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.

Joint Rigid Motion Correction and Sparse-View CT via Self-Calibrating Neural Field (preprint)

Neural Radiance Field (NeRF) has widely received attention in Sparse-View (SV) CT reconstruction problems as a self-supervised deep learning framework. NeRF-based SVCT methods model the desired CT image as a continuous function that maps coordinates to intensities and then train a Multi-Layer Perceptron (MLP) to learn the function by minimizing loss on the SV measurement. Thanks to the continuous representation provided by NeRF, the function can be approximated well and thus the high-quality CT image is reconstructed. However, existing NeRF-based SVCT methods strictly suppose there is completely no relative motion during the CT acquisition because they require accurate projection poses to simulate the X-rays that scan the SV sinogram. Therefore, these methods suffer from severe performance drops for real SVCT imaging with motion. To this end, this work proposes a self-calibrating neural field that recovers the artifacts-free image from the rigid motion-corrupted SV measurement without using any external data. Specifically, we parametrize the coarse projection poses caused by rigid motion as trainable variables and then jointly optimize these variables and the MLP. We perform numerical experiments on a public COVID-19 CT dataset. The results indicate that our model significantly outperforms two latest NeRF-based methods for SVCT reconstruction with four different levels of rigid motion.

Evaluation on Performance of Domestic A-Share Listed Cross-Border E-Commerce Export Enterprises Based on Hierarchy Process and Grey Correlation

According to the three principles of cross-border export trade such as the main business, physical transaction, and data availability, eight domestic A-share listed cross-border e-commerce export enterprises are selected to build a performance evaluation index system integrating operation ability, solvency, profitability, and growth ability. Based on the three-year annual public report data from 2018 to 2020, the grey correlation degree and ranking of the performance of eight enterprises are calculated by using the hierarchical method and grey theory. Excluding the factors of COVID-19 outbreak, the two aspects of operation capability and solvency are the key factors that affect the performance of such enterprises at the present stage. It provides reference for the development of cross-border e-commerce enterprises in China and also provides some reference for other types of e-commerce enterprises. [ FROM AUTHOR] Copyright of Mathematical Problems in Engineering is the property of Hindawi Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Impact of COVID-19 on College Students' at One of the Most Diverse Campuses in the United States: A Factor Analysis of Survey Data (preprint)

Objective: This survey study is designed to understand the impact of the COVID-19 pandemic on stress among specific sub-populations of college students. Design, Settings and Participants: An online questionnaire was sent to the students from University of Nevada, Las Vegas between 2020 October and December to assess the psychological impact of COVID-19. A total of 2,091 respondents signed the consent form online and their responses were collected. Methods: The Perceived Stress levels of college students were analyzed via exploratory factor analysis of a survey of college students, which was collected at the University of Nevada, Las Vegas (UNLV). An explanatory factor analysis was carried out on the Perceived Stress Scale (PSS-10) results. We subsequently analyzed each factor using stepwise linear regression that focused on various socio-demographic groups. Results: A two-factor model was obtained using the explanatory factor analysis. After comparing with the past studies that investigated the factor structure of the PSS-10 scale, we identified these two factors as "Anxiety" and "Irritability". The subsequent stepwise linear regression analysis suggested that gender and age (P< 0.01) are significantly associated with both factors. However, the ethnicities of students are not significantly associated with both factors. Conclusions: To our knowledge, this is the first study that assessed the perceived stress of university students in the US during the COVID-19 pandemic. We showed that the PSS-10 scale could be summarized as a two-factor structure through an exploratory factor analysis. A stepwise regression approach was used and we found both of the factors are significantly associated with the gender of the participants. However, we found no significant association between both factors and ethnicity. In summary, our findings will help identify students with higher risk for stress and mental health issues in pandemics and future crises.

Risk assessment of global COVID-19 pandemic in January 2022

Objective: To assess the global epidemic of Coronavirus disease 2019(COVID-19)in January 2022 and the risk of importation.

Rational development of a combined mRNA vaccine against COVID-19 and influenza (preprint)

As the world continues to experience the COVID-19 pandemic, seasonal influenza remain a cause of severe morbidity and mortality globally. Worse yet, coinfection with SARS-CoV-2 and influenza A virus (IAV) leads to more severe clinical outcomes. The development of a combined vaccine against both COVID-19 and influenza is thus of high priority. Based on our established lipid nanoparticle (LNP)-encapsulated mRNA vaccine platform, we developed and characterized a novel mRNA vaccine encoding the HA antigen of influenza A (H1N1) virus, termed ARIAV. Then, ARIAV was combined with our COVID-19 mRNA vaccine ARCoV, which encodes the receptor binding domain (RBD) of the SARS-CoV-2 S protein, to formulate the final combined vaccine, AR-CoV/IAV. Further characterization demonstrated that immunization with two doses of AR-CoV/IAV elicited robust protective antibodies as well as antigen-specific cellular immune responses against SARS-CoV-2 and IAV. More importantly, AR-CoV/IAV immunization protected mice from coinfection with IAV and the SARS-CoV-2 Alpha and Delta variants. Our results highlight the potential of the LNP-mRNA vaccine platform in preventing COVID-19 and influenza, as well as other respiratory diseases.

Risk assessment of global COVID-19 pandemic in February 2021

Objective: To assess the global epidemic of COVID-19 in February 2021 and the risk of importation.

The precision of epidemiological investigation of COVID-19 transmission in Shanghai, China.

BACKGROUND: Shanghai had a local outbreak of COVID-19 from January 21 to 24. Timely and precise strategies were taken to prevent further spread of the disease. We discussed and shared the experience of COVID-19 containment in Shanghai. PROCESS: The first two patients worked at two hospitals but no staff from the two hospitals were infected. The suspected case and his two close contacts were confirmed to be infected within 12 h. The testing rate of individuals was low. The scope of screening was minimized to two related districts and the close contact tracing was completed within 12 h, which were precise and cost-effective. CONCLUSIONS: Active monitoring, precise epidemiological investigation and timely nucleic acid testing help discover new cases, minimize the scope of screening, and interrupt the transmission.

The differential demographic pattern of Coronavirus Disease 2019 patient fatality outside Hubei and from six hospitals in Hubei, China: a descriptive analysis (preprint)

Background: The Coronavirus Disease 2019 (COVID-19) epidemic has been largely controlled in China, to the point where case fatality rate (CFR) data can be comprehensively evaluated.Methods: Data on confirmed patients, with a final outcome reported as of 29 March 2020, were obtained from official websites and other internet sources. The hospitalized CFR (HCFR) was estimated, epidemiological features described, and risk factors for a fatal outcome identified.Findings: The overall CFR in China was estimated to be 4.6% (95% CI 4.5%-4.8%). It increased with age and was higher in males than females. The highest CFR observed was in male patients ≥70 years old. Although the outcome of infection is generally worse for males, this adverse effect from male sex decreased as people get old. Differential age/sex CFR patterns across geographical regions were found: the age effect on CFR was greater in other provinces outside Hubei than in Wuhan. An effect of longer interval from symptom onset to admission was only observed outside Hubei, not in Wuhan. By performing multivariate analysis and survival analysis, the higher CFR was associated with older age, and male sex. Only in regions outside Hubei, longer interval from symptom onset to admission, were associated with higher CFR.Interpretation: This up-to-date and comprehensive picture of COVID-19 CFR and its drivers will help healthcare givers target limited medical resources to patients with high risk of fatality.

A rapid screening model for early predicting novel coronavirus pneumonia in Zhejiang Province of China: A Multicenter Study (preprint)

Novel coronavirus pneumonia (NCP) has been widely spread in China and several other countries. Early finding of this pneumonia from huge numbers of suspects gives clinicians a big challenge. The aim of the study was to develop a rapid screening model for early predicting NCP in a Zhejiang population, as well as its utility in other areas. A total of 880 participants who were initially suspected of NCP from Jan 17 to Feb 19 were included. Potential predictors were selected via stepwise logistic regression analysis. The model was established based on epidemiological features, clinical manifestations, white blood cell count, and pulmonary imaging changes, with the area under receiver operating characteristic (AUROC) curve of 0.920 (95% confidence interval : 0.902-0.938; AUROC=0.915, and its standard deviation of 0.028, as evaluated in 5-fold cross-validation). At a value of whether the predicted score >4.0, the model could detect NCP with a specificity of 98.3%; at a cut-off value of < -0.5, the model could rule out NCP with a sensitivity of 97.9%. The study demonstrated that the rapid screening model was a helpful and cost-effective tool for early predicting NCP and had great clinical significance given the high activity of NCP.

Recommendations for standardized management of CML patients in the core epidemic area of COVID-19(Multi-center survey results in Hubei Province, China) (preprint)

Background Since late December 2019, the outbreak of the novel coronavirus disease, COVID-19, that began in Wuhan, has become endemic in China and more than 100 countries and regions in the world. There is no report about the prevalence of COVID-19 in CML patients untill now. We aimed to describe the clinical course, outcomes of CML patients with COVID-19 and prevalence of COVID-19 in CML patients. Methods In this multi-center survey, cross-sectional survey, observational study, the clinical data of CML patients with COVID-19 in each center were collected. Simultaneously, an online survey was conducted for information about the CML patients under the management at each center by asking the CML patients to complete a questionnaire,from February 15, 2020 to February 21, 2020. The questionnaire includes demographic data, place of residence, smoking status, CML diagnosis and treatment, comorbidities, combined medications, epidemiological history, symptoms(fever, cough, shortness of breath, etc) during the epidemic. Additional clinical data was collected on respondents suspected or confirmed to have COVID-19. We described and analyzed the prevalence of COVID-19 in CML patients, and focus on the clinical characteristics and outcomes of COVID-19 patients. Data were compared between the CML patients with optimal response and those with non-optimal response. The primary outcome was prevalence of COVID-19 in CML patients, as of Feb 21, 2020. Secondary outcomes included the history of epidemiology of CML patients, the clinical characteristics and outcomes of CML patients with COVID-19 . Findings Of 392 respondents, 223( 56.9%) were males, and 240( 61.2%) were 50 years or younger. Only 10 patients took drugs irregularly due to the influence of the epidemic because of traffic control, pharmacies unable to operate normally, etc. In the history of epidemiology, there were 4 patients with definite contact with COVID-19, of which 3 were remote contact and 1 was close contact. 12 respondents had fever, cough or shortness of breath during the epidemic, 1 case (common type) was confirmed with COVID-19 and cured after treatment. 1 patient was clinically diagnosed and succumbed. 1 of 299 (0.3%) patients with an optimal response was diagnosed with COVID-19. Of the 50 patients who failed to respond to CML treatment or had a poor response, 1 patient (2%) had a clinical diagnosis of COVID-19. Interpretation While the 392 CML respondents required regular referrals to hospitals, they did not have much contact with COVID-19 patients during the outbreak. Patients who failed to achieved an optimal response to CML therapy appear more likely to have a symptomatic infection with SARS-CoV-2. Older patients with comorbidities are at increased risk of death.

Prevalence of novel coronavirus pneumonia in the early stage of transmission and responding strategies in Japan / 上海预防医学

Novel coronavirus pneumonia disease (COVID-19) caused by SARS-CoV-2 began to emerge in Wuhan, Hubei, China in December 2019. It is currently spreading globally including Japan. The COVID-19 case in Japan began to appear in middle January 2020 and continued to increase over time. The period from middle January to the end of February is considered to be the initial stage of domestic transmission in Japan. This article described the spread of 935 COVID-19 cases related to Japan by the end of February 2020, including the 15 infected Japanese returned from Wuhan, the 696 infected individuals in the large-scale cruise ship 'Diamond Princess' and the 224 infected individuals in Japan. This paper summarizes the measures to control the spread of SARS-CoV-2 in Japan, such as limiting RT-PCR detection for SARS-CoV-2, reducing the number of patients with mild illness who go to medical institutions unnecessarily, formulating guidelines for SARS-CoV-2 infection consultation, canceling large gatherings and temporarily closing schools. This paper further points out the problems encountered in the prevention and control of the spread of SARS-CoV-2 in Japan, such as the slow detection of RT-PCR, the risk of infection faced by medical staff, the regional differences in the domestic health care service system, the confusion of information disclosure and management. The above introduction as allows us to acquire a better understanding of the new coronavirus pneumonia in Japan and the world and may provide reference for the control the epidemic of COVID-19 in worldwide.

Analysis of 8 274 cases of new coronavirus nucleic acid detection and co-infection in Wuhan / 中华检验医学杂志

Objective@#To investigate the positive rate for 2019-nCoV tests and co-infections in Wuhan district.@*Methods@#A total of 8 274 cases in Wuhan were enrolled in this cross-sectional study during January 20 to February 9, 2020, and were tested for 2019-nCoV using fluorescence quantitative PCR. Both respiratory tract samples (nasopharynx, oropharynx, sputum and alveolar lavage fluid) and non-respiratory tract samples (urine, feces, anal swabs, blood and conjunctival sac swabs) were collected. If both orf1ab and N genes are positive, they are classified as nucleic acid test positive group; if both orf1ab and N genes are negative, they are classified as negative group; if single gene target is positive, they are classified as suspicious group. Individuals were divided into male group and female group according to sex. At the same time, 316 patients were tested for 13 respiratory pathogens by multiplex PCR.@*Results@#Among the 8 274 subjects, 2 745 (33.2%) were 2019-nCoV infected; 5 277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test; and 252 cases (3.05%) was not definitive (inconclusive result). The age of cases with COVID-19 patients and inconclusive cases was significantly higher than that of cases without 2019-nCoV infection (40 vs 56, t=27.569, P<0.001; 52 vs 56, t=6.774, P<0.001). The positive rate of 13 respiratory pathogens multiple tests was significantly lower in 104 subjects who were positive for 2019-nCoV compared with those in subjects who were negative for 2019-nCoV test (5.77% vs 18.39%, χ2=24.105, P=0.003). Four types of respiratory tract samples and five types of non-respiratory tract samples were found to be positive for 2019-nCoV nucleic acid test.@*Conclusion@#The 2019-nCoV nucleic acid positive rate in male is higher than in female. Co-infections should be pay close attention in COVID-19 patients. 2019-nCoV nucleic acid can be detected in non-respiratory tract samples.

Clinical diagnosis of 8274 samples with 2019-novel coronavirus in Wuhan (preprint)

Background: 2019-Novel coronavirus (2019-nCoV) outbreaks create challenges for hospital laboratories because thousands of samples must be evaluated each day. Sample types, interpretation methods, and corresponding laboratory standards must be established. The possibility of other infections should be assessed to provide a basis for clinical classification, isolation, and treatment. Accordingly, in the present study, we evaluated the testing methods for 2019-nCoV and co-infections. Methods: We used a fluorescence-based quantitative PCR kit urgently distributed by the Chinese CDC to detect 8274 close contacts in the Wuhan region against two loci on the 2019-nCoV genome. We also analyzed 613 patients with fever who underwent multiple tests for 13 respiratory pathogens; 316 subjects were also tested for 2019-nCoV. Findings: Among the 8274 subjects, 2745 (33.2%) had 2019-nCoV infection; 5277 (63.8%) subjects showed negative results in the 2019-nCoV nucleic acid test (non-019-nCoV); and 252 cases (3.0%) because only one target was positive, the diagnosis was not definitive. Sixteen patients who originally had only one positive target were re-examined a few days later; 14 patients (87.5%) were finally defined as 2019-nCoV-positive, and 2 (12.5%) were finally defined as negative. The positive rates of nCoV-NP and nCovORF1ab were 34.7% and 34.7%, respectively. nCoV-NP-positive only and nCovORF1ab-positive cases accounted for 1.5% and 1.5%, respectively. In the 316 patients with multiple respiratory pathogens, 104 were positive for 2019-nCov and 6/104 had co-infection with coronavirus (3/104), influenza A virus (2/104), rhinovirus (2/104), and influenza A H3N2 (1/104); the remaining 212 patients had influenza A virus (11/202), influenza A H3N2 (11/202), rhinovirus (10/202), respiratory syncytial virus (7/202), influenza B virus (6/202), metapneumovirus (4/202), and coronavirus (2/202). Interpretation: Clinical testing methods for 2019-nCoV require improvement. Importantly, 5.8% of 2019-nCoV infected and 18.4% of non-2019-nCoV-infected patients had other pathogen infections. It is important to treat combined infections and perform rapid screening to avoid cross-contamination of patients. A test that quickly and simultaneously screens as many pathogens as possible is needed.