Can internet concern about COVID-19 help predict stock markets: new evidence from high-concern and low-concern periods

The unprecedented outbreak of Corona Virus Disease 2019 (COVID-19) has resulted in extreme volatility in stock markets. This study mainly examines the predictive ability of the Internet concern about COVID-19 on stock index returns, based on the framework of GARCH type models. Instead of using the whole sample period, we divide the Internet concern about COVID-19 into high-concern and low-concern periods by breakpoint test method and then examine its predictive ability for stock returns in different periods, respectively. Using stock indexes of 10 countries and abnormal Google search volume of 'coronavirus' as study samples, the results reveal that (1) the Internet concern about COVID-19 has a negative impact on the stock index returns in the whole and high-concern periods, while its influence in the low-concern period is mixed;(2) the Internet concern about COVID-19 improves the prediction accuracy of stock index returns in the high-concern period, while seems to lose its powerful predictive ability in the whole and low-concern periods.

Emotion Analysis and Detection during COVID-19

Understanding emotions that people express during large-scale crises helps inform policy makers and first responders about the emotional states of the population as well as provide emotional support to those who need such support. We present COVIDEMO, a dataset of similar to 3,000 English tweets labeled with emotions and temporally distributed across 18 months. Our analyses reveal the emotional toll caused by COVID-19, and changes of the social narrative and associated emotions over time. Motivated by the time-sensitive nature of crises and the cost of large-scale annotation efforts, we examine how well large pre-trained language models generalize across domains and timeline in the task of perceived emotion prediction in the context of COVID-19. Our analyses suggest that cross-domain information transfers occur, yet there are still significant gaps. We propose semi-supervised learning as a way to bridge this gap, obtaining significantly better performance using unlabeled data from the target domain. We make our code and data available at https://github.com/tsosea2/CovidEmo.

Why Do You Feel This Way? Summarizing Triggers of Emotions in Social Media Posts

Crises such as the COVID-19 pandemic continuously threaten our world and emotionally affect billions of people worldwide in distinct ways. Understanding the triggers leading to people's emotions is of crucial importance. Social media posts can be a good source of such analysis, yet these texts tend to be charged with multiple emotions, with triggers scattering across multiple sentences. This paper takes a novel angle, namely, emotion detection and trigger summarization, aiming to both detect perceived emotions in text, and summarize events and their appraisals that trigger each emotion. To support this goal, we introduce COVIDET (Emotions and their Triggers during Covid-19), a dataset of ~1, 900 English Reddit posts related to COVID-19, which contains manual annotations of perceived emotions and abstractive summaries of their triggers described in the post. We develop strong baselines to jointly detect emotions and summarize emotion triggers. Our analyses show that COVIDET presents new challenges in emotion-specific summarization, as well as multi-emotion detection in long social media posts. © 2022 Association for Computational Linguistics.

Fast and direct identification of SARS-CoV-2 variants via 2D InSe field-effect transistors

As the COVID-19 pandemic evolves and new variants emerge, the development of more efficient identification approaches of variants is urgent to prevent continuous outbreaks of SARS-CoV-2. Field-effect transistors (FETs) with two-dimensional (2D) materials are viable platforms for the detection of virus nucleic acids (NAs) but cannot yet provide accurate information on NA variations. Herein, 2D Indium selenide (InSe) FETs were used to identify SARS-CoV-2 variants. The device's mobility and stability were ensured by atomic layer deposition (ALD) of Al2O3. The resulting FETs exhibited sub-fM detection limits ranging from 10(-14) M to 10(-)(8) M. The recognition of single-nucleotide variations was achieved within 15 min to enable the fast and direct identification of two core mutations (L452R, R203M) in Delta genomes (p < .01). Such capability originated from the trap states in oxidized InSe (InSe1-xOx) after ALD, resulting in traps-involved carrier transport responsive to the negative charges of NAs. In sum, the proposed approach might highly provide epidemiological information for timely surveillance of the COVID pandemic.

An approach combining bioinformatics and machine learning to identify eight autophagy-related biomarkers and construct molecular mechanisms underlying COVID-19 and major depressive disorders.

OBJECTIVE: A lack of objective biomarkers is preventing the screening and diagnosis of COVID-19 combined with major depression disorder (COVID-19-MDD). The purpose of this study was to identify diagnostic biomarkers and gene regulatory mechanisms associated with autophagy; a crucial process significantly involved in the pathogenesis of COVID-19-MDD. MATERIALS AND METHODS: In this study, differentially expressed genes (DEGs) were screened using GSE98793 from the GEO2R analysis (GEO) database, and intersected with the COVID-19-related gene (CRGs) and autophagy-related genes (ARGs) to obtain common genes involved in. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these common genes were performed. Subsequently, the transcription factor (TF)-gene regulatory network and comorbidity network were constructed. In addition, 10 drug candidates were screened using the DSigDB database. To identify diagnostic markers, we used LASSO regression. RESULTS: In total, 13 common genes were screened, which were primarily enriched in lysosomes, endoplasmic reticulum membranes, and other endomembrane systems also associated with autophagy. Additionally, these genes were involved in neurological cell signaling and have a functional role in pathways related to vascular endothelial growth factor, tyrosine kinase, autophagy, inflammation, immunity, and carcinogenesis. Tumors and psychiatric disorders were the most highly linked diseases to COVID-19. Finally, ten drug candidates and eight diagnostic markers (STX17, NRG1, RRAGD, XPO1, HERC1, HSP90AB1, EPHB2, and S1PR3) were screened. CONCLUSIONS: This is the first study to screen eight diagnostic markers and construct a gene regulatory network for COVID-19-MDD from the perspective of autophagy. The findings of our study provide novel insights into the diagnosis and treatment of COVID-19-MDD.

[Diagnostic value of rapid antigen testing for the detection of SARS-CoV-2 infection].

Objective: To investigate the diagnostic value of rapid antigen test based on colloidal gold immunochromatographic assay for the detection of SARS-CoV-2 infection in symptomatic patients. Methods: From May 20 to June 5 2022, 76 hospitalized children and their 55 accompanying family members with confirmed SARS-CoV-2 infection in the COVID-19 isolation unit of the Children's Hospital of Fudan University (designated referral hospital for SARS-CoV-2 infection in Shanghai) enrolled. Their nasopharyngeal swab specimens were consecutively collected. The samples were tested for SARS-CoV-2 nucleic acid by real-time quantitative. SARS-CoV-2 antigen was tested by immunochromatography. The correlation between the antigen detection results and the change of the cycle threshold (Ct) values were evaluated, as well as the sensitivity and specificity of SARS-CoV-2 antigen detection at different periods after the onset of the disease. Kappa consistency test was conducted to investigate the consistency between the 2 diagnostic methods. Results: Of the enrolled SARS-CoV-2 symptomatic infections, 76 were children, including 41 males and 35 females, with an age of 5 (2, 9) years; 55 were accompanying families, including 8 males and 47 females, with an age of 38 (32, 41) years. All 478 samples were simultaneously tested for SARS-CoV-2 antigen and nucleic acid. In any period from disease onset to negative conversion of viral nucleic acid, the overall sensitivity of the rapid antigen test was 48.2% (119/247), the specificity was 98.3% (227/231), and antigen test and nucleic acid test showed moderate consistency (κ=0.46, P<0.05). The sensitivity of antigen test was 100% (82/82) when the Ct value was ≤25. And the sensitivity of antigen test was 8/10, 4/15 and 8.3% (3/36) when the Ct value was 26, 30 and 35, respectively. All antigen tests were negative when Ct value was >35. During the period of 1-2 days, 3-5 days, 6-7 days, 8-10 days and >10 days after onset, the sensitivity and specificity of SARS-CoV-2 antigen test were 5/8 and 5/5, 90.2% (37/41) and 5/5, 88.9% (24/27) and 2/5, 45.0% (36/80) and 94.1% (32/34), 18.7% (17/91) and 98.9% (183/185) respectively. The Ct values of nasopharyngeal swabs were<26 during 2 to 7 days after onset, 28.7±5.0 on day 8, 34.5±2.9 on day 13 and > 35 after 14 days, respectively. Conclusion: SARS-CoV-2 antigen test in the patients with SARS-CoV-2 infection shows acceptable sensitivity and specificity within 7 days after onset of disease, and the sensitivity was positively correlated with viral load and negatively correlated with onset time.

Visualizing the Electroencephalography Signal Discrepancy When Maintaining Social Distancing: EEG-Based Interactive Moire Patterns

In the context of the COIVD-19 pandemic, everyone must maintain social distances in public. Our ability to perceive each other through "distances" in public places has been compromised. However, "distance" is an essential factor in communication that cannot be ignored, like "facial expressions" and "body movements". This paper reflects on the current fixed "social distancing" in the context of the current viral pandemic. The innovative point of our research is to detect and calculate the differences of brainwave signal data between two people and visualize the differences through programmed 2D moving images. In terms of the research process, first, we explored a new way of interaction, using brainwave signals to express "distances" and moire patterns as visual representations. Then we wrote an algorithm to generate the dynamic responses of the moire patterns to different stimuli in real-time to represent the concepts of distances and visualize people's reactions. Finally, we developed an interactive device to imagine "electroencephalography (EEG) signal discrepancy" to perceive the "distances" in social situations. Nowadays, online meetings, classes, etc., are becoming more and more popular, and the distances between people in virtual spaces will be more ambiguous. In light of this, we plan to explore the visualization of electroencephalography (EEG) signal discrepancy in remote communication to enhance people's perceptions of each other in the future.

Inactivation Effect of All-Solid-State 228 nm Far-UVC Pulsed Laser

Objective The ongoing coronavirus pandemic has propelled the need for new approaches to disinfection, especially for airborne viruses. The 254 nm emission of low-pressure vacuum lamps is known for its antimicrobial effect;however, its radiation is harmful to human health, causing skin cancer and cataracts. Some studies have shown that short-wavelength ultraviolet (UV) light in the spectral region of 200-230 nm (far-UVC) can inactivate pathogens without harming human cells. Thus, it has great prospects for many applications. Sufficient studies have proved the antibacterial performance of far-UVC band range in an excimer lamp emitting a peak wavelength of 222 nm light. Furthermore, laser light sources can realize long-distance transmission and complement the deficiency of excimer lamps in remote sterilization and disinfection. This study investigates the antibacterial effect of a self-developed far-UVC laser with a peak wavelength of 228 nm and hopes to provide a new technical approach for the inactivation of the novel coronavirus and other microbial pathogens. Methods Bacterial sample preparation: Escherichia coli (E. coli) widely exists naturally and is a pathogen of major focus in human public health defense. It is also one of the most drug-resistant species in the enterobacterium group. Therefore, it is often used in ultraviolet disinfection and environmental health research. Bacillus cereus (B. cereus), which is closely related to humans, causes food poisoning and cannot be eliminated by pasteurization or normal hygiene procedures due to the heat and acid resistance of its spores. Therefore, the strains used in this experiment are E. coli and B. cereus. E. coli and B. cereus are provided by the Ministry of Education Key Laboratory for Ecology of Tropical Islands, Hainan Normal University, and subsp. Kustaki HD-1, provided by the Environmental Microbial Ecology Laboratory of Hainan Normal University. Both strains are cultured in a nutrient agar medium and placed in an incubator at 35 degrees C for 1 day. Nutrient agar medium is provided by Guangdong Huankai Microbial Technology Co., LTD, China. UV irradiation source: the irradiation source is a self-developed all-solid-state 228 nm far-UVC laser, which provides UV irradiance of up to 35 mW/cm(2), and its spectral linewidth is less than 0.1 nm. The laser is realized by LD-pumped Nd3+ laser crystal, Q-switched technology, and nonlinear optical frequency conversion technology. All-solid-state lasers have the advantages of small size, high efficiency, good beam quality, high reliability, long life, and portability. 228 nm far-UVC laser sterilization: we input a certain concentration of 1 mL bacterial suspension sample into a high permeability UVC cuvette. The 228 nm laser irradiance of 0.1 mW/cm(2) is obtained by adjusting the laser output power and the placement of the colorimeter. E. coli suspension samples are irradiated for 5, 10, 15, and 20 s [Fig. 1 (b), and B. cereus suspension samples are irradiated for 15, 30, 45, and 60 s [Fig. 1(c)] at 228 nm far-UV light of 0.1 mW/cm(2). The experiment is repeated three times for each sample at the same irradiation dose. Results and Discussions Figs. 1 (b) and (c) show the distribution of bacteria before and after 228 nm laser irradiation. The concentration of bacterial suspension samples in the control and irradiated groups is determined using the nutrient agar plate counting method. The detection results are shown in Table 1. When the E. coli suspension is irradiated by 228 nm laser for 10, 15, and 20 s (1, 1.5, and 2 mJ/cm(2)), the inactivation rates are 90. 7 %, 96.9 %, and 100 yo, respectively. When the B. cereus suspension is irradiated by 228 nm laser for 30, 45, and 60 s (3, 4. 5, and 6 mJ/cm(2)), the inactivation rates are 88. 4%, 98.6 %, and 100 %, respectively. Conclusions This experimental study shows that the use of several mJ/cm(2) doses of far-UVC 228 nm pulsed laser irradiation can effectively inactivate E. coli and B. cereus, whereas the use of excimer lamps requires dozens of mJ/cm(2) doses. Compared with the excimer light source, the far-UVC pulsed laser light source shows a stronger sterilization effect. The next step is to conduct experimental research on the inactivation of the influenza virus using a far-UVC 228 nm pulsed laser.

CASTING: A Potent Supramolecular Strategy to Cytosolically Deliver STING Agonist for Cancer Immunotherapy and SARS-CoV-2 Vaccination

Stimulator of interferon genes, namely STING, an adaptor protein located in the endoplasmic reticulum, has been recognized as a shining target for cancer and infection research. However, STING agonists cyclic dinucleotides (CDNs) have shown almost zero efficacy in phase I clinical trials as a monotherapy, likely due to poor cellular permeability and rapid diffusion despite intratumoral injection. These deficiencies further affect other applications of CDNs, such as pandemic SARS-CoV-2 prevention and therapy. Here, we rationally design a supramolecular cytosolic delivery system based on controllable recognition of calixarene, namely CASTING (CAlixarene-STING), to improve CDN druggability, including degradation stability, cellular permeability, and tissue retention. CASTING efficiently enhances the immunostimulatory potency of CDG(SF) [a chemically modified cyclic di-GMP (CDG)] to generate an immunogenic microenvironment for melanoma regression, anti-PD-1 response rate increase, and durable memory formation against tumor recurrence. More importantly, CASTING displays a superior adjuvant activity on SARS-CoV-2 recombinant spike/receptor binding domain vaccines, inducing robust and coordinated T-cell and antibody responses against SARS-CoV-2 infection in vivo. Collectively, the CASTING design represents an innovative advancement to facilitate the clinical translational capability of STING agonists. [GRAPHICS] .

[Initiation timing of veno-arterial extracorporeal membrane oxygenation].

Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a salvage therapy for critical patients with refractory cardiogenic shock caused by various reasons. It can temporarily replace cardiopulmonary function, and rapidly improve hypoxemia, increase systemic oxygen content and remove carbon dioxide. Although the Extracorporeal Life Support Organization (ELSO) guideline proposed clear indication for VA-ECMO, the heterogeneity of cardiac pathogeny is large, so the clear timing of ECMO initiation is still vague. We discuss the timing of ECMO initiation for external cardiopulmonary resuscitation (ECPR) and cardiogenic shock which is caused by fulminant myocarditis, acute myocardial infarction, acute pulmonary embolism, acute right heart failure related to lung transplantation, corona virus disease 2019 (COVID-19)-associated cardiovascular collapse. Also, we look forward to making more suggestions for clinicians' judgment and choice for VA-ECMO.

Analysis on the Influence and Cause of a Heavy Pollution Process on Air Quality in Baoding during COVID-19

Due to the outbreak of the novel coronavirus, China had implemented a strict home isolation policy after the Spring Festival, and human activities in many areas had been prohibited. However, Baoding still suffered heavy air pollution during February 2020, especially in February 8-13. The results showed that the concentrations of pollutants in February 2020 had a decrease from February 2019. The reduction of human activities during the epidemic significantly decreased the concentration of air pollutants and improved air quality. In addition, compared with non-pollution period (February 22-29), the PM2.5 concentration during pollution period (February 8-13) increased the most visibly. The analysis of OC and EC shows that there was a certain amount of civil coal combustion during the heavy pollution period;K+ and Mg2+ in PM2.5 revealed the huge influence of fireworks and firecrackers in Baoding. The backward trajectory and potential source analysis indicated that Baoding was influenced by air masses from southwest during the heavy pollution period, and the potential source areas were mainly distributed in southwest of Baoding. It can be seen that the impact of pollutants in the superimposed area of local emission and transportation with unfavorable meteorological condition in Baoding. © 2022, HARD Publishing Company. All rights reserved.

Evaluation Toolkit for Robustness Testing of Automatic Essay Scoring Systems

Automatic scoring engines have been used for scoring approximately fifteen million test-takers in just the last three years. This number is increasing further due to COVID-19 and the associated automation of education and testing. Yet, the AI-based testing literature of these intelligent"models is highly lacking as most of the papers propose new models that rely only on quadratic weighted kappa (QWK) based agreement with human raters for showing model efficacy. However, this effectively ignores the highly multi-feature nature of essay scoring. Essay scoring depends on features like coherence, grammar, relevance, etc. and to date, there has been no study testing Automated Essay Scoring (AES) systems holistically on all these features. With this motivation, we propose a model agnostic adversarial evaluation scheme and associated metrics for AES systems to test their natural language understanding capabilities and overall robustness. We evaluate the current state-of-the-art AES models using the proposed scheme and report the results on five recent models. These models range from feature-engineering-based approaches to the latest deep learning algorithms. We find that AES models are highly overstable such that even heavy modifications (as much as 25%) with content unrelated to the topic of the questions do not decrease the score produced by the models. On the other hand, unrelated content, on average, increases the scores, thus showing that the models' evaluation strategy and rubrics should be reconsidered. We conduct a human survey with 200 human raters and observe that they can easily detect differences between the original and perturbed responses and have a general disagreement with the scores assigned by auto scorers. © 2022 ACM.

Effect of Perceived Organizational Support on Fatigue of Chinese Nurses during the COVID-19 Pandemic: Resilience as a Mediator

As working for the nurse is believed to be one of the most stressful professions, nurses are particularly at risk of experiencing fatigue. Especially during the COVID-19 pandemic, fatigue among nurses may affect physical and mental health seriously, which is attracting increasing attention of researchers and clinical practitioners to find effective prevention measures to alleviate nurses' fatigue. This study aims to investigate the mediational effect of resilience on the relationship between nurses' perceived organizational support and fatigue. A total of 476 nurses from secondary and above hospitals in Hebei province, China during March and April in 2020, were investigated with Perceived Organizational Support Scale, Resilience Scale and Work Fatigue Inventory. Structural equation modeling was conducted to explore the mechanisms of nurses' perceived organizational support on fatigue. Results revealed that perceived organizational support can decrease the nurses' mental/physical/emotional fatigue through the mediating role of resilience. These findings guide for hospital managers to identify effective prevention strategies to alleviate the fatigue of clinical nurses.

Efficacy and safety of COVID-19 vaccines: a systematic review

OBJECTIVE: To evaluate systematically the efficacy and safety of COVID-19 vaccines. METHODS: PubMed, Embase, Cochrane Library, Clinicaltrial.gov, CNKI, Wanfang Data, China Biomedical Literature Service System, and China Clinical Trial Registry were searched for randomized controlled trials of COVID-19 vaccines published up to December 31, 2020. The Cochrane bias risk assessment tool was used to assess the quality of studies. A qualitative analysis was performed on the results of clinical trials. RESULTS: Thirteen randomized, blinded, controlled trials, which involved the safety and efficacy of 11 COVID-19 vaccines, were included. In 10 studies, the 28-day seroconversion rate of subjects exceeded 80%. In two 10 000-scale clinical trials, the vaccines were effective in 95% and 70.4% of the subjects, respectively. The seroconversion rate was lower than 60% in only one study. In six studies, the proportion of subjects who had an adverse reaction within 28 days after vaccination was lower than 30%. This proportion was 30%-50% in two studies and > 50% in the other two studies. Most of the adverse reactions were mild to moderate and resolved within 24 hours after vaccination. The most common local adverse reaction was pain or tenderness at the injection site, and the most common systemic adverse reaction was fatigue, fever, or bodily pain. The immune response and incidence of adverse reactions to the vaccines were positively correlated with the dose given to the subjects. The immune response to the vaccines was worse in the elderly than in the younger population. In 6 studies that compared single-dose and double-dose vaccination, 4 studies showed that double-dose vaccination produced a stronger immune response than single-dose vaccination. CONCLUSIONS: Most of the COVID-19 vaccines appear to be effective and safe. Double-dose vaccination is recommended. However, more research is needed to investigate the long-term efficacy and safety of the vaccines and the influence of dose, age, and production process on the protective efficacy.

[Clinical analysis of liver chemistries in children and adolescent with 2019-nCoV infection].

Objective: To describe the clinical features of liver involvement in children and adolescent with 2019-nCoV infection. Methods: The clinical data of 77 hospitalized cases admitted to the Children's Hospital of Fudan University were collected from January 19 to November 28, 2020. The characteristics and risk factors of abnormal liver chemistries in children with laboratory-confirmed 2019-nCoV infection were analyzed. Results: Of the 77 cases, 44 were male (57.1%) and 33 were female (42.9%), with a median age of 10 years. 27(35.1%) were asymptomatic, 28(36.4%) had mild illness, 22(28.6%)had non-severe pneumonia. Hydroxychloroquine was used in 7 cases. Of the 75 children without underlying diseases, alanine aminotransferase was elevated in 1 case (1.5%, during hydroxychloroquine therapy), aspartate aminotransferase was elevated in 7 cases (10.3%), alkaline phosphatase was elevated in 7 cases (28%), and total bilirubin, direct bilirubin, albumin, international normalized ratio were in normal range. There was no statistical difference between the pneumonia group and the non-pneumonia group in term of liver chemistries (P > 0.05), same as between the elevated erythrocyte sedimentation rate group and the normal group. There was no aggravation of liver injury in the child with biliary atresia. The child with epilepsy showed no abnormal liver chemistries after infection. Conclusion: Children with 2019-nCoV infection had mild clinical symptoms with few cases of liver injury. The abnormal liver chemistries in children with COVID-19 infection may be related to the underlying disease and the use of antiviral drugs.

[The role of large-scale testing platform in the prevention and control of the COVID-19 pandemic: an empirical study based on a novel numerical model].

Objective: China adopted an unprecedented province-scale quarantine since January 23rd 2020, after the novel coronavirus (COVID-19) broke out in Wuhan in December 2019. Responding to the challenge of limited testing capacity, large-scale (>20 000 tests per day) standardized and fully-automated laboratory (Huo-Yan) was built as an ad-hoc measure. There is so far no empirical data or mathematical model to reveal the impact of the testing capacity improvement since quarantine. Methods: Based on the suspected case data released by the Health Commission of Hubei Province and the daily testing data of Huo-Yan Laboratory, the impact of detection capabilities on the realization of "clearing" and "clearing the day" of supected cases was simulated by establishing a novel non-linear and competitive compartments differential model. Results: Without the establishment of Huo-Yan, the suspected cases would increase by 47% to 33 700, the corresponding cost of quarantine would be doubled, the turning point of the increment of suspected cases and the achievement of "daily settlement" (all newly discovered suspected cases are diagnosed according to the nucleic acid testing result) would be delayed for a whole week and 11 days. If the Huo-Yan Laboratory could ran at its full capacity, the number of suspected cases could start to decrease at least a week earlier, the peak of suspected cases would be reduced by at least 44%, and the quarantine cost could be reduced by more than 72%. Ideally, if a daily testing capacity of 10 500 tests was achieved immediately after the Hubei lockdown, "daily settlement" for all suspected cases could be achieved. Conclusions: Large-scale, standardized clinical testing platform, with nucleic acid testing, high-throughput sequencing, and immunoprotein assessment capabilities, need to be implemented simultaneously in order to maximize the effect of quarantine and minimize the duration and cost of the quarantine. Such infrastructure, for both common times and emergencies, is of great significance for the early prevention and control of infectious diseases.

Network pharmacology for treatment of COVID-19 with Renshen Baidu Powder based on cytokines

Objective: To investigate the multi compound-target-pathway mechanism of Renshen Baidu Powder (RSBDS) in the treatment of COVID-19 from cytokine perspective. Methods: The active compounds of RSBDS were collected by TCMSP and the cytokine storm related targets were collected by the drug target database. The interaction network of RSBDS on single drug-active compounds-targets was established by Cytoscape. The interaction network, GO function and KEGG pathway of the targets were analyzed by String and DAVID databases. Results: The interaction network of RSBDS on single drug-active compounds-targets included 10 kinds of medicinal materials, 211 active compounds and 151 disease targets. Interaction network showed that the targets related to the inhibition to cytokine storm of RSBDS on COVID-19 might include STAT3, MAPK1, NFκB1, PIK3CA, MAPK3, TNF, CXCR4, VEGFA, IL-6, IL-2, etc. GO function showed that above targets in biological function involved chemotaxis and steroid metabolism;Molecular function entries involved heme binding, iron ion binding and oxygen binding;Cell composition entries involved cell surface and cell membrane. KEGG pathway showed that above targets participated in the regulation of Chagas disease, HIF-1 signaling pathway, TNF signaling pathway, etc. Conclusion: The multi compound-target-pathways effect of RSBDS on COVID-19 was realized by inhibiting cytokine storm, which through regulating chemotaxis, increasing blood oxygen saturation, inhibiting STAT, MAPK, NFκB, PIK3K and IL-6 signal pathways.