200, 2021.
Article in English | MEDLINE | ID: covidwho-1332145

ABSTRACT

Objective: To investigate the prevalence of sleep quality and post-traumatic stress disorder (PTSD) symptoms of healthcare workers (HCWs) and identify the determinants for PTSD symptoms among HCWs in high-risk and low-risk areas during the COVID-19 outbreak in China. Methods: The Pittsburgh Sleep Quality Index and the Impact of Event Scale were used to assess sleep quality and symptoms of PTSD of 421 Chinese HCWs, respectively, from January 30 to March 2, 2020. The influencing factors of PTSD symptoms were identified by univariate analysis and multiple regression. Results: The incidence of HCWs getting PTSD symptoms were 13.2%. HCWs from high-risk areas had significantly poorer sleep quality (p < 0.001). Poor sleep quality was the risk factor of PTSD symptoms for HCWs from high-risk (p = 0.018) and low-risk areas (p < 0.001). Furthermore, non-medical staff were found to be the risk factor for PTSD symptoms only in low-risk areas. Discussion: HCWs in Hubei had poorer sleep quality. Non-medical HCWs from low-risk areas were associated with more severe PTSD symptoms. Mental health programs should be considered for HCWs, especially those who are often overlooked.

10.
JOM (1989) ; 73(8): 2332-2334, 2021.
Article in English | MEDLINE | ID: covidwho-1328650
11.
J Diabetes Res ; 2021: 5537110, 2021.
Article in English | MEDLINE | ID: covidwho-1192132

ABSTRACT

This study was aimed at exploring the predictive value of first-trimester glycosylated hemoglobin (HbA1c) levels in the diagnosis of gestational diabetes mellitus (GDM). A total of 744 pregnant women registered at the Peking University International Hospital between March 2017 and March 2019 were included in this study. Data on personal characteristics and biochemical indicators of the pregnant women were collected during the first trimester. The International Association of Diabetes and Pregnancy Study Groups has adopted specific diagnostic criteria as the gold standard for the diagnosis of GDM. Receiver operating characteristic (ROC) curve statistics were used to assess the predictive value of first-trimester HbA1c levels in the diagnosis of GDM. HbA1c levels in the first trimester were significantly higher in the GDM group than in the non-GDM group (5.23% ± 0.29% vs. 5.06 ± 0.28%, P < 0.05). The first-trimester HbA1c level was an independent risk factor for gestational diabetes. The area under the ROC curve (AUC) of HbA1c for GDM was 0.655 (95% confidence interval 0.620-0.689, P < 0.001). The positive likelihood ratio was the highest at HbA1c = 5.9%, sensitivity was 2.78, and specificity was 99.83%. There was no statistical difference in AUC between fasting blood glucose and HbA1c (P = 0.407). First-trimester HbA1c levels can be used to predict GDM. The risk of GDM was significantly increased in pregnant women with first-trimester HbA1c levels > 5.9%. There was no statistical difference between first-trimester HbA1c and fasting blood glucose levels in predicting GDM.


Subject(s)
Diabetes, Gestational/diagnosis , Glycated Hemoglobin A/metabolism , Pregnancy Trimester, First/blood , Adult , Beijing , Biomarkers/blood , Blood Glucose/metabolism , Diabetes, Gestational/blood , Female , Humans , Longitudinal Studies , Predictive Value of Tests , Pregnancy , Prospective Studies , Risk Factors , Up-Regulation
13.
Data Inf Manag ; 4(3): 130-147, 2020 Sep 01.
Article in English | MEDLINE | ID: covidwho-826331

ABSTRACT

The COVID-19 outbreak is a global pandemic declared by the World Health Organization, with rapidly increasing cases in most countries. A wide range of research is urgently needed for understanding the COVID-19 pandemic, such as transmissibility, geographic spreading, risk factors for infections, and economic impacts. Reliable data archive and sharing are essential to jump-start innovative research to combat COVID-19. This research is a collaborative and innovative effort in building such an archive, including the collection of various data resources relevant to COVID-19 research, such as daily cases, social media, population mobility, health facilities, climate, socioeconomic data, research articles, policy and regulation, and global news. Due to the heterogeneity between data sources, our effort also includes processing and integrating different datasets based on GIS (Geographic Information System) base maps to make them relatable and comparable. To keep the data files permanent, we published all open data to the Harvard Dataverse (https://dataverse.harvard.edu/dataverse/2019ncov), an online data management and sharing platform with a permanent Digital Object Identifier number for each dataset. Finally, preliminary studies are conducted based on the shared COVID-19 datasets and revealed different spatial transmission patterns among mainland China, Italy, and the United States.

14.
Med Nov Technol Devices ; 8: 100043, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-733699

ABSTRACT

Since human coronavirus (HCoVs) was first described in the 1960s, seven strains of respiratory human coronaviruses have emerged and caused human infections. After the emergence of severe acute respiratory syndrome coronavirus (SARS-CoV) and Middle East respiratory syndrome coronavirus (MERS-CoV), a pneumonia outbreak of coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2) has represented a pandemic threat to global public health in the 21st century. Without effectively prophylactic and therapeutic strategies including vaccines and antiviral drugs, these three coronaviruses have caused severe respiratory syndrome and high case-fatality rates around the world. In this review, we detail the emergence event, origin and reservoirs of all HCoVs, compare the differences with regard to structure and receptor usage, and summarize therapeutic strategies for COVID-19 that cause severe pneumonia and global pandemic.

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