PA during the COVID-19 outbreak in China: a cross-sectional study.

COVID-19 has undergone several mutations and is still spreading in most countries now. PA has positive benefits in the prevention of COVID-19 infection and counteracting the negative physical and mental effects caused by COVID-19. However, relevant evidence has indicated a high prevalence of physical inactivity among the general population, which has worsened due to the outbreak of the pandemic, and there is a severe lack of exercise guidance and mitigation strategies to advance the knowledge and role of PA to improve physical and mental health in most countries during the epidemic. This study surveyed the effects of COVID-19 on PA in Chinese residents during the pandemic and provided important reference and evidence to inform policymakers and formulate policies and planning for health promotion and strengthening residents' PA during periods of public health emergencies. ANOVA, Kolmogorov-Smirnov, the chi-square test and Spearman correlation analysis were used for statistical analysis. A total of 14,715 participants were included. The results show that nearly 70% of Chinese residents had inadequate PA (95%CI 58.0%-82.19%) during the COVID-19 outbreak, which was more than double the global level (27.5%, 95%CI 25.0%-32.2%). The content, intensity, duration, and frequency of PA were all affected during the period of home isolation, and the types of PA may vary among different ages. The lack of physical facilities and cultural environment is the main factor affecting PA. However, there was no significant correlation between insufficient PA and the infection rate. During the period of home isolation and social distance of epidemic prevention, it is necessary to strengthen the scientific remote network monitoring and guidance for the process of PA in China.

Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model.

In December 2019, the New Crown Pneumonia (the COVID-19) outbroke around the globe, and China imposed a nationwide lockdown starting as early as January 23, 2020. This decision has significantly impacted China's air quality, especially the sharp decrease in PM2.5 (aerodynamic equivalent diameter of particulate matter less than or equal to 2.5 µm) pollution. Hunan Province is located in the central and eastern part of China, with a "horseshoe basin" topography. The reduction rate of PM2.5 concentrations in Hunan province during the COVID-19 (24.8%) was significantly higher than the national average (20.3%). Through the analysis of the changing character and pollution sources of haze pollution events in Hunan Province, more scientific countermeasures can be provided for the government. We use the Weather Research and Forecasting with Chemistry (WRF-Chem, V4.0) model to predict and simulate the PM2.5 concentrations under seven scenarios before the lockdown (2020.1.1-2020.1.22) and during the lockdown (2020.1.23-2020.2.14). Then, the PM2.5 concentrations under different conditions is compared to differentiate the contribution of meteorological conditions and local human activities to PM2.5 pollution. The results indicate the most important cause of PM2.5 pollution reduction is anthropogenic emissions from the residential sector, followed by the industrial sector, while the influence of meteorological factors contribute only 0.5% to PM2.5. The explanation is that emission reductions from the residential sector contribute the most to the reduction of seven primary contaminants. Finally, we trace the source and transport path of the air mass in Hunan Province through the Concentration Weight Trajectory Analysis (CWT). We found that the external input of PM2.5 in Hunan Province is mainly from the air mass transported from the northeast, accounting for 28.6%-30.0%. To improve future air quality, there is an urgent need to burn clean energy, improve the industrial structure, rationalize energy use, and strengthen cross-regional air pollution synergy control.

A multiplex method for detection of SARS-CoV-2 variants based on MALDI-TOF mass spectrometry.

The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic and the continuous evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have highlighted the significance of new detection methods for global monitoring and prevention. Although quantitative reverse transcription PCR (RT-qPCR), the current gold standard for diagnosis, performs excellently in genetic testing, its multiplexing capability is limited because of the signal crosstalk of various fluorophores. Herein, we present a highly efficient platform which combines 17-plex assays with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), enabling the targeting of 14 different mutation sites of the spike gene. Diagnosis using a set of 324 nasopharyngeal swabs or sputum clinical samples with SARS-CoV-2 MS method was identical to that with the RT-qPCR. The detection consistency of mutation sites was 97.9% (47/48) compared to Sanger sequencing without cross-reaction with other respiratory-related pathogens. Therefore, the MS method is highly potent to track and assess SARS-CoV-2 changes in a timely manner, thereby aiding the continuous response to viral variation and prevention of further transmission.

Causes of the unexpected slowness in reducing winter PM2.5 for 2014-2018 in Henan Province.

Toughest-ever clean air actions in China have been implemented nationwide to improve air quality. However, it was unexpected that from 2014 to 2018, the observed wintertime PM2.5 (particulate matter with an aerodynamic diameter of less than 2.5 µm) concentrations showed an insignificant decrease in Henan Province (HNP), a region in the west of the North China Plain. Emission controls seem to have failed to improve winter air quality in HNP, which has caused great confusion in formulating the next air improvement strategy. We employed a deweathering technique to decouple the impact of meteorological conditions. The results showed that the deweathered PM2.5 trend was -3.3%/yr in winter from 2014 to 2018, which had a larger decrease than the observed concentrations (-0.9%/yr), demonstrating that emission reduction was effective at improving air quality. However, compared with the other two megacity clusters, Beijing-Tianjin-Hebei (BTH) (-8.4%/yr) and Yangtze River Delta (YRD) (-7.4%/yr), the deweathered decreasing trend of PM2.5 for HNP remained slow. The underlying mechanism driving the changes in PM2.5 and its chemical components was further explored, using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Model simulations indicated that nitrate dominated the increase of PM2.5 components in HNP and the proportions of nitrate to total PM2.5 increased from 22.4% in January 2015 to 39.7% in January 2019. There are two primary reasons for this phenomenon. One is the limited control of nitrogen oxide emissions, which facilitates the conversion of nitric acid to particulate nitrate by ammonia. The other is unfavourable meteorological conditions, particularly increasing humidity, further enhancing nitrate formation through multiphase reactions. This study highly emphasizes the importance of reducing nitrogen oxide emissions owing to their impact on the formation of particulate nitrate in China, especially in the HNP region.

Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach.

Identifying effective drug treatments for COVID-19 is essential to reduce morbidity and mortality. Although a number of existing drugs have been proposed as potential COVID-19 treatments, effective data platforms and algorithms to prioritize drug candidates for evaluation and application of knowledge graph for drug repurposing have not been adequately explored. A COVID-19 knowledge graph by integrating 14 public bioinformatic databases containing information on drugs, genes, proteins, viruses, diseases, symptoms and their linkages is developed. An algorithm is developed to extract hidden linkages connecting drugs and COVID-19 from the knowledge graph, to generate and rank proposed drug candidates for repurposing as treatments for COVID-19 by integrating three scores for each drug: motif scores, knowledge graph PageRank scores, and knowledge graph embedding scores. The knowledge graph contains over 48 000 nodes and 13 37 000 edges, including 13 563 molecules in the DrugBank database. From the 5624 molecules identified by the motif-discovery algorithms, ranking results show that 112 drug molecules had the top 2% scores, of which 50 existing drugs with other indications approved by health administrations reported. The proposed drug candidates serve to generate hypotheses for future evaluation in clinical trials and observational studies.

A Multiplex Method for Detection of SARS-CoV-2 Variants Based on MALDI-TOF Mass Spectrometry

The recent outbreak of the coronavirus disease 2019 (COVID-19) pandemic and the continuous evolution of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have highlighted the significance of new detection methods for global monitoring and prevention. Although quantitative reverse transcription PCR (RT-qPCR), the current gold standard for diagnosis, performs excellently in genetic testing, its multiplexing capability is limited because of the signal crosstalk of various fluorophores. Herein, we present a highly efficient platform which combines 17-plex assays with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), enabling the targeting of 14 different mutation sites of the spike gene. Diagnosis using a set of 324 nasopharyngeal swab or sputum clinical samples with SARS-CoV-2 MS method was identical to that with the RT-qPCR. The detection consistency of mutation sites was 97.9% (47/48) compared to Sanger sequencing without cross-reaction with other respiratory-related pathogens. Therefore, the MS method is highly potent to track and assess SARS-CoV-2 changes in a timely manner, thereby aiding continuous response to viral variation and prevention of further transmission.

The effects of appearance personification of service robots on customer decision-making in the product recommendation context

PurposeThe COVID-19 pandemic has made contactless services such as those provided by robots increasingly pervasive. Some stores are gradually adopting service robots to sell products, which has not been explored in previous research. This study aims to explore how appearance personification of service robots affects customer decision-making in the product recommendation context.Design/methodology/approachBased on authentic in-store product recommendation service interactions, an experiment for three simulated scenarios was conducted and data was collected from 338 valid samples.FindingsThe results show appearance personification has a positive impact on customer purchase behavior while it has negative impacts on customer decision time and degree of hesitation.Originality/valueThis study not only enriches the literature on application scenarios of service robots but also supplements the literature on various customer decision-making variables in the field of service robots. It provides important practical guidance for designing robots to optimize their impact on customer decision-making.

Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry

PurposeAlthough prefabricated construction (PC) technology has attracted considerable attention worldwide because of its significant role in the global fight against COVID-19, market-driven adoption is still limited. The mechanisms for PC technology adoption have yet to be defined, which inhibits its diffusion in the construction market. This study aims to reveal the intrinsic motivation and action mechanism for PC technology adoption.Design/methodology/approachDrawing on the technology acceptance model (TAM), the study integrates characteristics from the diffusion of innovation theory to propose a multifaceted model for explaining practitioners' PC technology adoption behavior from technology, organization and environment contexts. The proposed theoretical model was empirically examined via a survey of 234 professionals in mainland China using the partial least squares-structural equation modeling technique.FindingsThe outcomes indicated that relative advantage, corporate social responsibility and market demand are significantly positively related to practitioners' perceived usefulness from PC technology. Regulatory support and trading partner support have noticeable positive effects on practitioners' perceived ease of use from PC technology. Perceived ease of use is found to positively influence perceived usefulness, and both of them have a positive influence on the attitude toward adopting PC technology. Attitude is further confirmed as an important predictor of adoption intention, which would lead to actual PC technology adoption behavior.Originality/valueTo the best of the authors' knowledge, this paper is the first attempt to explore industry perceptions toward PC technology adoption, providing valuable guidance for the effective diffusion of PC technology and laying a reliable foundation for research on other construction innovation adoption in post-COVID-19.

Spatio-Temporal Distribution Characteristics and Drivers of PM2.5 Pollution in Henan Province, Central China, before and during the COVID-19 Epidemic.

PM2.5 is the main cause of haze pollution, and studying its spatio-temporal distribution and driving factors can provide a scientific basis for prevention and control policies. Therefore, this study uses air quality monitoring information and socioeconomic data before and during the COVID-19 outbreak in 18 prefecture-level cities in Henan Province from 2017 to 2020, using spatial autocorrelation analysis, ArcGIS mapping, and the spatial autocorrelation analysis. ArcGIS mapping and the Durbin model were used to reveal the characteristics of PM2.5 pollution in Henan Province in terms of spatial and temporal distribution characteristics and analyze its causes. The results show that: (1) The annual average PM2.5 concentration in Henan Province fluctuates, but decreases from 2017 to 2020, and is higher in the north and lower in the south. (2) The PM2.5 concentrations in Henan Province in 2017-2020 are positively autocorrelated spatially, with an obvious spatial spillover effect. Areas characterized by a high concentration saw an increase between 2017 and 2019, and a decrease in 2020; values in low-concentration areas remained stable, and the spatial range showed a decreasing trend. (3) The coefficients of socio-economic factors that increased the PM2.5 concentration were construction output value > industrial electricity consumption > energy intensity; those with negative effects were: environmental regulation > green space coverage ratio > population density. Lastly, PM2.5 concentrations were negatively correlated with precipitation and temperature, and positively correlated with humidity. Traffic and production restrictions during the COVID-19 epidemic also improved air quality.

Neutralization against SARS-CoV-2 Delta/Omicron variants and B cell response after inactivated vaccination among COVID-19 convalescents.

Emerging SARS-CoV-2 variants have made COVID-19 convalescents susceptible to re-infection and have raised concern about the efficacy of inactivated vaccination in neutralization against emerging variants and antigen-specific B cell response. To this end, a study on a long-term cohort of 208 participants who have recovered from COVID-19 was conducted, and the participants were followed up at 3.3 (Visit 1), 9.2 (Visit 2), and 18.5 (Visit 3) months after SARS-CoV-2 infection. They were classified into three groups (no-vaccination (n = 54), one-dose (n = 62), and two-dose (n = 92) groups) on the basis of the administration of inactivated vaccination. The neutralizing antibody (NAb) titers against the wild-type virus continued to decrease in the no-vaccination group, but they rose significantly in the one-dose and two-dose groups, with the highest NAb titers being observed in the two-dose group at Visit 3. The NAb titers against the Delta variant for the no-vaccination, one-dose, and two-dose groups decreased by 3.3, 1.9, and 2.3 folds relative to the wild-type virus, respectively, and those against the Omicron variant decreased by 7.0, 4.0, and 3.8 folds, respectively. Similarly, the responses of SARS-CoV-2 RBD-specific B cells and memory B cells were boosted by the second vaccine dose. Results showed that the convalescents benefited from the administration of the inactivated vaccine (one or two doses), which enhanced neutralization against highly mutated SARS-CoV-2 variants and memory B cell responses. Two doses of inactivated vaccine among COVID-19 convalescents are therefore recommended for the prevention of the COVID-19 pandemic, and vaccination guidelines and policies need to be updated.

Evaluation of the Effectiveness of Remote Monitoring to Establish a Community Health Intervention During COVID-19: A Community Intervention Trial.

Background: The widespread use of telemedicine systems and medical information networks has made telemedicine one of the current trends in health care. The purpose of this article is to propose a community health intervention with remote monitoring and teleconsultation during COVID-19 for the prevention and control of COVID-19 at the rural level. Methods: In this intervention study, a randomized group of 1,500 community residents was selected. A questionnaire with acceptable validity and reliability was used to collect data. The study was conducted with the test group itself as a control, and the questionnaire was completed again 6 months after the health intervention through remote monitoring. The extent of the effect of the remote monitoring intervention on community health during COVID-19 was measured. The data were entered into SPSS 26, and the data were analyzed using the K-S normality test, t-test, and chi-square test. Results: After 6 months of the intervention, the differences in mean scores of the test group were statistically significant (p < 0.05) in cognition, perceived benefits, self-efficacy, and behavioral outcomes, with a substantial increase in mean scores for all variables. Conclusions: The application of remote monitoring during COVID-19 in rural communities can influence the health perception, benefit perception, self-efficacy, and behavior of community residents, thus effectively preventing and controlling the spread of COVID-19 in rural communities. It reduces medical barriers for rural areas while meeting.

Long-term outcomes of COVID-19 convalescents: An 18.5-month longitudinal study in Wuhan.

OBJECTIVES: This study aimed to describe the full scope of long-term outcomes and the ongoing pathophysiological alterations among COVID-19 survivors. METHODS: We established a longitudinal cohort of 208 COVID-19 convalescents and followed them at 3.3 (interquartile range [IQR]: 1.3, 4.4, visit 1), 9.2 (IQR: 9.0, 9.6, visit 2), and 18.5 (IQR: 18.2, 19.1, visit 3) months after infection, respectively. Serial changes in multiple physical and psychological outcomes were comprehensively characterized. We, in addition, explored the potential risk factors of SARS-CoV-2 antibody response and sequelae symptoms. RESULTS: We observed continuous improvement of sequelae symptoms, lung function, chest computed tomography (CT), 6-minute walk test, and the Borg dyspnea scale, whereas sequelae symptoms (at least one) and abnormal chest CT patterns still existed in 45.2% and about 30% of participants at 18.5 months, respectively. Anxiety and depression disorders were alleviated for the convalescents, although depression status was sustained for a longer duration. CONCLUSIONS: Most COVID-19 convalescents had an overall improved physical and psychological health status, whereas sequelae symptoms, residual lesions on lung function, exercise impairment, and mental health disorders were still observed in a small proportion of participants at 18.5 months after infection. Implementing appropriate preventive and management strategies for the ever-growing COVID-19 population is warranted.

Dysregulation of Innate and Adaptive Immune Responses in Asymptomatic SARS-CoV-2 Infection with Delayed Viral Clearance.

Asymptomatic infection with SARS-CoV-2 is a major concern in the control of the COVID-19 pandemic. Many questions concerning asymptomatic infection remain to be answered, for example, what are the differences in infectivity and the immune response between asymptomatic and symptomatic infections? In this study, based on a cohort established by the Wuchang District Health Bureau of Wuhan in the early stage of the COVID-19 pandemic in Wuhan in 2019, we conducted a comprehensive analysis of the clinical, virological, immunological, and epidemiological data of asymptomatic infections. The major findings of this study included: 1) the asymptomatic cohort enrolled this study exhibited low-grade but recurrent activity of viral replication; 2) despite a lack of overt clinical symptoms, asymptomatic infections exhibited ongoing innate and adaptive immune responses; 3) however, the immune response from asymptomatic infections was not activated adequately, which may lead to delayed viral clearance. Given the fragile equilibrium between viral infection and host immunity, and the delayed viral clearance in asymptomatic individuals, close viral monitoring should be scheduled, and therapeutic intervention may be needed.

Clinical evaluation of contrast-enhanced CT combined with PET/CT in diagnosis of mediastinal lymph node metastasis of non-small-cell lung cancer

Objectives: To investigate the clinical value of contrast-enhanced CT combined with PET/CT in the differential diagnosis of mediastinal lymph node metastasis (MLNM) of non-small-cell lung cancer (NSCLC). Methods: A total of 120 patients with NSCLC combined with mediastinal lymphadenopathy hospitalized in our hospital were selected. All the patients received radical resection of lung cancer and mediastinal lymphadenectomy. After pathological diagnosis, they were divided into MLNM group (malignant group, undergoing contrast-enhanced CT) and non-MLNM group (benign group, receiving contrast-enhanced CT combined with PET-CT). The results were judged by two senior radiologists independently. The results of different scanning methods and postoperative pathology were compared using the t test, χ2 test and Pearson correlation coefficient test. Results: Compared with the pathological results, contrast-enhanced CT diagnosed 31 cases, with a coincidence rate of 62%, and contrast-enhanced CT combined with PET-CT diagnosed 42 cases, with a coincidence rate of 84%, presenting a statistically significant difference (P = 0.02). Among the 120 patients with lung cancer, pathological examination confirmed MLNM in 50 patients and benign enlargement in 70 patients, contrast-enhanced CT alone detected metastasis in 40 patients and benign enlargement in 80 patients, and contrast-enhanced CT combined with PET-CT detected metastasis in 47 patients and benign enlargement in 73 patients. The sensitivity and accuracy of the latter were significantly higher than those of the former (sensitivity, P = 0.01;accuracy, P = 0.01). With the increase in the malignancy of lymph nodes, the degree of CT enhancement, the concentration of radioactive substances and SUV value increased, showing positive correlations. Conclusion: Contrast-enhanced CT combined with PET/CT in the diagnosis of MLNM of NSCLC presents higher coincidence rate, sensitivity and accuracy. With the increase in tumor malignancy, the enhancement degree and radioactive substance concentration increase. The two methods are synergistic and complementary in diagnosing MLNM.

Distinct gut microbiota and health outcomes in asymptomatic infection, viral nucleic acid test re-positive, and convalescent COVID-19 cases

Gut microbiota composition is suggested to associate with coronavirus disease 2019 (COVID-19) severity, but the impact of gut microbiota on health outcomes is largely unclear. We recruited 81 individuals from Wuhan, China, including 13 asymptomatic infection cases (Group A), 24 COVID-19 convalescents with adverse outcomes (Group C), 31 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) re-positive cases (Group D), and 13 non-COVID-19 healthy controls (Group H). The microbial features of Groups A and D were similar and exhibited higher gut microbial diversity and more abundant short-chain fatty acid (SCFA)-producing species than Group C. Group C was enriched with opportunistic pathogens and virulence factors related to adhesion and toxin production. The abundance of SCFA-producing species was negatively correlated, while Escherichia coli was positively correlated with adverse outcomes. All three groups (A, C, and D) were enriched with the mucus-degrading species Akkermansia muciniphila, but decreased with Bacteroides-encoded carbohydrate-active enzymes. The pathways of vitamin B6 metabolic and folate biosynthesis were decreased, while selenocompound metabolism was increased in the three groups. Specifically, the secondary bile acid (BA) metabolic pathway was enriched in Group A. Antibiotic resistance genes were common among the three groups. Conclusively, the gut microbiota was related to the health outcomes of COVID-19. Dietary supplementations (SCFAs, BA, selenium, folate, vitamin B6) may be beneficial to COVID-19 patients.

Establishment of primary health information in the COVID-19 outbreak: A cross-sectional study of population awareness of self-testing.

The global pandemic of the Corona Virus Disease 2019 is a severe threat to human health. This paper aims to investigate the status of mass health self-examination awareness and its influencing factors during the COVID-19 epidemic and establish complete health information to intervene in the prevention and control of the COVID-19 epidemic. The study used a simple random sampling method to survey permanent residents (9761 people) aged 15-70 years in a region of Jiangsu Province, China. The survey collected data using a questionnaire with acceptable reliability and validity. The data were entered into SPSS 26, and the data were analyzed using the chi-square test, ANOVA, and logistic regression. The differences in the status of mass health self-examination during COVID-19 were statistically significant (P < 0.05) in terms of the literacy level of the grassroots population, ease of access to medical care, primary medical and health conditions, the situation of medical examination programs, and the construction of primary health information technology. The establishment of comprehensive and systematic primary health information can effectively assist in raising people's awareness of health self-examination and promoting health behaviors, which is essential for enhancing COVID-19 prevention and intervention.

Phenonizer: A Fine-Grained Phenotypic Named Entity Recognizer for Chinese Clinical Texts.

Biomedical named entity recognition (BioNER) from clinical texts is a fundamental task for clinical data analysis due to the availability of large volume of electronic medical record data, which are mostly in free text format, in real-world clinical settings. Clinical text data incorporates significant phenotypic medical entities (e.g., symptoms, diseases, and laboratory indexes), which could be used for profiling the clinical characteristics of patients in specific disease conditions (e.g., Coronavirus Disease 2019 (COVID-19)). However, general BioNER approaches mostly rely on coarse-grained annotations of phenotypic entities in benchmark text dataset. Owing to the numerous negation expressions of phenotypic entities (e.g., "no fever," "no cough," and "no hypertension") in clinical texts, this could not feed the subsequent data analysis process with well-prepared structured clinical data. In this paper, we developed Human-machine Cooperative Phenotypic Spectrum Annotation System (http://www.tcmai.org/login, HCPSAS) and constructed a fine-grained Chinese clinical corpus. Thereafter, we proposed a phenotypic named entity recognizer: Phenonizer, which utilized BERT to capture character-level global contextual representation, extracted local contextual features combined with bidirectional long short-term memory, and finally obtained the optimal label sequences through conditional random field. The results on COVID-19 dataset show that Phenonizer outperforms those methods based on Word2Vec with an F1-score of 0.896. By comparing character embeddings from different data, it is found that character embeddings trained by clinical corpora can improve F-score by 0.0103. In addition, we evaluated Phenonizer on two kinds of granular datasets and proved that fine-grained dataset can boost methods' F1-score slightly by about 0.005. Furthermore, the fine-grained dataset enables methods to distinguish between negated symptoms and presented symptoms. Finally, we tested the generalization performance of Phenonizer, achieving a superior F1-score of 0.8389. In summary, together with fine-grained annotated benchmark dataset, Phenonizer proposes a feasible approach to effectively extract symptom information from Chinese clinical texts with acceptable performance.

Erratum: Drug Repurposing for the Treatment of COVID-19: A Knowledge Graph Approach.

[This corrects the article DOI: 10.1002/adtp.202100055.].

Efficacy of Jinhua Qinggan Granules Combined With Western Medicine in the Treatment of Confirmed and Suspected COVID-19: A Randomized Controlled Trial.

Objective: To conduct a randomized controlled clinical trial to evaluate the clinical efficacy and prognostic value of Jinhua Qinggan granules in patients with confirmed and suspected coronavirus disease 2019 (COVID-19). Methods: A total of 123 suspected and confirmed COVID-19 patients participated in this clinical trial and were randomly divided into Jinhua and Western medicine groups. For 14 days, the Jinhua group was treated with Jinhua Qinggan granules and antiviral drugs, and the Western medicine group was treated with antiviral drugs alone. We collected information on clinical symptoms, disease aggravation rates, and negative conversion rates of nucleic acids in patients, and observed the effects of anti-infective drugs. Results: There was no significant difference in symptom improvement rates between the two groups, both confirmed and suspected patients (P > 0.05). Both treatments relieved symptoms such as fever, fatigue, and diarrhea. However, the Jinhua treatment was superior in relieving fever and poor appetite. Anti-infective drug use rates were significantly lower in the Jinhua group than in the control group. Conclusion: Jinhua Qinggan granules combined with Western medicine could relieve the clinical symptoms of fever and poor appetite in COVID-19 patients, reduce the use of antibiotics to a certain extent. Clinical Trial Registration: The registration number at China Clinical Trial Registry is ChiCTR2000029601.