Efficacy and Safety of Huashi Baidu Granules in Treating Patients with SARS-CoV-2 Omicron Variant: A Single-Center Retrospective Cohort Study.

OBJECTIVE: To evaluate the efficacy and safety of Huashi Baidu Granules (HSBD) in treating patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant. METHODS: A single-center retrospective cohort study was conducted during COVID-19 Omicron epidemic in the Mobile Cabin Hospital of Shanghai New International Expo Center from April 1st to May 23rd, 2022. All COVID-19 patients with asymptomatic or mild infection were assigned to the treatment group (HSBD users) and the control group (non-HSBD users). After propensity score matching in a 1:1 ratio, 496 HSBD users of treatment group were matched by propensity score to 496 non-HSBD users. Patients in the treatment group were administrated HSBD (5 g/bag) orally for 1 bag twice a day for 7 consecutive days. Patients in the control group received standard care and routine treatment. The primary outcomes were the negative conversion time of nucleic acid and negative conversion rate at day 7. Secondary outcomes included the hospitalized days, the time of the first nucleic acid negative conversion, and new-onset symptoms in asymptomatic patients. Adverse events (AEs) that occurred during the study were recorded. Further subgroup analysis was conducted in vaccinated (378 HSBD users and 390 non-HSBD users) and unvaccinated patients (118 HSBD users and 106 non-HSBD users). RESULTS: The median negative conversion time of nucleic acid in the treatment group was significantly shortened than the control group [3 days (IQR: 2-5 days) vs. 5 days (IQR: 4-6 days); P<0.01]. The negative conversion rate of nucleic acid in the treatment group were significantly higher than those in the control group at day 7 (91.73% vs. 86.90%, P=0.014). Compared with the control group, the hospitalized days in the treatment group were significantly reduced [10 days (IQR: 8-11 days) vs. 11 days (IQR: 10.25-12 days); P<0.01]. The time of the first nucleic acid negative conversion had significant differences between the treatment and control groups [3 days (IQR: 2-4 days) vs. 5 days (IQR: 4-6 days); P<0.01]. The incidence of new-onset symptoms including cough, pharyngalgia, expectoration and fever in the treatment group were lower than the control group (P<0.05 or P<0.01). In the vaccinated patients, the median negative conversion time and hospitalized days were significantly shorter than the control group after HSDB treatment [3 days (IQR: 2-5 days) vs. 5 days (IQR: 4-6 days), P<0.01; 10 days (IQR: 8-11 days) vs. 11 days (IQR: 10-12 days), P<0.01]. In the unvaccinated patients, HSBD treatment efficiently shorten the median negative conversion time and hospitalized days [4 days (IQR: 2-6 days) vs. 5 days (IQR: 4-7 days), P<0.01; 10.5 days (IQR: 8.75-11 days) vs. 11.0 days (IQR: 10.75-13 days); P<0.01]. No serious AEs were reported during the study. CONCLUSION: HSBD treatment significantly shortened the negative conversion time of nuclear acid, the length of hospitalization, and the time of the first nucleic acid negative conversion in patients infected with SARS-COV-2 Omicron variant (Trial registry No. ChiCTR2200060472).

Quantifying the COVID-19-affected tourism education in China: a potential crisis in tourism recovery

Human resources is a crucial factor in supporting the development of tourism as a labour-intensive industry. This research enhances the understanding of China's tourism education associated with the spread of COVID-19 and its implications for tourism recovery. Initial findings imply that: COVID-19 had a profound lagging negative effect on the intention to apply for tourism-related majors of examinees, which is severe challenging for tourism recovery, and the impact was more pronounced in typical tourism-dependent cities than in non-tourism-dependent cities. The MICE Economics and Management was least affected, while the Sports Tourism was most affected. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Therapeutic mechanisms and impact of traditional Chinese medicine on COVID-19 and other influenza diseases

Coronavirus disease 2019 (COVID-19), first reported in Wuhan, China, has rapidly spread worldwide. Traditional Chinese medicine (TCM) has been used to prevent and treat viral epidemics and plagues for over 2,500 years. In the guidelines on fighting against COVID-19, the National Health Commission of the People's Republic of China has recommended certain TCM formulas, namely Jinhua Qinggan granule (JHQGG), Lianhua Qingwen granule (LHQWG), Qingfei Paidu decoction (QFPDD), Xuanfei Baidu granule (XFBD), Xuebijing injection (XBJ), and Huashi Baidu granule (HSBD) for treating COVID-19 infected individuals. Among these six TCM formulas, JHQGG and LHQWG effectively treated mild/moderate and severe COVID-19 infections. XFBD therapy is recommended for mild COVID-19 infections, while XBJ and HSBD effectively treat severe COVID-19 infections. The internationalization of TCM faces many challenges due to the absence of a clinical efficacy evaluation system, insufficient research evidence, and a lack of customer trust across the globe. Therefore, evidence-based research is crucial in battling this infectious disease. This review summarizes SARS-CoV-2 pathogenesis and the history of TCM used to treat various viral epidemics, with a focus on six TCM formulas. Based on the evidence, we also discuss the composition of various TCM formulas, their underlying therapeutic mechanisms, and their role in curing COVID-19 infections. In addition, we evaluated the roles of six TCM formulas in the treatment and prevention of other influenza diseases, such as influenza A (H1N1), severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS). Furthermore, we highlighted the efficacy and side effects of single prescriptions used in TCM formulas.Copyright © 2021

Using the internet search data to investigate symptom characteristics of COVID-19: A big data study.

OBJECTIVE: Analyzing the symptom characteristics of Coronavirus Disease 2019(COVID-19) to improve control and prevention. METHODS: Using the Baidu Index Platform (http://index.baidu.com) and the website of Chinese Center for Disease Control and Prevention as data resources to obtain the search volume (SV) of keywords for symptoms associated with COVID-19 from January 1 to February 20 in each year from 2017 to 2020 and the epidemic data in Hubei province and the other top 9 impacted provinces in China. Data of 2020 were compared with those of the previous three years. Data of Hubei province were compared with those of the other 9 provinces. The differences and characteristics of the SV of COVID-19-related symptoms, and the correlations between the SV of COVID-19 and the number of newly confirmed/suspected cases were analyzed. The lag effects were discussed. RESULTS: Comparing the SV from January 1, 2020 to February 20, 2020 with those for the same period of the previous three years, Hubei's SV for cough, fever, diarrhea, chest tightness, dyspnea, and other symptoms were significantly increased. The total SV of lower respiratory symptoms was significantly higher than that of upper respiratory symptoms (P＜0.001). The SV of COVID-19 in Hubei province was significantly correlated with the number of newly confirmed/suspected cases (r confirmed = 0.723, r suspected = 0.863, both p < 0.001). The results of the distributed lag model suggested that the patients who searched relevant symptoms on the Internet may begin to see doctors in 2-3 days later and be confirmed in 3-4 days later. CONCLUSION: The total SV of lower respiratory symptoms was higher than that of upper respiratory symptoms, and the SV of diarrhea also increased significantly. It warned us to pay attention to not only the symptoms of the lower respiratory tract but also the gastrointestinal symptoms, especially diarrhea in patients with COVID-19. Internet search behavior had a positive correlation with the number of newly confirmed/suspected cases, suggesting that big data has an important role in the early warning of infectious diseases.

Xuanfei Baidu Decoction regulates NETs formation via CXCL2/CXCR2 signaling pathway that is involved in acute lung injury.

Acute lung injury (ALI) and acute respiratory distress syndrome (ARDS) are life-threatening symptoms in Coronavirus Disease 2019 (COVID-19) patients. Xuanfei Baidu Decoction (XFBD) is a recommend first-line traditional Chinese medicine (TCM) formula therapeutic strategy for COVID-19 patients. Prior studies demonstrated the pharmacological roles and mechanisms of XFBD and its derived effective components against inflammation and infections through multiple model systems, which provided the biological explanations for its clinical use. Our previous work revealed that XFBD inhibited macrophages and neutrophils infiltration via PD-1/IL17A signaling pathway. However, the subsequent biological processes are not well elucidated. Here, we proposed a hypothesis that XFBD can regulate the neutrophils-mediated immune responses, including neutrophil extracellular traps (NETs) formation and the generation of platelet-neutrophil aggregates (PNAs) after XFBD administration in lipopolysaccharide (LPS)-induced ALI mice. The mechanism behind it was also firstly explained, that is XFBD regulated NETs formation via CXCL2/CXCR2 axis. Altogether, our findings demonstrated the sequential immune responses of XFBD after inhibiting neutrophils infiltration, as well as shedding light on exploiting the therapy of XFBD targeting neutrophils to ameliorate ALI during the clinical course.

New insights for infection mechanism and potential targets of COVID-19: Three Chinese patent medicines and three Chinese medicine formulas as promising therapeutic approaches.

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high pathogenicity and infectiousness has become a sudden and lethal pandemic worldwide. Currently, there is no accepted specific drug for COVID-19 treatment. Therefore, it is extremely urgent to clarify the pathogenic mechanism and develop effective therapies for patients with COVID-19. According to several reliable reports from China, traditional Chinese medicine (TCM), especially for three Chinese patent medicines and three Chinese medicine formulas, has been demonstrated to effectively alleviate the symptoms of COVID-19 either used alone or in combination with Western medicines. In this review, we systematically summarized and analyzed the pathogenesis of COVID-19, the detailed clinical practice, active ingredients investigation, network pharmacology prediction and underlying mechanism verification of three Chinese patent medicines and three Chinese medicine formulas in the COVID-19 combat. Additionally, we summarized some promising and high-frequency drugs of these prescriptions and discussed their regulatory mechanism, which provides guidance for the development of new drugs against COVID-19. Collectively, by addressing critical challenges, for example, unclear targets and complicated active ingredients of these medicines and formulas, we believe that TCM will represent promising and efficient strategies for curing COVID-19 and related pandemics.

Did the COVID-19 pandemic impact urticaria information-seeking behavior in China? A retrospective longitudinal study.

Purpose: To investigate information-seeking behavior related to urticaria before and during the COVID-19 pandemic in China. Methods: Search query data for terms related to urticaria were retrieved using Baidu Index database from October 23, 2017 to April 23, 2022, and daily COVID-19 vaccination doses data were obtained from the website of the Chinese Center for Disease Control and Prevention. Among the 23 eligible urticaria search terms, four urticaria themes were generated as classification, symptom, etiology, and treatment of urticarial, respectively. Baidu Search Index (BSI) value for each term were extracted to analyze and compare the spatial and temporal distribution of online search behavior for urticaria before and after the COVID-19 pandemic, and to also explore the correlation between search query and daily COVID-19 vaccination doses. Results: The classification of urticaria accounted for nearly half of the urticaria queries on the internet. Regular seasonal patterns of BSI were observed in urticaria-related online search, by attaining its highest level in spring and summer and lowest level in winter. The BSIs of all urticaria themes significantly increased after the COVID-19 pandemic than that before the pandemic (all P<0.05). Xizang, Qinghai and Ningxia are the most active geographical areas for increased urticaria-searching activities after the COVID-19 pandemic. There was also a significant positive correlation between daily BSIs and daily COVID-19 vaccination doses in each urticaria theme. Cross-correlation analysis found that the search of symptom, etiology, and treatment attained their strongest correlation with daily COVID-19 vaccination doses at 11-27 days before the injection of vaccine, imply vaccination hesitation related to concerns of urticaria. Conclusions: This study used the internet as a proxy to provide evidence of public search interest and spatiotemporal characteristics of urticaria, and revealed that the search behavior of urticaria have increased significantly after the COVID-19 pandemic and COVID-19 vaccination. It is anticipated that the findings about such increase in search behavior, as well as the behavior of urticaria-related vaccine-hesitancy, will help guide public health education and policy regulation.

Mapping Population Distribution with High Spatiotemporal Resolution in Beijing Using Baidu Heat Map Data

Population distribution data with high spatiotemporal resolution are of significant value and fundamental to many application areas, such as public health, urban planning, environmental change, and disaster management. However, such data are still not widely available due to the limited knowledge of complex human activity patterns. The emergence of location-based service big data provides additional opportunities to solve this problem. In this study, we integrated ambient population data, nighttime light data, and building volume data;innovatively proposed a spatial downscaling framework for Baidu heat map data during work time and sleep time;and mapped the population distribution with high spatiotemporal resolution (i.e., hourly, 100 m) in Beijing. Finally, we validated the generated population distribution maps with high spatiotemporal resolution using the highest-quality validation data (i.e., mobile signaling data). The relevant results indicate that our proposed spatial downscaling framework for both work time and sleep time has high accuracy, that the distribution of the population in Beijing on a regular weekday shows "centripetal centralization at daytime, centrifugal dispersion at night" spatiotemporal variation characteristics, that the interaction between the purpose of residents' activities and the spatial functional differences leads to the spatiotemporal evolution of the population distribution, and that China's "surgical control and dynamic zero COVID-19" epidemic policy was strongly implemented. In addition, our proposed spatial downscaling framework can be transferred to other regions, which is of value for governmental emergency measures and for studies about human risks to environmental issues.

Big Data Statistics of Logistics Warehousing Supply and Demand in Key Cities of Central and Western China Based on Baidu Index and Warehouse in Cloud

Based on the Baidu Index, taking "warehousing"and "warehouse"as the keywords, the Baidu search index of "warehousing"and "warehouse"nationwide is statistically analyzed. It is found that the Baidu search index with "warehousing"and "warehouse"as the keywords has significantly increased before and after the COVID-19 epidemic, which shows that the basic role of logistics warehousing in the national economic and social development is increasingly obvious, and the corresponding demand for logistics warehousing is growing. Based on the big data of Warehouse in Cloud, incomplete statistics of "warehousing demand"of "demand location"in China's provinces are similar to the analysis of differences in the source places (regions and provinces) of different search groups through the "population portrait"of Baidu Index. The "warehousing demand"and "warehousing supply"of the key cities in central and Western China are counted. Focusing on the key cities in central and Western China, the correlation analysis of warehousing rent and demand area is carried out. It is found that, on the one hand, the regional logistics warehousing demand is 3 years (the lease term is less than 1 year or 1-3 years), with intra-period volatility. On the other hand, regional centers (National Central Cities) have absolute advantages in the attraction of regional logistics and warehousing. Furthermore, in recent years, due to the impact of the COVID-19 epidemic and extreme meteorological and geological disasters, the adverse impact on the regional economic and social development will show that the demand for logistics and warehousing will be interrupted, reduced and lagged, and the growth will be restored in subsequent years. The average rent of key cities in Western China is 22.52 yuan/m2·month, the average vacancy rate is 11.65%, and there are 1359 warehouses in the park. The average rent of key cities in the central region is 23.5 yuan/m2·month, the average vacancy rate is 13.86%, and there are 1070 warehouses in the park. From the perspective of rent, Changsha shows the highest rent, while Taiyuan shows the lowest rent. Furthermore, the vacancy rate of Chongqing and Xi'an are the highest and lowest, respectively. There is a correlation between the variable of warehousing rent in 2022 and the total retail sales of consumer goods in 2021 (Spearman correlation coefficient is significant). There is a correlation between the variable of average warehousing demand area in 2019-2021 and the sample of the third industry production value in 2021 and the sample variable of total import and export volume of goods in 2021 (Pearson correlation coefficient is significant). The variable of average warehousing demand area in 2019-2021 and the sample variable of resident population. There is a correlation between the total retail sales of social consumer goods in 2021 (Spearman correlation coefficient is significant). On the one hand, the statistical analysis of big data on the digital warehousing information platform can provide reference for the prediction of supply and demand of logistics warehousing and modern logistics service industry in the high-quality development of the region. On the other hand, the spatial econometric analysis of logistics industry and regional economic growth represented by logistics warehousing needs further research. CCS CONCEPTS •Human-centered computing ∼Collaborative and social computing ∼Collaborative and social computing theory, concepts and paradigms ∼Computer supported cooperative work © 2022 ACM.

Early warning signals for Omicron outbreaks in China: a retrospective study.

The Omicron variant has become the dominant COVID-19 variant worldwide due to its rapid and cryptic spread; therefore, successful early warning is of great importance to be able to control epidemics in their early phase, before developing into large outbreaks. COVID-19-related Baidu search index, which reflects human behavior to a certain degree, was used to retrospectively detect the warning signs for Omicron variant outbreaks in China in 2022. The characteristics and effects of warning signs were analyzed in detail. We detected the presence of early warning signs (both high and low thresholds) and found that these occurred 4-7 days earlier than traditional epidemiological surveillance and >20 days earlier than the implementation of the local "lockdown" policy. Compared with the "high threshold" warning, the early warning effect of the "low threshold" is also vital because it indicates a complacency about epidemic prevention and control. However, there is obvious heterogeneity in the optimal threshold for detecting early warning signs and their distribution in different cities. Multi-source and multi-point early warning systems should be established via combining internet-based big data in the future to conduct effective and early real-time warning. This would create precious time for the early control of COVID-19 outbreaks. This article is protected by copyright. All rights reserved.

Increasing public concern on insomnia during the COVID-19 outbreak in China: An info-demiology study.

Background: Since December 2019, an unexplained pneumonia has broken out in Wuhan, Hubei Province, China. In order to prevent the rapid spread of this disease, quarantine or lockdown measures were taken by the Chinese government. These measures turned out to be effective in containing the contagious disease. In spite of that, social distancing measures, together with disease itself, would potentially cause certain health risks among the affected population, such as sleep disorder. We herein conducted this web search analysis so as to examine the temporal and spatial changes of public search volume of the mental health topic of "insomnia" during COVID-19 pandemic in China. Methods: The data sources included Baidu Index (BDI) to analyze related search terms and the official website of the National Health Commission of the People's Republic of China to collect the daily number of newly confirmed COVID-19 cases. Following a descriptive analysis of the overall search situation, Spearman's correlation analysis was used to analyze the relationship between the daily insomnia-related search values and the daily newly confirmed cases. The means of search volume for insomnia-related terms during the COVID-19 outbreak period (January 23rd, 2020 to April 8th, 2020) were compared with those during 2016-2019 using Student's t test. Finally, by analyzing the overall daily mean of insomnia in various provinces, we further evaluated whether there existed regional differences in searching for insomnia during the COVID-19 outbreak period. Results: During the COVID-19 outbreak period, the number of insomnia-related searches increased significantly, especially the average daily the BDI for the term "1 min to fall asleep immediately". Spearman's correlation analysis showed that 6 out of the 10 insomnia-related keywords were significantly positively related to the daily newly confirmed cases. Compared with the same period in the past four years, a significantly increased search volume was found in 60.0% (6/10) insomnia-related terms during the COVID-19 outbreak period. We also found that Guangdong province had the highest number of searches for insomnia-related during the pandemic. Conclusions: The surge in the number of confirmed cases during the COVID-19 pandemic has led to an increase in concern and online searches on this topic of insomnia. Further studies are needed to determine whether the search behavior truly reflect the real-time prevalence profile of relevant mental disorders, and further to establish a risk prediction model to determine the prevalence risk of psychopathological disorders, including insomnia, using insomnia-related BDI and other well-established risk factors.

Early Warning and Monitoring of Coronavirus Disease 2019 Using Baidu Search Index and Baidu Information Index in Guangxi, China

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease, and it is important to detect early and monitor the disease trend for policymakers to make informed decisions. We explored the predictive utility of Baidu Search Index and Baidu Information Index for early warning of COVID-19 and identified search keywords for further monitoring of epidemic trends in Guangxi. A time-series analysis and Spearman correlation between the daily number of cases and both the Baidu Search Index and Baidu Information Index were performed for seven keywords related to COVID-19 from January 8 to March 9, 2020. The time series showed that the temporal distributions of the search terms "coronavirus," "pneumonia" and "mask" in the Baidu Search Index were consistent and had 2 to 3 days' lead time to the reported cases;the correlation coefficients were higher than 0.81. The Baidu Search Index volume in 14 prefectures of Guangxi was closely related with the number of reported cases;it was not associated with the local GDP. The Baidu Information Index search terms "coronavirus" and "pneumonia" were used as frequently as 192,405.0 and 110,488.6 per million population, respectively, and they were also significantly associated with the number of reported cases (r(s) > 0.6), but they fluctuated more than for the Baidu Search Index and had 0 to 14 days' lag time to the reported cases. The Baidu Search Index with search terms "coronavirus," "pneumonia" and "mask" can be used for early warning and monitoring of the epidemic trend of COVID-19 in Guangxi, with 2 to 3 days' lead time.

Psychological Impact of COVID-19 Lockdown and Its Evolution: A Case Study Based on Internet Searching Data during the Lockdown of Wuhan 2020 and Shanghai 2022.

It has been three years since the initial outbreak of COVID-19 in Wuhan, China, which incurred huge damage both physically and psychologically on human's normal life. As a prevention measure, the lockdown was first adopted by Wuhan, then by a long list of Chinese cities and many other major cities around the world. Lockdown is the most restrictive social distancing strategy, turning out effective in mitigating the spreading of COVID-19 on the community level, which, however, cuts off all social interactions and isolates healthy people from each other. The isolated nature of the lockdown could induce severe mental health issues, forming one major source of depression and domestic violence. Given the potential side effect, a comprehensive investigation based on reliable data sources is needed to evaluate the real psychological impact of COVID-19 lockdown and its evolution over time, particularly in the time when the Omicron variant, known for its low death risk, dominates the pandemic. Based on the Baidu Searching Index data collected for Wuhan and Shanghai, two major cities in China that suffered from long-lasting (over two months) lockdowns in 2020 and 2022, respectively, it is found that the major psychological issue during the lockdown period is not induced by the spreading of COVID-19, but by the execution of lockdown. With the deepening of knowledge about COVID-19 and the decrease in the death risk, the psychological impact of lockdown keeps increasing, while the impact of virus spreading becomes less important and even irrelevant to depression and domestic violence issues. The findings reveal that from the psychological perspective, the negative effect of lockdown already overweighs the positive one, which is especially true for the Omicron variant provided its almost ignorable death risk. Therefore, it is necessary to re-evaluate the yield and cost of lockdown for those countries where the COVID-19 pandemic has not yet come to an end.

Xuanfei Baidu Formula attenuates LPS-induced acute lung injury by inhibiting the NF-κB signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Acute lung injury (ALI) is a common manifestation of COVID-19. Xuanfei Baidu Formula(XFBD) is used in China to treat mild or common damp-toxin obstructive pulmonary syndrome in COVID-19 patients. However, the active ingredients of XFBD have not been extensively studied, and its mechanism of action in the treatment of ALI is not well understood. AIM OF THE STUDY: The purpose of this study was to investigate the mechanism of action of XFBD in treating ALI in rats, by evaluating its active components. MATERIALS AND METHODS: Firstly, the chemical composition of XFBD was identified using ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry. The potential targets of XFBD for ALI treatment were predicted using network pharmacological analysis. Finally, the molecular mechanism of XFBD was validated using a RAW264.7 cell inflammation model and a mouse ALI model. RESULTS: A total of 113 compounds were identified in XFBD. Network pharmacology revealed 34 hub targets between the 113 compounds and ALI. The results of Kyoto Encyclopedia of Genes and Genomes and gene ontology analyses indicated that the NF-κB signaling pathway was the main pathway for XFBD in the treatment of ALI. We found that XFBD reduced proinflammatory factor levels in LPS-induced cellular models. By examining the lung wet/dry weight ratio and pathological sections in vivo, XFBD was found that XFBD could alleviate ALI. Immunohistochemistry results showed that XFBD inhibited ALI-induced increases in p-IKK, p-NF-κB p65, and iNOS proteins. In vitro experiments demonstrated that XFBD inhibited LPS-induced activation of the NF-κB pathway. CONCLUSION: This study identified the potential practical components of XFBD, combined with network pharmacology and experimental validation to demonstrate that XFBD can alleviate lung injury caused by ALI by inhibiting the NF-κB signaling pathway.

Using search trends to analyze web-based users' behavior profiles connected with COVID-19 in mainland China: infodemiology study based on hot words and Baidu Index.

Background: Mainland China, the world's most populous region, experienced a large-scale coronavirus disease 2019 (COVID-19) outbreak in 2020 and 2021, respectively. Existing infodemiology studies have primarily concentrated on the prospective surveillance of confirmed cases or symptoms which met the criterion for investigators; nevertheless, the actual impact regarding COVID-19 on the public and subsequent attitudes of different groups towards the COVID-19 epidemic were neglected. Methods: This study aimed to examine the public web-based search trends and behavior patterns related to COVID-19 outbreaks in mainland China by using hot words and Baidu Index (BI). The initial hot words (the high-frequency words on the Internet) and the epidemic data (2019/12/01-2021/11/30) were mined from infodemiology platforms. The final hot words table was established by two-rounds of hot words screening and double-level hot words classification. Temporal distribution and demographic portraits of COVID-19 were queried by search trends service supplied from BI to perform the correlation analysis. Further, we used the parameter estimation to quantitatively forecast the geographical distribution of COVID-19 in the future. Results: The final English-Chinese bilingual table was established including six domains and 32 subordinate hot words. According to the temporal distribution of domains and subordinate hot words in 2020 and 2021, the peaks of searching subordinate hot words and COVID-19 outbreak periods had significant temporal correlation and the subordinate hot words in COVID-19 Related and Territory domains were reliable for COVID-19 surveillance. Gender distribution results showed that Territory domain (the male proportion: 67.69%; standard deviation (SD): 5.88%) and Symptoms/Symptom and Public Health (the female proportion: 57.95%, 56.61%; SD: 0, 9.06%) domains were searched more by male and female groups respectively. The results of age distribution of hot words showed that people aged 20-50 (middle-aged people) had a higher online search intensity, and the group of 20-29, 30-39 years old focused more on Media and Symptoms/Symptom (proportion: 45.43%, 51.66%; SD: 15.37%, 16.59%) domains respectively. Finally, based on frequency rankings of searching hot words and confirmed cases in Mainland China, the epidemic situation of provinces and Chinese administrative divisions were divided into 5 levels of early-warning regions. Central, East and South China regions would be impacted again by the COVID-19 in the future.

Investor attention and the COVID-19 concept stocks in China's stock market

Purpose This paper investigates the impact of investor attention on the COVID-19 concept stocks in China's stock market from the perspectives of the macroeconomy, the stock market and the COVID-19 pandemic. Design/methodology/approach On the basis of controlling the time effects and individual fixed effects, this paper studies the impact of investor attention on the COVID-19 concept stocks in China's stock market through a set of fixed effect panel data models. Among them, investor attention focuses on macroeconomy, stock market and the COVID-19 pandemic, respectively, while stock indicators cover return, volatility and turnover. In addition, this paper also examines the heterogeneity influence of investor attention on the COVID-19 concept stocks from the perspective of time and stock classification. Findings Findings indicate that the attention to macroeconomy does not have a statistically significant effect on the return, unlike the attention to stock market and COVID-19 incident. Three types of investor attention have significant positive effects on the volatility and turnover rate. During the outbreak of the domestic epidemic, the impact of investor attention was significantly higher than that during the outbreak of the epidemic overseas. A finer-grained analysis shows that the attention to stock market has significantly increased the return of preventive type and treatment type stocks, while diagnostic-related stocks have been most affected by the attention to COVID-19 incident. Research limitations/implications The major limitation of this work is the construction of investor attention. Although Baidu index is widely used, investor attention can be assessed more accurately based on more unstructured data. In addition, the effect of the COVID-19 can also be investigated in a longer time domain. Further research can be combined with the dynamics of the COVID-19 pandemic to more comprehensively evaluate its impact on the stock market. Originality/value The research proves that investor attention plays an important role in stock pricing and provides empirical evidence on the behavioral foundations of the conceptual sector of the stock market under uncertainty. It also has practical implications for regulators and investors interested in conducting accurate asset allocation and risk assessment.

Xuanfei Baidu formula alleviates impaired mitochondrial dynamics and activated NLRP3 inflammasome by repressing NF-κB and MAPK pathways in LPS-induced ALI and inflammation models.

BACKGROUND: Xuanfei Baidu Formula (XBF) is an effective traditional Chinese medicine (TCM) remedy for treating coronavirus disease 2019 (COVID-19) in China. This herbal medicine has shown effects in reducing clinical symptoms and shortening the average length of hospital stay for COVID-19 patients. Previous studies have demonstrated that XBF alleviates acute lung injury (ALI) by regulating macrophage-mediated immune inflammation, but the mechanisms of action remain elusive. PURPOSE: This study aimed to evaluate the lung-protective and anti-inflammatory effects of XBF and its underlying mechanisms. METHODS: Here, XBF's effects were investigated in an ALI mouse model induced by inhalation of atomized lipopolysaccharide (LPS). Besides, the LPS-induced inflammation model in RAW264.7 cells was used to clarify the underlying mechanisms of XBF against ALI. RESULTS: Our results showed that XBF treatment alleviated LPS-induced lung injury, as evidenced by reduced histopathological changes, pulmonary alveoli permeability, fibrosis, and apoptosis in the lung tissues. In addition, inflammation was alleviated as shown by decreased levels of tumor necrosis factor (TNF)-α, interleukin (IL)-6, IL-1ß in serum and bronchoalveolar lavage fluid (BALF), and reduced white blood cell (WBC) count in BALF. Furthermore, consistent with the in vivo assay, XBF inhibited LPS-induced inflammatory cytokines release and pro-inflammatory polarization in RAW264.7 cells. Mechanistically, XBF increased mitochondrial fusion by upregulating Mfn1 and attenuated NLRP3 inflammasome activation by repressing Casp11, respectively, to inhibit NF-κB and MAPK pathways, thus repressing pro-inflammatory macrophage polarization. CONCLUSION: In this study, we demonstrate that XBF exerts anti-ALI and -inflammatory effects by recovering mitochondrial dynamics and reducing inflammasome activation, providing a biological illustration of the clinical efficacy of XBF in treating COVID-19 patients.

Online public attention toward allergic rhinitis in Wuhan, China: Infodemiology study using Baidu index and meteorological data.

Background: With the popularization of the Internet and medical knowledge, more and more people are learning about allergic rhinitis (AR) on the Internet. Objective: This study aims to analyze the epidemiological characteristics and online public attention to AR in Wuhan, China, utilizing the most popular search engine in mainland China and meteorological data of Wuhan. Methods: To study the Internet attention and epidemiological characteristics of AR in Wuhan, the search volume (SV) of "Allergic Rhinitis" in Mandarin and AR-related search terms from 1 January 2014 through 31 December 2021 were recorded. For user interest, the search and demand data were collected and analyzed. Results: The yearly average Baidu SV of AR in both Wuhan and China increased year by year but began to decline gradually after the COVID-19 pandemic. Baidu SV of AR in Wuhan exhibited significant seasonal variation, with the first peak was from March to May and the second peak occurring between September and October. Correlation analysis revealed a moderate positive correlation between the monthly average SV of "Allergic Rhinitis" and "Mites" and "Mites + Pollen Allergy" in Wuhan, a weak positive correlation between the monthly average SV of "Allergic Rhinitis" and "Pollen Allergy," and a positive correlation between monthly SV of "Allergic Rhinitis" and the meteorological index of pollen allergy (MIPA). Conclusion: The attention given to the topic on the internet, as measured by the search volume, was reflective of the situation in Wuhan, China. It has the potential to predict the epidemiological characteristics of AR and help medical professionals more effectively plan seasonal AR health education.

The effect of interurban movements on the spatial distribution of population

Understanding how interurban movements can modify the spatial distribution of the population is important for transport planning but is also a fundamental ingredient for epidemic modeling. We illustrate this on vacation trips for all transportation modes in China during the Lunar New Year and compare the results for 2019 with the ones for 2020 where travel bans were applied for mitigating the spread of a novel coronavirus (COVID-19). We first show that inter-urban travel flows are broadly distributed and display both large temporal and spatial fluctuations, making their modeling very difficult. When flows are larger, they appear to be more dispersed over a larger number of origins and destinations, creating de facto hubs that can spread an epidemic at a large scale. These movements quickly induce (in about a week for this case) a very strong population concentration in a small set of cities. We characterize quantitatively the return to the initial distribution by defining a pendular ratio which allows us to show that this dynamics is in general very slow and even stopped for the 2020 Lunar New Year due to travel restrictions. Travel restrictions obviously limit the spread of the diseases between different cities, but have thus the counter-effect of keeping high concentration in a small set of cities, a priori favoring intra-city spread, unless individual contacts are strongly limited. These results shed some light on the statistics of interurban movements and how they modify the national distribution of populations, a crucial ingredient for devising effective control strategies at a national level. Copyright © 2022 Ye, Hu, Ji and Barthelemy.