The effect of information overload and perceived risk on tourists' intention to travel in the post-COVID-19 pandemic.

Since the COVID-19 pandemic, the tourism economy has been seriously affected. China has implemented a direct traveling management mechanism and recovered from the pandemic faster than the rest of the world. However, the COVID-19 situation is complicated and uncontrollable because of the available unclear information including difficult medical terminologies. This study attempts to find the determinants of the travel intention of China's tourists in the post-COVID-19 epidemic. Along with information overload and perception risk, an expanded research model of the Theory of Planned Behavior (TPB) was employed to propose the theoretical framework of this study. A survey was conducted among 518 tourists who spend their holiday in Hainan, which is a popular tourist destination in China. The empirical results show that information overload positively and significantly impacted perceived risk. Furthermore, perceived risk negatively affects the intention to travel. Perceived risk also negatively affected the attitude toward traveling. However, response self-efficacy did not have a significant effect on the intention to travel. Finally, based on the analysis results, this study proposes relevant research contributions and practical recommendations with management implications for the travel industries.

Global dynamics of a diffusive SIR epidemic model with saturated incidence rate and discontinuous treatments

In this paper, we study a diffusive SIR epidemic model with saturated incidence rate and discontinuous treatments under Neumann boundary conditions. Firstly, the existence and boundedness of the solution of the system are addressed. Then, on the basis of the differential inclusions theory, we analysis the existence of endemic equilibrium. Furthermore, by constructing different appropriate Lyapunov functions, we investigate the global asymptotic stability of the disease free equilibrium(DFE) and the endemic equilibrium(EE), respectively. Additionally, numerical simulations are given to confirm the correctness of theorem. Finally, we give a brief conclusion and discussion in the end of the paper.

Impact of two epidemic control on air quality characteristics in Shijiazhuang City

Studies have shown that during the 2020 epidemic control period, air quality data has been"abnormal", but due to differences in geography and demographic factors, the survey results in different regions are not consistent. The purpose of the study is to analyze the difference in air quality under the control of the two epidemics in Shijiazhuang City, further explore the impact of control measures on air quality, and provide reference and ideas for improving air quality and adjusting atmospheric control measures. Based on the China Air Quality Online Monitoring and Analysis Platform and Zhenqi.com, with Shijiazhuang air quality as the research object, the air quality and meteorological monitoring data in the past 6 years have been collected and sorted, and the t-test and rank-sum test methods are used to analyze the air pollution status and change characteristics in the two epidemic control periods based on the air quality monitoring data of Shijiazhuang City during the epidemic control period from January 5 to February 8,2021, with comparison with the data of the same time period in 2019. With reference to changes in meteorological factors, the impact of epidemic control on air quality was comprehensively analyzed. Results indicate that in 2021, the social blockade measures against the epidemic have greatly reduced the concentrations of various pollutants. The concentrations of PM2.5,PM10,SO2,CO2, and NO2 have dropped by 52.13%,40.62%,74.93%,55.53%,44.59%,(p<0.05),respectively, compared with the same period before the epidemic (2016-2019 average levels).O3 pollution increased, and the concentration increased by 49.40%compared to before the epidemic (p<0.05);the severity of epidemic control measures also has a certain impact on air quality compared with the epidemic blockade carried out in the same period in 2020.PM2.5,PM10,CO2,and NO2 during the epidemic control period in 2021 decreased by 54.85%,37.79%,52.36%and 31.15%,respectively,(p<0.05). Analysis of meteorological factors showed that there was no significant difference in the average temperature and wind speed in Shijiazhuang during the survey period from January 5 to February 8 in the past 6 years. Compared with before the epidemic, there was no significant change in the relative humidity during the epidemic period in 2021. The relative humidity in the same period in 2020 was 65.28% higher than before the epidemic (p<0.05). There were obvious differences in air quality during the two epidemic control periods in Shijiazhuang, but the meteorological factors did not show corresponding changes. The change in air quality may be related to the strictness of the epidemic control measures and the order of implementation.

Resilience, perceived social support and professional quality of life among medical social workers during COVID-19 pandemic in Mainland China: A cross-sectional survey.

As COVID-19 rapidly overwhelmed the world in 2020, medical social workers have fought against the disease on the front lines as a member of medical teams, but little is known about the impact of the pandemic on their mental health. This study investigated the resilience, perceived social support and professional quality of life of medical social workers in Mainland China under the influence of the COVID-19 pandemic. An online questionnaire survey was applied to 319 respondents and the results showed that informal support was positively related with compassion satisfaction (r = 0.67, p < .01) and negatively correlated with job burnout (r = -0.51, p < .01) while formal support was positively associated with compassion satisfaction (r = 0.61, p < .01) and negatively associated with job burnout (r = -0.44. p < .01). Resilience was positively correlated with compassion satisfaction (r = 0.56, p < .01) and negatively correlated with job burnout (r = -0.49, p < .01). Nevertheless, neither perceived social support nor resilience was associated with secondary traumatic stress. The regression results further highlighted the role of informal social support on job burnout. Measures should be taken to enhance the professional quality of life for medical social workers during a public health crisis .

Performance Prediction of Listed Companies in Smart Healthcare Industry: Based on Machine Learning Algorithms.

With the development of wireless network, communication technology, cloud platform, and Internet of Things (IOT), new technologies are gradually applied to the smart healthcare industry. The COVID-19 outbreak has brought more attention to the development of the emerging industry of smart healthcare. However, the development of this industry is restricted by factors such as long construction cycle, large investment in the early stage, and lagging return, and the listed companies also face the problem of financing difficulties. In this study, machine learning algorithm is used to predict performance, which can not only deal with a large amount of data and characteristic variables but also analyse different types of variables and predict their classification, increasing the stability and accuracy of the model and helping to solve the problem of poor performance prediction in the past. After analysing the sample data from 53 listed companies in smart healthcare industry, we argued that the conclusion of this study can not only provide reference for listed companies in smart healthcare industry to formulate their own strategies but also provide shareholders with strategies to avoid risks and help the development of this emerging industry.

Optimization of magnetic bead-based nucleic acid extraction for SARS-CoV-2 testing using readily available reagents.

The COVID-19 pandemic has highlighted the need for generic reagents and flexible systems in diagnostic testing. Magnetic bead-based nucleic acid extraction protocols using 96-well plates on open liquid handlers are readily amenable to meet this need. Here, one such approach is rigorously optimized to minimize cross-well contamination while maintaining sensitivity.

Air quality changes in Shijiazhuang during COVID-19 outbreak

[Background] The coronavirus disease 2019（COVID-19） was first detected in December 2019. To combat the disease, a series of strict measures were adopted across the country, which led of improved air quality. This provides an opportunity to discuss the impact of human activities on air quality. [Objective] This study investigates the air quality changes in Shijiazhuang, and analyzes the impacts of epidemic prevention and control measures on air quality, so as to provide reference and ideas for further improving air quality and prevention and control measures. [Methods] The air quality data were collected online from https://www.zq12369.com/and https://aqicn.org/city/shijiazhuang/cn/. Comparisons in air quality index（AQI） and the concentrations of air pollutants(PM2.5, PM10, SO2, CO, NO2, and O3) were made between the period from December 2019 to June 2020（reference） and the same period from 2016 to 2019 by t-test and chi-square test. [Results] The daily average AQI dropped by 25.38% in Shijiazhuang during the COVID-19 prevention and control compared with the some period from 2016 to 2019（t=6.28, P < 0.05）. The proportions of pollution days during the COVID-19 outbreak in Shijiazhuang were PM2.5（44.56%）, O3（31.09%）, PM10（23.83%）, and NO2（2.59%） successively, the pollution days of PM10 decreased significantly（χ2=3.86, P < 0.05） compared with 2016-2019, but during traffic lockdown the numbers of pollution days of PM2.5 and in the mid stage of prevention the number of pollution days of O3 increased（P < 0.05）. Compared with the control period, the concentrations of the six air pollutants decreased to varying degrees（P < 0.05）, especially SO2 dropped by 55.36%.[Conclusion] The measures taken for COVID-19 control and prevention have reduced the pollution sources and emissions, which resulted in better general air quality of Shijiazhuang City, but have aggravated the pollution of O3 and other pollutants. It is necessary to further explore the causes for the aggravation of O3 pollution in order to formulate reasonable air quality control strategies.

Particulate matter exposure exacerbates susceptibility to SARS-CoV-2 infection in humanized ACE2 mice.

The global outbreak of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), as of 8 May 2021, has surpassed 150 700 000 infections and 3 279 000 deaths worldwide. Evidence indicates that SARS-CoV-2 RNA can be detected on particulate matter (PM), and COVID-19 cases are correlated with levels of air pollutants. However, the mechanisms of PM involvement in the spread of SARS-CoV-2 remain poorly understood. Here, we found that PM exposure increased the expression level of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) in several epithelial cells and increased the adsorption of the SARS-CoV-2 spike protein. Instillation of PM in a hACE2 mouse model significantly increased the expression of ACE2 and Tmprss2 and viral replication in the lungs. Furthermore, PM exacerbated the pulmonary lesions caused by SARS-CoV-2 infection in the hACE2 mice. In conclusion, our study demonstrated that PM is an epidemiological factor of COVID-19, emphasizing the necessity of wearing anti-PM masks to cope with this global pandemic.

COVID-19 and early-stage lung cancer both featuring ground-glass opacities: a propensity score-matched study.

BACKGROUND: Radiological manifestations of coronavirus disease 2019 (COVID-19) featured ground-glass opacities (GGOs), especially in the early stage, which might create confusion in differential diagnosis with early lung cancer. We aimed to specify the radiological characteristics of COVID-19 and early lung cancer and to unveil the discrepancy between them. METHODS: One hundred and fifty-seven COVID-19 patients and 374 early lung cancer patients from four hospitals in China were retrospectively enrolled. Epidemiological, clinical, radiological, and pathological characteristics were compared between the two groups using propensity score-matched (PSM) analysis. RESULTS: COVID-19 patients had more distinct symptoms, tended to be younger (P<0.0001), male (P<0.0001), and had a higher body mass index (P=0.014). After 1:1 PSM, 121 matched pairs were identified. Regarding radiological characteristics, patients with a single lesion accounted for 17% in COVID-19 and 89% in lung cancer (P<0.0001). Most lesions were peripherally found in both groups. Lesions in COVID-19 involved more lobes (median 3.5 vs. 1; P<0.0001) and segments (median 6 vs. 1; P<0.0001) and tended to have multiple types (67%) with patchy form (54%). Early lung cancer was more likely to have a single type (92%) with oval form (66%). Also, COVID-19 and early lung cancer either had some distinctive features on computed tomography (CT) images. CONCLUSIONS: Both COVID-19 and early lung cancers showed GGOs, with similar but independent features. The imaging characteristics should be fully understood and combined with epidemiological history, pathogen detection, laboratory tests, short-term CT reexamination, and pathological results to aid differential diagnosis.

Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: A retrospective, multi-center study.

Limited data are available for clinical characteristics of patients with coronavirus disease 2019 (COVID-19) outside Wuhan. This study aimed to describe the clinical characteristics of COVID-19 and identify the risk factors for severe illness of COVID-19 in Jiangsu province, China. Clinical data of hospitalized COVID-19 patients were retrospectively collected in 8 hospitals from 8 cities of Jiangsu province, China. Clinical findings of COVID-19 patients were described and risk factors for severe illness of COVID-19 were analyzed. By Feb 10, 2020, 202 hospitalized patients with COVID-19 were enrolled. The median age of patients was 44.0 years (interquartile range, 33.0-54.0). 55 (27.2%) patients had comorbidities. At the onset of illness, the common symptoms were fever (156 [77.2%]) and cough (120 [59.4%]). 66 (32.7%) patients had lymphopenia. 193 (95.5%) patients had abnormal radiological findings. 11 (5.4%) patients were admitted to the intensive care unit and none of the patients died. 23 (11.4%) patients had severe illness. Severe illness of COVID-19 was independently associated with body mass index (BMI) ≥ 28 kg/m2 (odds ratio [OR], 9.219; 95% confidence interval [CI], 2.731 to 31.126; P<0.001) and a known history of type 2 diabetes (OR, 4.326; 95% CI, 1.059 to 17.668; P = 0.041). In this case series in Jiangsu Province, COVID-19 patients had less severe symptoms and had better outcomes than the initial COVID-19 patients in Wuhan. The BMI ≥ 28 kg/m2 and a known history of type 2 diabetes were independent risk factors of severe illness in patients with COVID-19.