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Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio OR=5.618, 95% confidence interval CI) 2.136-14.776, P0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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We employed publicly available user-generated content (UGC) data from the website Tripadvisor and developed an autoregressive integrated moving average (ARIMA) model using the R language to analyze the seasonality of the use of urban green space (UGS) in Okinawa under normal conditions and during the COVID-19 pandemic. The seasonality of the use of ocean-area UGS is primarily influenced by climatic factors, with the peak season occurring from April to October and the off-peak season from November to March. Conversely, the seasonality of the use of non-ocean-area UGS remains fairly stable throughout the year, with a relatively high number of visitors in January and May. The outbreak of the COVID-19 pandemic greatly impacted visitor enthusiasm for travel, resulting in significantly fewer actual postings compared with predictions. During the outbreak, use of ocean-area UGS was severely restricted, resulting in even fewer postings and a negative correlation with the number of new cases. In contrast, for non-ocean-area UGS, a positive correlation was observed between the change in postings and the number of new cases. We offer several suggestions to develop UGS management in Okinawa, considering the opportunity for a period of recovery for the tourism industry.
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The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the reso-lution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images;and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at x3 SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.
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Objective To explore the sociodemographic and psychological factors influencing the continuity of treatment of patients with chronic kidney disease under the regular epidemic prevention and control of coronavirus disease 2019 (COVID-19). Methods A total of 277 patients with chronic kidney disease who were admitted to Department of Nephrology, The First Affiliated Hospital of Naval Medical University (Second Military Medical University) from Apr. 2020 to Mar. 2021 were enrolled and divided into 3 groups: non-dialysis group (n=102), hemodialysis (HD) group (n=108), and peritoneal dialysis (PD) group (n=67). All patients were investigated by online and offline questionnaires, including self-designed basic situation questionnaire, self-rating anxiety scale (SAS), and self-rating depression scale (SDS). The general sociodemographic data, anxiety and depression of the 3 groups were compared, and the influence of sociodemographic and psychological factors on the interruption or delay of treatment was analyzed by binary logistic regression model. Results There were significant differences in age distribution, marital status, occupation, medical insurance type, caregiver type, whether there was an urgent need for hospitalization and whether treatment was delayed or interrupted among the 3 groups (all P<0.05). The average SAS score of 65 PD patients was 38.15+/-15.83, including 53 (81.5%) patients without anxiety, 7 (10.8%) patients with mild anxiety, and 5 (7.7%) patients with moderate to severe anxiety. The average SAS score of 104 patients in the HD group was 36.86+/-14.03, including 81 (77.9%) patients without anxiety, 18 (17.3%) patients with mild anxiety, and 5 (4.8%) patients with moderate to severe anxiety. There were no significant differences in the mean score of SAS or anxiety severity grading between the 2 groups (both P>0.05). The mean SDS scores of 65 PD patients were 53.42+/-13.30, including 22 (33.8%) patients without depression, 21 (32.3%) patients with mild depression, and 22 (33.8%) patients with moderate to severe depression. The mean SDS scores of 104 patients in the HD group were 50.79+/-10.76, including 36 (34.6%) patients without depression, 56 (53.8%) patients with mild depression, and 12 (11.6%) patients with moderate to severe depression. There were no significant differences in mean SDS scores or depression severity grading between the 2 groups (both P>0.05). The results of intra-group comparison showed that the incidence and severity of depression were higher than those of anxiety in both groups. Multivariate binary logistic regression analysis showed that high school education level (odds ratio [OR]=5.618, 95% confidence interval [CI]) 2.136-14.776, P<0.01), and unmarried (OR=6.916, 95% CI 1.441-33.185, P=0.016), divorced (OR= 5.588, 95% CI 1.442-21.664, P=0.013), urgent need for hospitalization (OR=8.655, 95% CI 3.847-19.476, P<0.01) could positively promote the continuity of treatment in maintenance dialysis patients under the regular epidemic prevention and control of COVID-19. In the non-dialysis group, no sociodemographic and psychological factors were found to be associated with the interruption or delay of treatment (P>0.05). Conclusion Education, marital status, and urgent need for hospitalization are correlated with the continuity of treatment in patients with chronic kidney disease on maintenance dialysis.Copyright © 2022, Second Military Medical University Press. All rights reserved.
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Determining the optimal vehicle routing of emergency material distribution (VREMD) is one of the core issues of emergency management, which is strategically important to improve the effectiveness of emergency response and thus reduce the negative impact of large-scale emergency events. To summarize the latest research progress, we collected 511 VREMD-related articles published from 2010 to the present from the Scopus database and conducted a bibliometric analysis using VOSviewer software. Subsequently, we cautiously selected 49 articles from these publications for system review;sorted out the latest research progress in model construction and solution algorithms;and summarized the evolution trend of keywords, research gaps, and future works. The results show that do -mestic scholars and research organizations held an unqualified advantage regarding the number of published papers. However, these organizations with the most publications performed poorly regarding the number of literature citations. China and the US have contributed the vast majority of the literature, and there are close collaborations between researchers from both countries. The optimization model of VREMD can be divided into single-, multi-, and joint-objective models. The shortest travel time is the most common optimization objective in the single-objective optimization model. Several scholars focus on multiobjective optimization models to consider conflicting objectives simultaneously. In recent literature, scholars have focused on the impact of uncertainty and special events (e.g., COVID-19) on VREMD. Moreover, some scholars focus on joint optimization models to optimize vehicle routes and central locations (or material allocation) simultaneously. So-lution algorithms can be divided into two primary categories, i.e., mathematical planning methods and intelligent evolutionary algorithms. The branch and bound algorithm is the most dominant mathematical planning algorithm, while genetic algorithms and their enhancements are the most commonly used intelligent evolutionary algorithms. It is shown that the nondominated sorting genetic algorithm II (NSGA-II) can effectively solve the multiobjective model of VREMD. To further improve the algorithm's performance, re-searchers have proposed improved hybrid intelligent algorithms that combine the ad-vantages of NSGA-II and certain other algorithms. Scholars have also proposed a series of optimization algorithms for specific scenarios. With the development of new technologies and computation methods, it will be exciting to construct optimization models that consider uncertainty, heterogeneity, and temporality for large-scale real-world issues and develop generalized solution approaches rather than those applicable to specific scenarios.(c) 2022 Periodical Offices of Chang'an University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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Background: Fever is a common clinical manifestation of COVID-19 infection. Fever has also been associated with unmasking Brugada pattern ECG in patients and may result in life-threatening arrhythmia. Little is known regarding COVID-19 associated Brugada pattern ECG. There is paucity of data and guidance in how to manage these patients. Method(s): To identify all published case reports, the latest Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was followed. A literature search was conducted using PubMed, EMBASE, and Scopus through September 2021. A systematic review was performed to identify the incidence, clinical characteristics, and management outcomes of COVID-19 patients with a Brugada pattern ECG. Result(s): A total of 18 cases were collected. The mean age was 47.1 years and 11.1% were women. No patient had prior confirmed diagnosis of Brugada syndrome. The most common presenting clinical symptoms were fever (83.3%), chest pain (38.8%), shortness of breath (38.8%), and syncope (16.6%). All 18 patients presented with type 1 Brugada pattern ECG. Four patients (22.2%) underwent left heart catheterization, and none demonstrated the presence of obstructive coronary disease. The most common reported therapies included antipyretics (55.5%), hydroxychloroquine (27.7%), and antibiotics (16.6%). One patient (5.5%) died during hospitalization. Three patients (16.6%) who presented with syncope received either an implantable cardioverter defibrillator or wearable cardioverter defibrillator at discharge. At follow up, thirteen patients (72.2%) had resolution of type 1 Brugada pattern ECG. Conclusion(s): COVID-19 associated Brugada pattern ECG is rare. Most patients may see resolution of the ECG pattern once their symptoms have improved. Increased awareness and timely use of antipyretics is warranted in this population.
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COVID-19 opened a window of opportunity to change the green development of the hospitality industry. For many years, Chinese tourists have been the world's largest source of outbound tourists. Therefore, this study attempted to improve built-environment strategies for green rooms at B&Bs using the empirical statistics of Chinese tourists after the end of COVID-19 control measures and different green B&B standards, combining IPA (importance-performance analysis). For the lack of a green built-environment study from a tourism perspective, this study can be used mainly for improving the green satisfaction of urban B&Bs as it attempted to fill the gaps in research on green B&B rooms. This study will significantly help improve the quality of green rooms for the B&B industry in the future, and it also provides an improved green B&B room sample for other countries and regions. Moreover, it is an optimistic attempt at hospitality and tourism recovery. © 2023 by the authors.
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In the era of "Post-epidemic" and "Dual-carbon targets", the focus of research on China's carbon trading market has changed from basic framework design to problem solving and development paths in the process of practice. Foreign carbon trading markets have developed for many years, and have experienced the financial crisis and the impact of the coronavirus epidemic. By analyzing the important problems and countermeasures encountered in the process of carbon trading market by representative organizations such as EU, USA, New Zealand, Korea and Japan, the valuable experience and reference significance of foreign carbon trading practice were summarized. At the same time, comparing the similarities and differences between Chinese and foreign carbon trading national conditions, and taking into account the current development of China's carbon trading market, this paper put forward some carbon trading strategies with Chinese characteristics and absorbing foreign advanced experience, such as choosing appropriate emission caps, balancing regulation, formulating price stabilization mechanism, and leaving interfaces for international cooperation. © 2023 Research Institute of Petroleum Processing, SINOPEC. All rights reserved.
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China's wolf warrior diplomacy has attracted worldwide attention since April 2020. There are discussions about the potential negative effects on the Chinese economy. Based on weekly Google Trends data during April 2020 to February 2022, this study creatively created a 'wolf warrior diplomacy index' used as a proxy measuring the aggressiveness or assertiveness of Chinese foreign policy. Using an exponential generalised autoregressive conditional heteroskedastic model, this study finds that the effects of the wolf warrior diplomacy index on the Chinese stock markets, i.e., a proxy variable for the Chinese economy, are insignificant. Various robustness tests and fundamental data also support this conclusion. The implication is that, while a country's foreign policy may potentially impact its economy, its decisive force may be primarily fundamental factors. Copyright © 2023 Inderscience Enterprises Ltd.
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It was to explore the clinical characteristics of late pregnant women with asymptomatic infection of coronavirus disease 2019 (COVID-19) and the risk of intrauterine vertical transmission and breastfeeding transmission. The clinical data of a late pregnant woman with COVID-19 were retrospectively analyzed. The patient (singleton, cephalic) was admitted to the hospital on April 3, 2022. The patient had a dramatic increase in C-reactive protein after delivery, other blood routine tests were unremarkable, and the result of nucleic acid test was positive. On April 13, 2022, due to oligohydramnios, under measures such as positive pressure headgear and protective clothing in negative pressure operating room, second cesarean section combined with hysterorrhaphy (emergency) was performed to terminate the pregnancy, and the mother and baby were in good condition. Postpartum amniotic fluid, milk, and neonatal nucleic acid tests were negative. Corresponding treatment was given after cesarean section, and the patient was continuously monitored for nucleic acid detection to meet the discharge criteria of the COVID-19 and discharged and isolated. After discharge, the patient was followed up for 1 month. The newborn's spirit, diet, and development were normal. The maternal cesarean section incision recovered well. Patient with COVID-19 in the third trimester has prolonged hospital stays and are difficult to treat. However, the virus was not found in amniotic fluid, breast milk, and newborn, for which COVID-19 does not lead to intrauterine vertical transmission and breastfeeding transmission in the third trimester.Copyright © 2023 by the authors.
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The medical conversational system can relieve doctors' burden and improve healthcare effi-ciency, especially during the COVID-19 pan-demic. However, the existing medical dialogue systems have die problems of weak scalability, insufficient knowledge, and poor controlla-bility. Thus, we propose a medical conversa-tional question-answering (CQA) system based on the knowledge graph, namely MedConQA, which is designed as a pipeline framework to maintain high flexibility. Our system utilizes automated medical procedures, including medi-cal triage, consultation, image-text drug recom-mendation, and record. Each module has been open-sourced as a tool, which can be used alone or in combination, with robust scalability. Besides, to conduct knowledge-grounded dia-logues with users, we first construct a Chinese Medical Knowledge Graph (CMKG) and col-lect a large-scale Chinese Medical CQA (CM-CQA) dataset, and we design a series of meth-ods for reasoning more intellectually. Finally, we use several state-of-the-art (SOTA) tech-niques to keep the final generated response more controllable, which is further assured by hospital and professional evaluations. We have open-sourced related code, datasets, web pages, and tools, hoping to advance future research. © 2022 Association for Computational Linguistics.
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In the era of "Post-epidemic" and "Dual-carbon targets", the focus of research on China's carbon trading market has changed from basic framework design to problem solving and development paths in the process of practice. Foreign carbon trading markets have developed for many years, and have experienced the financial crisis and the impact of the coronavirus epidemic. By analyzing the important problems and countermeasures encountered in the process of carbon trading market by representative organizations such as EU, USA, New Zealand, Korea and Japan, the valuable experience and reference significance of foreign carbon trading practice were summarized. At the same time, comparing the similarities and differences between Chinese and foreign carbon trading national conditions, and taking into account the current development of China's carbon trading market, this paper put forward some carbon trading strategies with Chinese characteristics and absorbing foreign advanced experience, such as choosing appropriate emission caps, balancing regulation, formulating price stabilization mechanism, and leaving interfaces for international cooperation. © 2023 Research Institute of Petroleum Processing, SINOPEC. All rights reserved.
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The operation of the regional logistics network is often interrupted by emergencies such as rainstorms and earthquakes, especially the COVID-19 pandemic in recent years. Therefore, it is particularly important to improve the toughness of the regional logistics network to resist the risk of emergencies. This paper firstly constructed a multi-layered weighted regional logistics network of highways and railways in the central region of China based on the gravity model, analyzed its network structure characteristics by using dominant flow and social network analysis methods, then simulated the evolution trend of network toughness under different strategies. Finally, the optimization model of logistics network structural toughness under fixed cost was proposed to explore the optimization path of network structural toughness. The results show that: (1) The economically developed cities are located in the core area of the regional logistics network, on the contrary, they are located in the edge area of the regional logistics network. (2) The network as a whole has formed a "two main and four auxiliary” distribution pattern with Zhengzhou and Wuhan as the two main cores in the north and south, and Taiyuan, Hefei, Changsha, and Nanchang as the four auxiliary cores. (3) The network has higher toughness under the node random order failure strategy than under the node specified order failure strategy, and the optimization plans improve the structural toughness of the regional logistics network by 11.68%. © 2022 SPIE.
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We use large eddy simulations to investigate the puff and droplet dynamics from violent expiratory events such as coughs and sneezes in the first few seconds following an ejection. For each of the eleven simulations considered, over 60,000 droplets are ejected and individually tracked using the point-particle Euler–Lagrange approach. We test the sensitivity of the puff and droplet dynamics to various parameters including the ejection volume, momentum, and orientation. We also explore the effect of the mouth shape on the aforementioned dynamics by considering elliptical and circular inlet cross-sections. The results from the simulations compare favorably with a recent theoretical framework put forth by Balachandar et al. (2020) in terms of the puff size and propagation velocity. More importantly however, the theory is able to accurately predict the number and size spectra of the potentially virus-laden droplet nuclei that remain airborne within the puff. We observe that the ejection angle and mouth shape do not significantly affect the puff and droplet dynamics. Additionally, we quantify the carrying capacity of the detached puff portions in terms of the number and size spectra of droplets/droplet nuclei suspended within. © 2022 Elsevier Ltd
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Using Asian Critical Race Theory and Resilience Theory, this qualitative study explores how Asian international college students experienced racism before and after the eruption of the COVID-19 pandemic and how they developed and used resilience to counteract that racism. Eleven Asian participants shared their counter-narratives through semi-structured interviews. Results reveal that, before the pandemic, participants were regularly subjected to racist acts and attitudes grounded in a deficit view of Asians that treated them as inscrutable foreigners, blamed them as individuals for perceived shortcomings in their home countries, dismissed their expertise outside of technical STEM fields, and failed to recognize their abilities in creative and leadership roles. During the pandemic, the racist acts and attitudes experienced by Asian international college students greatly exacerbated the unprecedented challenges of isolation, limited access to university space and resources, and financial and physical insecurity caused by the pandemic. Results also indicate that Asian international students developed resilience grounded on their life experiences and community assets to counteract racism.
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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cause severe outbreak of coronavirus disease 2019 (COVID-19). Even though vaccination, the spread of SARS-CoV-2 is still continue. It is urgent to have a model that can efficiently evaluate potential therapeutic agents to counteract SARS-CoV-2 infection. Iron is an essential molecule for maintaining homeostasis. Supplement of iron significantly to affect virus infection. But the detailed mechanisms of iron on regulating SARS-CoV-2 infection are still unveiled. The three-dimensional (3D) model is a promising system for drug screening and disease progression analysis. Organoid is a typical 3D culture system that recapitulates genetic characteristics and phenotypic features of organs within body. Vasculature is prevalent for all various organs or tumors in the body which transport nutrients, oxygen and metabolites to maintain cellular homeostasis. Thus, we have established a 3D model of vascularized organoid to evaluate the effects of iron on infectivity of SARS-CoV-2 pseudovirus to provide the novel therapeutic strategy in coping SARS-CoV-2 infection. © 2022 IEEE.
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INTRODUCTION: Glycemic control is an important component of quality improvement bundles within the ICU. Dysglycemia among intensive care unit (ICU) patients has been associated with greater morbidity and mortality. The COVID-19 pandemic has been shown to influence hypoglycemia in patients presenting to the emergency department. The purpose of this study is to evaluate risk factors for dysglycemia during the COVID-19 pandemic in critically ill ICU patients on subcutaneous insulin. METHOD(S): Single-center, retrospective quality improvement study of adult critically ill patients admitted to the ICU in 2020. Patients were included if they were on subcutaneous insulin and primarily managed by an intensive care unit multidisciplinary team. Patients were excluded with active endocrinology consultation or receiving intravenous insulin infusion. Rates of hyperglycemia (blood glucose (BG) greater than or equal to 180 mg/dL), severe hyperglycemia (BG > 300 mg/dL), hypoglycemia (less than or equal to 70 mg/dL), or severe hypoglycemia (BG < 54 mg/dL) were evaluated. Basic patient demographics, including history of diabetes, steroid use, COVID-19 diagnosis were obtained. Regression analysis was performed adjusting for age, past medical history of diabetes, use of corticosteroid medications, COVID-19 diagnosis and use of a self-adjusting insulin calculator. RESULT(S): There were 244 adult ICU patients and 2,198 patient days evaluated in this study. History of diabetes was associated with greater odds of hyperglycemia (odds ratio (OR) 2.09 (1.57-2.78), p< 0.01), severe hyperglycemia (OR 1.82 (1.02-3.24), p=0.04), and lower risk for severe hypoglycemia (OR 0.24 (0.07-0.81), p=0.02). Corticosteroid use was associated with greater risk of hyperglycemia (OR 3.04 (2.31-3.99), p< 0.01) and severe hyperglycemia (OR 4.54 (2.59-7.95), p< 0.01), with no significant difference in hypoglycemia. COVID-19 diagnosis was associated with greater hyperglycemia (OR 1.49 (1.11-2), p=0.007) and hypoglycemia (OR 3.93 (1.32-11.73), p=0.01). CONCLUSION(S): In our quality improvement analysis, dysglycemia was found to be more prevalent in patients with corticosteroid use, history of diabetes and patients with a COVID-19 diagnosis. Larger studies would be beneficial to confirm these results.
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China's wolf warrior diplomacy has attracted extensive attention since 2020. One of the most prominent "wolf warriors"is Zhao Lijian, China's Ministry of Foreign Affairs spokesperson. Based on weekly Google Trends datasets between August 21, 2016 and August 8, 2021, this study provides a quantitative description of the development of Zhao Lijian diplomacy. Employing Granger causality tests and autoregressive distributed lag models, this study finds that Zhao Lijian diplomacy is part of China's wolf warrior diplomacy. Most importantly, COVID-19 may be the only factor that has driven the rise of Zhao Lijian diplomacy. This study contributes to academia by presenting a new quantitative approach to international relations studies and contributes to our understanding of China's foreign policy. © 2022 by Kerry Liu.
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Aim To elucidate the effective components of Ganoderma applanatum and its mechanism of preventing the coronavirus disease 2019(COVID-19).Methods To begin with, UHPLC-Q-Exactive-Orbitrap-MS was established to identify the main chemical constituents of G.applanatum.Then, the predicted targets of G.applanatum were selected by Swiss Target Prediction.GO analysis and KEGG analysis of core target genes were performed using the DAVID database.Finally, to explore the potential mechanism of G.applanatum against COVID-19, core functional components-core target-metabolism path network diagram was constructed using Cytoscape 3.8.0, and molecular docking was used to analyze the binding force of the core effective compounds with angiotensin-converting enzyme II(ACE2)and three SARS CoV-2 proteins, nonstructural protein-15 Endoribonuclease(NSP15), the receptor-binding domain of spike protein(RBD of S protein), and main protease(Mpro/3CLpro).Results Sixty-two components were identified from G.applanatum by UHPLC-Q-Exactive-Orbitrap-MS study;30 active components were closely associated with 32 core targets including IL6, PTGS2, and MAPK1;KEGG analysis showed that it might treat COVID-19 through signaling pathways, such as PI3K-Akt signaling pathway, TNF signaling pathway, tuberculosis, and so on;molecular docking analysis showed that 1,4-Dihydroxy-2-naphthoic acid, parthenolide, 7,8-Dihydroxycoumarin, and other vital compounds had a certain degree of affinity with ACE2 and three SARS CoV-2 proteins.Conclusion This study clarifies the chemical composition and the potential mechanism of G.applanatum, providing a scientific basis for screening the effective ingredients of G.applanatum. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.