Effects of EEG burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients: A randomized clinical trial.

BACKGROUND: This randomized clinical trial determined the effects of electroencephalographic burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients. METHODS: The patients were placed into burst suppression (BS) and non-burst suppression (NBS) groups. All patients were under bispectral index monitoring of an etomidate target-controlled infusion for anesthesia induction and intraoperative combination sevoflurane and remifentanil for anesthesia maintenance. The cerebral oxygen extraction ratio (CERO2), jugular bulb venous saturation (SjvO2), and difference in arteriovenous oxygen (Da-jvO2) were measured at T0, T1, and T2. One day before surgery, and 1, 3, and 7 days after surgery, postoperative cognitive dysfunction was assessed using the mini-mental state examination (MMSE). RESULTS: Compared with T0, the Da-jvO2 and CERO2 values were decreased, and SjvO2 was increased in the 2 groups at T1 and T2 (P < .05). There was no statistical difference in the SjvO2, Da-jvO2, and CERO2 values between T1 and T2. Compared with the NBS group, the SjvO2 value increased, and the Da-jvO2 and CERO2 values decreased at T1 and T2 in the BS group (P < .05). The MMSE scores on the 1st and 3rd days postoperatively were significantly lower in the 2 groups compared to the preoperative MMSE scores (P < .05). The MMSE scores of the NBS group were higher than the BS group on the 1st and 3rd days postoperatively (P < .05). CONCLUSION: In elderly patients undergoing surgery, intraoperative BS significantly reduced cerebral oxygen metabolism, which temporarily affected postoperative neurocognitive function.

Supplying masks to combat respiratory diseases: safety index, welfare and government involvement

Coronavirus (COVID-19) is a highly infectious respiratory disease which spread can be effectively curbed by wearing facial masks, especially N95 and surgical masks. In this paper, we develop a stylised game-theoretical model to evaluate the impacts of producing and selling masks on supply chain profits, safety index and consumer and social welfare. Firstly, we find that as the infection probability without protection (IPWP) increases, both the retail price and demand for these masks will increase. When the IPWP is sufficiently low, those consumers who want to purchase masks are more likely to purchase N95 masks, but when the IPWP increases, surgical masks are more popular amongst consumers. Secondly, we develop a safety index that indicates the effectiveness of using masks in preventing respiratory disease infection. This index is especially crucial in cases where the IPWP is moderate;in other words, recommending to wear masks is particularly important when the IPWP is moderate. We also examine the impacts of government involvement in handling the outbreak of respiratory diseases. Providing consumer subsidies and promoting the social mask enterprise can effectively combat respiratory diseases under different conditions. Our results can be used for combating COVID-19 and preparing for future health crisess.

Immunogenicity of inactivated coronavirus disease 2019 vaccines in patients with chronic hepatitis B undergoing antiviral therapy.

Objectives: To investigate the effect and its mechanisms of different antiviral agents on the immunogenicity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines in patients with chronic hepatitis B (CHB). Methods: A total of 125 patients with CHB receiving nucleos(t)ide analogs (NAs) monotherapy or combined with Peg-interferon-alpha (Peg-IFNα) therapy and 29 healthy controls (HCs) were enrolled. Adverse reactions (ADRs) and levels of neutralizing antibody (NAb), immunoglobulin G (IgG), immunoglobulin M (IgM), and peripheral cytokines post-vaccination were analyzed. Results: All ADRs were tolerable in CHB patients. Overall, no significant difference was observed in the antibody levels between patients and HCs after two doses of vaccination. An inverse correlation between NAb, IgG titers and the days after two doses was found in non-IFN group but not in IFN group. Correspondingly, peripheral interferon-γ levels were significantly higher in IFN group than in non-IFN group. After a booster dose, NAb and IgG antibodies were maintained at high levels in NA-treated patients. Conclusion: Peg-interferon-alpha-based therapy may be beneficial for maintaining the immunogenicity of SARS-CoV-2 vaccines in CHB patients, which may be related to the high levels of IFN-γ induced by Peg-IFNα therapy. A booster dose can effectively recall the robust and long-lasting immunogenicity of SARS-CoV-2 vaccines.

Optimal Establishments of Massive Testing Programs to Combat COVID-19: A Perspective of Parallel-Machine Scheduling-Location (ScheLoc) Problem

Massive testing to identify COVID-19-infected people is crucial in combating COVID-19. However, from the perspective of facility location problems, many current massive testing programs are not properly set, leading to unreasonable travelling distances, long makespan, unbalanced workload, and long queues. This article proposes a decision framework for developing massive testing programs. Specifically, a biobjective parallel-testing-site Scheduling-location (Scheloc) model is formulated, simultaneously minimizing the makespan and total travelling distance. The former can help reduce the time length of potential virus spread, and the latter can help alleviate the risk of virus spread and traveler inconvenience. To solve the proposed biobjective ScheLoc problem, in addition to the standard epsilon-constraint method, we further develop two novel strategies. The first one iteratively solves simpler approximate MIP models (IMIP). The second innovatively extends the classical logic-based Benders decomposition approach to solve biobjective problems (B-LBBD). A Hong Kong-based case study shows that the proposed decision framework can significantly reduce the makespan and travelling distance (with a mean of 13% and 5.1%, respectively) and enhance workload balancing. Besides, the developed solution methods, especially the B-LBBD, outperform the adapted epsilon-constraint method in various aspects.

Matrix Kendall's tau in High-dimensions: A Robust Statistic for Matrix Factor Model (preprint)

In this article, we first propose generalized row/column matrix Kendall's tau for matrix-variate observations that are ubiquitous in areas such as finance and medical imaging. For a random matrix following a matrix-variate elliptically contoured distribution, we show that the eigenspaces of the proposed row/column matrix Kendall's tau coincide with those of the row/column scatter matrix respectively, with the same descending order of the eigenvalues. We perform eigenvalue decomposition to the generalized row/column matrix Kendall's tau for recovering the loading spaces of the matrix factor model. We also propose to estimate the pair of the factor numbers by exploiting the eigenvalue-ratios of the row/column matrix Kendall's tau. Theoretically, we derive the convergence rates of the estimators for loading spaces, factor scores and common components, and prove the consistency of the estimators for the factor numbers without any moment constraints on the idiosyncratic errors. Thorough simulation studies are conducted to show the higher degree of robustness of the proposed estimators over the existing ones. Analysis of a financial dataset of asset returns and a medical imaging dataset associated with COVID-19 illustrate the empirical usefulness of the proposed method.

Discussion on Influencing Factors and Control Range of Disinfection Effect in Waterworks during the COVID-19 Outbreak

This paper studied the influencing factors of disinfection effect in water purification process and the influence of external demand on the water purification process to ensure that the effective virus inactivation rate of waterworks can meet the requirements of microbiological safety during the COVID-19 outbreak. The results showed that the effluent turbidity should be no more than 0. 3 NTU to meet the requirements of coagulation sedimentation filtration process for virus 2-lg removal rate under the condition of the fixed source water temperature and pH value. On the basis of the above,with the monitoring of the effluent turbidity,water level of clean water tank,water quantity of waterworks and residual chlorine by real-time online instruments,the CT value of the clean water tank was controlled and adjusted within an appropriate range in real time,so that it not only met the 4-lg virus inactivation rate but also reduced the risk of disinfection by-products. Finally,a virus reduction rate of above 6-lg was achieved with the treatment process of waterworks,which could meet the biological safety requirements of drinking water during the epidemic,and have a sufficient safety margin.

Kinetics of IgM and IgG antibody specific to SARS-CoV-2 nucleocapsid and spike proteins

：Objective To study the kinetics of IgM and IgG antibodies based on nucleocapsid（N） and spike（S） protein of SARS-Co V2-in COVID-19 patients. Methods Immunofluorescent kits were used to detect N and S protein specific IgM and IgG antibodies from Jan.21 to Feb.11, 2020 for the 60 hospitalized COVID-19 patients（48 mild, 12 severe cases） with a total of 290 plasma samples collected 9 weeks after the onset of the disease. Results The level of antibodies specific for S protein varied significantly with the course of disease（Ig M from 27.32 to 110.10 TU/ml, IgG from 56.85 to 135.00 TU/ml）, but not for N protein.Higher level of Ig M/Ig G antibodies specific to S protein was observed during the 2-7 week than that to N protein.The seropositive rate of antibodies gradually increased during the early stage of disease.IgM/IgG antibodies specific to N protein changed from 12.50% at the first week to peak level（51.72% and 86.21% respectively） at the 4 th week and those for S protein from 25.00% and 14.58% to 100.00%, and then declined.The seropositive rate of Ig M antibody specific to S protein was higher than that for N protein during 2-8 th week and that for Ig G antibody at 2, 3, 4, 6 and 7 th week.The seropositive rate of Ig G antibody specific to N protein in severe patients at the third week was higher than that in mild patients（100.00% vs 59.52%,χ2=9.67, P=0.001 9）, and the same as to Ig G antibody for S protein at the second week after disease onset（80.00% vs 46.58%, χ2=5.57, P=0.018 2）. Conclusions SARS-Co V2-S protein can induc stronger antibody response than N protein, and the antibody level was related to the severity of the disease.

On the mass COVID-19 vaccination scheduling problem.

The outbreak of COVID-19 dramatically impacts the global economy. Mass COVID-19 vaccination is widely regarded as the most promising way to fight against the pandemic and help return to normal. Many governments have authorized certain types of vaccines for mass vaccination by establishing appointment platforms. Mass vaccination poses a vital challenge to decision-makers responsible for scheduling a large number of appointments. This paper studies a vaccination site selection, appointment acceptance, appointment assignment, and scheduling problem for mass vaccination in response to COVID-19. An optimal solution to the problem determines the open vaccination sites, the set of accepted appointments, the assignment of accepted appointments to open vaccination sites, and the vaccination sequence at each site. The objective is to simultaneously minimize 1) the fixed cost for operating vaccination sites; 2) the traveling distance of vaccine recipients; 3) the appointment rejection cost; and 4) the vaccination tardiness cost. We formulate the problem as a mixed-integer linear program (MILP). Given the NP-hardness of the problem, we then develop an exact logic-based Benders decomposition (LBBD) method and a matheuristic method (MH) to solve practical-sized problem instances. We conduct numerical experiments on small- to large-sized instances to demonstrate the performance of the proposed model and solution methods. Computational results indicate that the proposed methods provide optimal solutions to small-sized instances and near-optimal solutions to large ones. In particular, the developed matheuristic can efficiently solve practical-sized instances with up to 500 appointments and 50 vaccination sites. We discuss managerial implications drawn from our results for the mass COVID-19 vaccination appointment scheduling, which help decision-makers make critical decisions.

SARS-CoV-2 causes a significant stress response mediated by small RNAs in the blood of COVID-19 patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had a serious impact on the world. In this study, small RNAs from the blood of COVID-19 patients with moderate or severe symptoms were extracted for high-throughput sequencing and analysis. Interestingly, the levels of a special group of tRNA-derived small RNAs (tsRNAs) were found to be dramatically upregulated after SARS-CoV-2 infection, particularly in coronavirus disease 2019 (COVID-19) patients with severe symptoms. In particular, the 3'CCA tsRNAs from tRNA-Gly were highly consistent with the inflammation indicator C-reactive protein (CRP). In addition, we found that the majority of significantly changed microRNAs (miRNAs) were associated with endoplasmic reticulum (ER)/unfolded protein response (UPR) sensors, which may lead to the induction of proinflammatory cytokine and immune responses. This study found that SARS-CoV-2 infection caused significant changes in the levels of stress-associated small RNAs in patient blood and their potential functions. Our research revealed that the cells of COVID-19 patients undergo tremendous stress and respond, which can be reflected or regulated by small non-coding RNA (sncRNAs), thus providing potential thought for therapeutic intervention in COVID-19 by modulating small RNA levels or activities.

Kinetics of SARS-CoV-2 antibodies in COVID-19 patients and relationship with severity of disease

Objective To study the kinetics of SARS-CoV-2 antibodies in COVID-19 patients and the correlation with disease severity. Methods A total of 290 plasma samples were collected from 60 hospitalized patients including 48 mild cases and 12 severe cases within 63 days after disease onset in Guangzhou Eighth People′s Hospital affiliated to Guangzhou Medical University during January 21 to April 11, 2020.SARS-CoV-2 specific antibodies were determined by four commercial colloidal gold serologic reagents validated by National Medical Products Administration in China. Results The seropositive rate ranged from 19.23% to 34.62% by four assays within one week after disease onset, and rapidly increased within the following two weeks.The seropositive rates were 52.27% to 68.18% and 83.05% to 98.31%, respectively.IgM antibody peaked within the fourth week and maintained high level for 1 to 2 weeks, and decreased significantly until the 9 th week.But no obvious decreasing trend of the seropositive rate of IgG antibody was observed during two months after disease onset.The seropositive rates of antibodies between mild and severe cases showed no statistical difference.Four assays demonstrated a sensitivity of 78.33%to 91.67%in 60 COVID-19 patients.The difference was statistically significant between the highest and the lowest values（χ2=4.183,P=0.041）． Conclusions The colloidal gold serologic reagents show good sensitivity during the late stage of disease but not at the early stage.There is no correlation between seropositive and disease severity.The sensitivity of different reagents is different

Moments in autophagy and disease: Past and present.

Over the past several decades, research on autophagy, a highly conserved lysosomal degradation pathway, has been advanced by studies in different model organisms, especially in the field of its molecular mechanism and regulation. The malfunction of autophagy is linked to various diseases, among which cancer and neurodegenerative diseases are the major focus. In this review, we cover some other important diseases, including cardiovascular diseases, infectious and inflammatory diseases, and metabolic disorders, as well as rare diseases, with a hope of providing a more complete understanding of the spectrum of autophagy's role in human health.

Association Analysis of Hyperlipidemia with the 28-Day All-Cause Mortality of COVID-19 in Hospitalized Patients.

Objective This study aimed to determine the association of hyperlipidemia with clinical endpoints among hospitalized patients with COVID-19, especially those with pre-existing cardiovascular diseases (CVDs) and diabetes. Methods This multicenter retrospective cohort study included all patients who were hospitalized due to COVID-19 from 21 hospitals in Hubei province, China between December 31, 2019 and April 21, 2020. Patients who were aged < 18 or ≥ 85 years old, in pregnancy, with acute lethal organ injury (e.g., acute myocardial infarction, severe acute pancreatitis, acute stroke), hypothyroidism, malignant diseases, severe malnutrition, and those with normal lipid profile under lipid-lowering medicines (e.g., statin, niacin, fenofibrate, gemfibrozil, and ezetimibe) were excluded. Propensity score matching (PSM) analysis at 1:1 ratio was performed to minimize baseline differences between patient groups of hyperlipidemia and non-hyperlipidemia. PSM analyses with the same strategies were further conducted for the parameters of hyperlipidemia in patients with increased triglyceride (TG), increased low-density lipoprotein cholesterol (LDL-C), and decreased high-density lipoprotein cholesterol (HDL-C). Mixed-effect Cox model analysis was performed to investigate the associations of the 28-days all-cause deaths of COVID-19 patients with hyperlipidemia and the abnormalities of lipid parameters. The results were verified in male, female patients, and in patients with pre-existing CVDs and type 2 diabetes. Results Of 10 945 inpatients confirmed as COVID-19, there were 9822 inpatients included in the study, comprising 3513 (35.8%) cases without hyperlipidemia and 6309 (64.2%) cases with hyperlipidemia. Based on a mixed-effect Cox model after PSM at 1:1 ratio, hyperlipidemia was not associated with increased or decreased 28-day all-cause death [adjusted hazard ratio (HR), 1.17 (95% CI, 0.95-1.44), P =0.151]. We found that the parameters of hyperlipidemia were not associated with the risk of 28-day all-cause mortality [adjusted HR, 1.23 (95% CI, 0.98-1.55), P = 0.075 in TG increase group; 0.78 (95% CI, 0.57-1.07), P = 0.123 in LDL-C increase group; and 1.12 (95% CI, 0.9-1.39), P = 0.299 in HDL-C decrease group, respectively]. Hyperlipidemia was also not significantly associated with the increased mortality of COVID-19 in patients accompanied with CVDs or type 2 diabetes, and in both male and female cohorts. Conclusion Our study support that the imbalanced lipid profile is not significantly associated with the 28-day all-cause mortality of COVID-19 patients, even in those accompanied with CVDs or diabetes. Similar results were also obtained in subgroup analyses of abnormal lipid parameters. Therefore, hyperlipidemia might be not a major causative factor for poor outcome of COVID-19, which provides guidance for the intervention of inpatients during the epidemic of COVID-19.

Study on the Knowledge, Attitude, and Practice (KAP) of Nursing Staff and Influencing Factors on COVID-19.

The aim of this study is to investigate the knowledge, attitude, and practice (KAP) on Coronavirus Disease 2019 (COVID-19) care among nursing staff and analyze its influencing factors. The survey was conducted on February 18, 2020, among 7,716 voluntary participants from 143 medical institutions in Zhejiang, China. The findings indicated that KAP of nursing staff scored well. However, the accuracy of psychological nursing knowledge was much lower, 14.3% only. Nursing staff working in isolation wards have higher knowledge (OR = 1.776, 95% CI: 1.491-2.116), attitude (OR = 1.542, 95% CI: 1.298-1.832), and practice (OR = 1.902, 95% CI: 1.590-2.274) scores than those in general wards. In terms of KAP, nursing staff with working experience ≤ 10 years scored lower than those with working experience ≥ 20 years, with OR values of 0.490 (95% CI: 0.412-0.583), 0.654 (95% CI: 0.551-0.775), and 0.747 (95% CI: 0.629-0.886), respectively. It is necessary to take measures to enhance the training on COVID-19, especially for KAP of junior nurses in general wards.

Clinical characteristics and plasma antibody titer of patients with COVID-19 in Zhejiang, China.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first affected humans in China on December 31, 2019 (Shi et al., 2020). Coronaviruses generally cause mild, self-limiting upper respiratory tract infections in humans, such as the common cold, pneumonia, and gastroenteritis (To et al., 2013; Berry et al., 2015; Chan et al., 2015). According to the Report of the World Health Organization (WHO)-China Joint Mission on COVID-19 (WHO, 2020), the case fatality rate of COVID-19 increases with age, while the rate among males is higher than that among females (4.7% and 2.8%, respectively). Since an effective vaccine and specific anti-viral drugs are still under development, passive immunization using the convalescent plasma (CP) of recovered COVID-19 donors may offer a suitable therapeutic strategy for severely ill patients in the meantime. So far, several studies have shown therapeutic efficacy of CP transfusion in treating COVID-19 cases. A pilot study first reported that transfusion of CP with neutralizing antibody titers above 1:640 was well tolerated and could potentially improve clinical outcomes through neutralizing viremia in severe COVID-19 cases (Chen et al., 2020). Immunoglobulin G (IgG) and IgM are the most abundant and important antibodies in protecting the human body from viral attack (Arabi et al., 2015; Marano et al., 2016). Our study aimed to understand the aspects of plasma antibody titer levels in convalescent patients, as well as assessing the clinical characteristics of normal, severely ill, and critically ill patients, and thus provide a basis for guiding CP therapy. We also hoped to find indicators which could serve as a reference in predicting the progression of the disease.

No significant association between dipeptidyl peptidase-4 inhibitors and adverse outcomes of COVID-19.

BACKGROUND: Dipeptidyl peptidase-4 (DPP4) is commonly targeted to achieve glycemic control and has potent anti-inflammatory and immunoregulatory effects. Recent structural analyses indicated a potential tight interaction between DPP4 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), raising a promising hypothesis that DPP4 inhibitor (DPP4i) drugs might be an optimal strategy for treating coronavirus disease 2019 (COVID-19) among patients with diabetes. However, there has been no direct clinical evidence illuminating the associations between DPP4i use and COVID-19 outcomes. AIM: To illuminate the associations between DPP4i usage and the adverse outcomes of COVID-19. METHODS: We conducted a multicenter, retrospective analysis including 2563 patients with type 2 diabetes who were hospitalized due to COVID-19 at 16 hospitals in Hubei Province, China. After excluding ineligible individuals, 142 patients who received DPP4i drugs and 1115 patients who received non-DPP4i oral anti-diabetic drugs were included in the subsequent analysis. We performed a strict propensity score matching (PSM) analysis where age, sex, comorbidities, number of oral hypoglycemic agents, heart rate, blood pressure, pulse oxygen saturation (SpO2) < 95%, CT diagnosed bilateral lung lesions, laboratory indicators, and proportion of insulin usage were matched. Finally, 111 participants treated with DPP4i drugs were successfully matched to 333 non-DPP4i users. Then, a linear logistic model and mixed-effect Cox model were applied to analyze the associations between in-hospital DPP4i use and adverse outcomes of COVID-19. RESULTS: After rigorous matching and further adjustments for imbalanced variables in the linear logistic model and Cox adjusted model, we found that there was no significant association between in-hospital DPP4i use (DPP4i group) and 28-d all-cause mortality (adjusted hazard ratio = 0.44, 95%CI: 0.09-2.11, P = 0.31). Likewise, the incidences and risks of secondary outcomes, including septic shock, acute respiratory distress syndrome, or acute organ (kidney, liver, and cardiac) injuries, were also comparable between the DPP4i and non-DPP4i groups. The performance of DPP4i agents in achieving glucose control (e.g., the median level of fasting blood glucose and random blood glucose) and inflammatory regulation was approximately equivalent in the DPP4i and non-DPP4i groups. Furthermore, we did not observe substantial side effects such as uncontrolled glycemia or acidosis due to DPP4i application relative to the use of non-DPP4i agents in the study cohort. CONCLUSION: Our findings demonstrated that DPP4i use is not significantly associated with poor outcomes of COVID-19 or other adverse effects of anti-diabetic treatment. The data support the continuation of DPP4i agents for diabetes management in the setting of COVID-19.

Prevalence and impact of diabetes in patients with COVID-19 in China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that has spread rapidly around the world. Previous studies have indicated that COVID-19 patients with diabetes are prone to having poor clinical outcomes. AIM: To systematically evaluate the prevalence of diabetes among COVID-19 patients in China and its impact on clinical outcomes, including ICU admission, progression to severe cases, or death. METHODS: We searched studies published in PubMed, Web of Science, and EMBASE from December 1, 2019 to March 31, 2020 to identify relevant observational study that investigated the prevalence of diabetes among COVID-19 patients or its impact on clinical outcomes. We used a random-effects or fixed-effects model to estimate the pooled prevalence of diabetes and risk ratio (RR) and its 95% confidence interval (CI) of diabetes on outcomes. Funnel plots were used to evaluate the publication bias and the heterogeneity was evaluated by I 2 statistic. RESULTS: Twenty-three eligible articles including 49564 COVID-19 patients (1573 with and 47991 without diabetes) were finally included. The pooled prevalence of diabetes was 10% (95%CI: 7%-15%) in COVID-19 patients. In the subgroup analyses, the pooled prevalence of diabetes was higher in studies with patients aged > 50 years (13%; 95%CI: 11%-16%) than in studies with patients aged ≤ 50 years (7%; 95%CI: 6%-8%), in severe patients (17%; 95%CI: 14%-20%) than in non-severe patients (6%; 95%CI: 5%-8%), and in dead patients (30%; 95%CI: 13%-46%) than in survivors (8%; 95%CI: 2%-15%) (P < 0.05 for all). Compared with patients without diabetes, the risk of severe cases was higher (RR = 2.13, 95%CI: 1.76-2.56, I 2 = 49%) in COVID-19 patients with diabetes. The risk of death was also higher in COVID-19 patients with diabetes (RR = 3.16, 95%CI: 2.64-3.78, I 2 = 34%). However, diabetes was not found to be significantly associated with admission to ICU (RR = 1.16, 95%CI: 0.15-9.11). CONCLUSION: Nearly one in ten COVID-19 patients have diabetes in China. Diabetes is associated with a higher risk of severe illness and death. The present study suggested that targeted early intervention is needed in COVID-19 patients with diabetes.

Statistical Analysis of Dispelling Rumors on Sina Weibo

Analyzing the process and results of dispelling rumors is a prerequisite for designing an effective anti-rumor strategy. Current research on this subject focuses on the simulation experiments, short of empirical study. By using the False Information Publicity Results of Sina Weibo as the data source of empirical research, this article compares the typical features of rumor and anti-rumor accounts. Furthermore, taking COVID-19 as the target topic, distributions of the reported time, frequency, platform penalty levels, and diffusion parameters of rumors related to COVID-19 are given, and some interesting results are obtained.