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1.
Journal of Pharmaceutical and Biomedical Analysis ; : 114804, 2022.
Article in English | ScienceDirect | ID: covidwho-1804615

ABSTRACT

Enzyme-labeled secondary antibody is often used to amplify the output signal in the process of antibody detection. However, its preparation process is complex and time-consuming. Herein, we fabricated an innovative hydrophilic rhodamine B-loaded / boronic acid-modified graphene oxide (HRBGO) nanocomposite, used as a substitute of enzyme-labeled second antibody. The synthetic HRBGO was loaded with generous rhodamine B and modified with boronic acid. Therefore, the HRBGO could selectively label the carbohydrate chains of Fc fragment of primary antibody through specific boronate affinity recognition, and then perform signal output and amplification by releasing rhodamine B. To verify the practicability of HRBGO, trastuzumab as a humanized monoclonal antibody targeting human epidermal growth factor receptor-2 (HER2) was selected as model antibody. A glycosylation site-blocked / HER2-immobilized magnetic nanoparticles (GHMN) was also prepared for selectively capturing trastuzumab from complex samples via specific immunoaffinity. Because the glycosylation sites of HER2 can also be labeled with the HRBGO by boronate affinity recognition, these sites were blocked by a masking agent to minimize the background signal. For specific and ultrasensitive detection of trastuzumab, the integration of GHMN and HRBGO was proposed and optimized in detail. Trastuzumab detection based on HRBGO consisted of three steps: specific capture, selective labeling, and output signal. The proposed strategy provided ultrahigh sensitivity with limit of detection of 0.35 fg mL-1 and was successfully applied in the detection of trastuzumab in spiked serum sample with recovery and relative standard deviation in the range of 98.7% to 103.8% and 3.8% to 6.0%, respectively. To assess universal applicability, the HRBGO was also successfully used for the determination of anti-SARS-COV2 RBD antibody in human serum sample.

2.
International Journal of Ophthalmology ; 15(4):533-540, 2022.
Article in English | PMC | ID: covidwho-1798637

ABSTRACT

AIM: To investigate the effects of baffle and intraocular pressure (IOP) on the aerosols generated in the noncontact tonometer (NCT) measurement and provide recommendations for the standardized use of the NCT during coronavirus disease 2019 (COVID-19). METHODS: This clinical trial included 252 subjects (312 eyes) in The Eye Hospital, Wenzhou Medical University from March 7, 2020, to March 28, 2020. Sixty subjects (120 eyes) with normal IOP were divided into two groups. One group used an NCT without a baffle, another group used an NCT with a baffle. Another 192 subjects (192 eyes) were divided into four groups: Group A1 (without a baffle+normal IOP), Group A2 (without a baffle+high IOP), Group B1 (with a baffle+normal IOP) and Group B2 (with a baffle+high IOP). Particulate matter (PM) 2.5 and PM10 generated by all subjects were quantified during the NCT measurement. The IOP values were recorded simultaneously. Effects of baffle and IOP on aerosols generated during the NCT measurement were analyzed. RESULTS: In the normal eye group with a baffle, the aerosol density decreased in a wave-like shape near the NCT with the increase in the number of people measured for IOP, demonstrating no cumulative effect. However, in the normal eye group without a baffle, there was a cumulative effect. PM2.5 and PM10 in Group A2 were higher than Group A1 (both P<0.001). The PM2.5 and PM10 in Group B2 were higher than Group B1 (P<0.01, P<0.001 respectively). The PM10 of Group B1 was lower than Group A1 (P<0.01). PM2.5 in Group B2 were lower than Group A2 (P<0.01). The median of per capita PM2.5 and PM10 in the combined Group A1+A2 were 0.80 and 1.10 μg/m3 respectively, which were higher than 0.20 and 0.60 μg/m3 in the combined Group B1+B2 (both P<0.01). The median of per capita PM2.5 and PM10 in the combined Group A1+B1 were 0.10 and 0.20 μg/m3 respectively, which were lower than 1.30 and 1.70 μg/m3 in the combined Group A2+B2 (both P<0.001). CONCLUSION: More aerosols could be generated in patients with high IOP. After the NCT is equipped with a baffle, per capita aerosol density generated decreased significantly near the NCT;And with the increase in the number of people measured for IOP, the aerosols gradually dissipated near the NCT, demonstrating no cumulative effect. Therefore, it is suggested that the NCT should be equipped with a baffle, especially for patients with high IOP.

3.
J Infect Dis ; 2022 Apr 16.
Article in English | MEDLINE | ID: covidwho-1795253

ABSTRACT

INTRODUCTION: This study aims to examine the worldwide prevalence of post COVID-19 condition, through a systematic review and meta-analysis. METHODS: PubMed, Embase, and iSearch were searched on July 5, 2021 with verification extending to March 13, 2022. Using a random effects framework with DerSimonian-Laird estimator, we meta-analyzed post COVID-19 condition prevalence at 28+ days from infection. RESULTS: 50 studies were included, and 41 were meta-analyzed. Global estimated pooled prevalence of post COVID-19 condition was 0.43 (95% CI: 0.39,0.46). Hospitalized and non-hospitalized patients have estimates of 0.54 (95% CI: 0.44,0.63) and 0.34 (95% CI: 0.25,0.46), respectively. Regional prevalence estimates were Asia- 0.51 (95% CI: 0.37,0.65), Europe- 0.44 (95% CI: 0.32,0.56), and North America- 0.31 (95% CI: 0.21,0.43). Global prevalence for 30, 60, 90, and 120 days after infection were estimated to be 0.37 (95% CI: 0.26,0.49), 0.25 (95% CI: 0.15,0.38), 0.32 (95% CI: 0.14,0.57) and 0.49 (95% CI: 0.40,0.59), respectively. Fatigue was the most common symptom reported with a prevalence of 0.23 (95% CI: 0.17,0.30), followed by memory problems (0.14 [95% CI: 0.10,0.19]). DISCUSSION: This study finds post COVID-19 condition prevalence is substantial; the health effects of COVID-19 appear to be prolonged and can exert stress on the healthcare system.

4.
Front Public Health ; 10: 838106, 2022.
Article in English | MEDLINE | ID: covidwho-1776042

ABSTRACT

In the spring semester of 2020, online flipped classroom was used to replace offline face-to-face teaching of the physiology course at Xiangya School of Medicine. In order to analyze the preferences and utilization of different teaching resources by students, registered questionnaire was applied to investigate the preference divergence of the students on the duration of different teaching videos used in the online flipped classroom model. One hundred forty-seven students of clinical medicine in grade 2018 of Xiangya School of Medicine were selected as the research objects. Three formal surveys were conducted in total. The results showed that there were significant divergences in preference of students for different durations in the first two surveys. 56.43 and 50.00% of the students preferred 15 min mini-video, whereas 43.57 and 50.00% preferred 45 min complete video. Meanwhile, students showed a significant preference for mini-video in active learning before class, with 65.00 and 59.29% watched only mini-video, 17.14 and 25.71% watched only complete videos, and 17.86 and 15.00% watched both mini and complete videos. Although most students preferred to watch mini-video in active learning before class, there was a significant proportion of students who watched complete video before class. The results suggested that the individualization of student in the online flipped classroom is prominent. Multiple logistic regression analysis showed that the selection of videos with different durations at different time points (before, in and after class) was significantly associated with the characteristics of the videos themselves. Therefore, the construction of online teaching resources and the application of teaching methods should consider the requirements of different student groups and provide a variety of online curriculum resources.


Subject(s)
Audiovisual Aids , Curriculum , Education, Distance , China , Education, Medical , Humans , Problem-Based Learning/methods , Students , Surveys and Questionnaires , Teaching Materials
5.
Front Public Health ; 9: 738412, 2021.
Article in English | MEDLINE | ID: covidwho-1775888

ABSTRACT

Background: Unbiased metagenomic next-generation sequencing (mNGS) detects pathogens in a target-independent manner. It is not well-understood whether mNGS has comparable sensitivity to target-dependent nucleic acid test for pathogen identification. Methods: This study included 31 patients with chickenpox and neurological symptoms for screening of possible varicella-zoster virus (VZV) central nervous system (CNS) infection. Microbiological diagnosing of VZV cerebrospinal fluid (CSF) infection was performed on stored CSF samples using mNGS, quantitative and qualitative VZV-specific PCR assays, and VZV IgM antibodies test. Results: The median age was 30.0 [interquartile range (IQR), 24.3-33.3] years. 51.6% of the patients were men. About 80.6% of the patients had normal CSF white blood cell counts (≤ 5 × 106/L). VZV IgM antibodies presented in 16.1% of the CSF samples, and nucleic acids were detectable in 16.1 and 9.7% using two different VZV-specific real-time PCR protocols. Intriguingly, maximal identification of VZV elements was achieved by CSF mNGS (p = 0.001 and p = 007; compared with qualitative PCR and VZV IgM antibody test, respectively), with sequence reads of VZV being reported in 51.6% (16/31) of the CSF samples. All VZV PCR positive samples were positive when analyzed by mNGS. Of note, human betaherpesvirus 6A with clinical significance was unexpectedly detected in one CSF sample. Conclusions: Our study suggests that CSF mNGS may have higher sensitivity for VZV detection than CSF VZV PCR and antibody tests, and has the advantage of identifying unexpected pathogens.


Subject(s)
Central Nervous System Infections , Chickenpox , Adult , Central Nervous System , Herpesvirus 3, Human/genetics , High-Throughput Nucleotide Sequencing/methods , Humans , Male
6.
Front Public Health ; 9: 666135, 2021.
Article in English | MEDLINE | ID: covidwho-1771101

ABSTRACT

Background: The implementation of evidence-based approaches by general practitioners (GPs) is new in the primary care setting, and few quantitative studies have evaluated the impact of contextual factors on the attendance of these approaches. Methods: In total, 892 GPs from 75 community healthcare centers (CHCs) in Shanghai completed our survey. We used logistic regression to analyze factors affecting the number of evidence-based chronic disease programs attended by GPs and whether they had held the lead position in such a program. Results: A total of 346 (38.8%) of the practitioners had never participated in any evidence-based chronic disease prevention (EBCDP) program. The EBCDP interventions in which the GPs had participated were predominantly related to hypertension, diabetes, and cardiovascular disease. However, the proportion of GPs in the lead role was relatively low, between 0.8% (programs involving prevention and control of asthma) and 5.0% (diabetes). Organizational factors and areas were significantly associated with evidence-based practices (EBPs) of the GP, while monthly income and department were the most significantly related to GPs who have the lead role in a program. The results indicated that GPs who had taken the lead position had higher scores for policy and economic impeding factors. GPs who were men, had a higher income, and worked in prevention and healthcare departments and urban areas were more likely to take the lead position. Conclusion: Evidence-based programs for chronic diseases should be extended to different types of diseases. Personal, organizational, political, and economic factors and the factors of female sex, lower income, department type, and suburban area environment should be considered to facilitate the translation of evidence to practice.


Subject(s)
General Practitioners , China , Chronic Disease , Female , Humans , Male , Primary Health Care
7.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330780

ABSTRACT

The cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the association of its receptor binding domain (RBD) with human angiotensin converting enzyme 2 (hACE2) as the first crucial step. Efficient and reliable prediction of RBD-hACE2 binding affinity changes upon amino acid substitutions can be valuable for public health surveillance and monitoring potential spillover and adaptation into non-human species. Here, we introduce a convolutional neural network (CNN) model trained on protein sequence and structural features to predict experimental RBD-hACE2 binding affinities of 8,440 variants upon single and multiple amino acid substitutions in the RBD or ACE2. The model achieves a classification accuracy of 83.28% and a Pearson correlation coefficient of 0.85 between predicted and experimentally calculated binding affinities in five-fold cross-validation tests and predicts improved binding affinity for most circulating variants. We pro-actively used the CNN model to exhaustively screen for novel RBD variants with combinations of up to four single amino acid substitutions and suggested candidates with the highest improvements in RBD-ACE2 binding affinity for human and animal ACE2 receptors. We found that the binding affinity of RBD variants against animal ACE2s follows similar trends as those against human ACE2. White-tailed deer ACE2 binds to RBD almost as tightly as human ACE2 while cattle, pig, and chicken ACE2s bind weakly. The model allows testing whether adaptation of the virus for increased binding with other animals would cause concomitant increases in binding with hACE2 or decreased fitness due to adaptation to other hosts.

8.
Preprint in English | bioRxiv | ID: ppbiorxiv-485413

ABSTRACT

The cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) involves the association of its receptor binding domain (RBD) with human angiotensin converting enzyme 2 (hACE2) as the first crucial step. Efficient and reliable prediction of RBD-hACE2 binding affinity changes upon amino acid substitutions can be valuable for public health surveillance and monitoring potential spillover and adaptation into non-human species. Here, we introduce a convolutional neural network (CNN) model trained on protein sequence and structural features to predict experimental RBD-hACE2 binding affinities of 8,440 variants upon single and multiple amino acid substitutions in the RBD or ACE2. The model achieves a classification accuracy of 83.28% and a Pearson correlation coefficient of 0.85 between predicted and experimentally calculated binding affinities in five-fold cross-validation tests and predicts improved binding affinity for most circulating variants. We pro-actively used the CNN model to exhaustively screen for novel RBD variants with combinations of up to four single amino acid substitutions and suggested candidates with the highest improvements in RBD-ACE2 binding affinity for human and animal ACE2 receptors. We found that the binding affinity of RBD variants against animal ACE2s follows similar trends as those against human ACE2. White-tailed deer ACE2 binds to RBD almost as tightly as human ACE2 while cattle, pig, and chicken ACE2s bind weakly. The model allows testing whether adaptation of the virus for increased binding with other animals would cause concomitant increases in binding with hACE2 or decreased fitness due to adaptation to other hosts.

9.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-330238

ABSTRACT

At the end of 2019, the COVID-19 emerged in Wuhan, China. It has since put global public health institutions on high alert. People reduced their traveling, and production has stopped nationwide during the epidemic. This paper explores the effect of these COVID-19-derived changes on the air quality in China. Air quality data of 367 cities around China were included. The daily air pollutants concentration (AQI,CO, O 3 , NO 2 , SO 2 , PM10, and PM2.5) were collected. We compared the air quality changes between three periods (23.1.2019-23.3.2019, 22.11.2019-22.1.2020, and 23.1.2020–23.3.2020). To compare, we calculated the daily average number of cities with pollution, and the trend in air quality index change. Furthermore, Air quality in the top 50 cities with confirmed cases and Wuhan was analyzed. During the period between 23.1.2020 and 23.3.2020, the number of cities with excellent air quality was significantly higher than that in another two periods. The concentrations of PM2.5, PM10, NO 2 , SO 2 , CO, and O 3 decreased significantly during the COVID-19 epidemic. The most significant decreases were in PM10 and NO 2 . The number of cities with good air quality in the later period was significantly higher than that a year before. The air quality has improved significantly during the COVID-19 outbreak, The reason for this change may be human activities such as reduced transportation and production stoppage.

10.
Ann Palliat Med ; 2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1743091

ABSTRACT

BACKGROUND: Sleep disturbance is well documented as a crucial element that impairs health. Depression and health-related quality of life (HRQOL), which on behalf of a patient's overall perception of emotional, physical and social well-being, are increasingly emphasized self-reported health outcomes especially during the coronavirus disease 2019 (COVID-19) pandemic. Among dialysis patients, sleep disturbance is associated with depression and poorer HRQOL. The study was designed to depict the prevalence of sleep disturbance, and to explore the association among sleep, depression, and HRQOL in patients with non-dialysis chronic kidney disease (CKD) during the COVID-19 pandemic. METHODS: A total of 172 non-dialysis CKD patients enrolled in this cross-sectional study, with sociodemographic and clinical data recorded. Sleep, HRQOL, and depression were evaluated via the Pittsburgh Sleep Quality Index (PSQI), the Kidney Disease Quality of Life 36-Item Short-Form Survey (KDQOL-36), and the 9-item Patient Health Questionnaire (PHQ-9), respectively. RESULTS: A total of 100 (58%) met the criteria for poor sleep. Good sleepers had strikingly disparate HRQOL and depression scores compared to poor sleepers. Sleep disorders were significantly associated with decreased HRQOL and increased depression in regression models adjusted or unadjusted for sociodemographic and clinical characteristics. Mediation analysis indicated depression was a significant mediator explaining 51% of the relationship between sleep status with physical component summary (PCS) and played a fully mediating role in the association between sleep and mental component summary (MCS). CONCLUSIONS: Our study suggested the high incidence of sleep disorders in patients with non-dialysis CKD during the COVID-19 pandemic, as well as the tight associations among sleep, depression, and HRQOL. Considering the negative influences of sleep and depression on HRQOL, appropriate screening and treatment for these treatable health-related domains are necessary for patients with non-dialysis CKD.

11.
Chest ; 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1739607

ABSTRACT

The outbreak of COVID-19 has brought renewed attention to past narratives of disease outbreaks. What do the Black Death and COVID-19 have in common? How we tell outbreak stories is shaped by political, cultural, social, and historical contexts. It is deeply rhetorical. The general public relies on experts (scientists, historians, and government officials) to provide credible information, but uncertainties during an outbreak can make it difficult to provide definitive answers quickly. Experts need to be conscious about the contexts in which their statements would be received. Regarding the Black Death, historians of medicine have relied heavily on a single medieval account of the outbreak, which confirmed their preconceptions about Mongol violence, allowing them to present the Black Death as an instance of biological warfare. Looking at other medieval accounts, however, makes clear that this narrative of Mongol biological warfare is false. Similarly, modern outbreak narratives also tend to use militarized language, which results in othering peoples and cultures where a disease might have originated. Given the contemporary political tensions between China and the United States, narratives about the origin of the SARS-CoV-2 virus and its transmission have led to a transnational infodemic of misinformation as well as discrimination and violence against people of Asian descent. In light of this long-running pattern, we argue for more interdisciplinary collaborations between the experts whose work is used to build outbreak narratives to adopt more critical rhetorical approaches in communicating with the public.

13.
Stress ; 25(1): 134-144, 2022 01.
Article in English | MEDLINE | ID: covidwho-1728770

ABSTRACT

The importance of social interactions has been reported in a variety of animal species. In human and rodent models, social isolation is known to alter social behaviors and change anxiety or depression levels. During the coronavirus pandemic, although people could communicate with each other through other sensory cues, social touch was mostly prohibited under different levels of physical distancing policies. These social restrictions inspired us to explore the necessity of physical contact, which has rarely been investigated in previous studies on mouse social interactions. We first conducted a long-term observation to show that pair-housed mice in a standard laboratory cage spent nearly half the day in direct physical contact with each other. Furthermore, we designed a split-housing condition to demonstrate that even with free access to visual, auditory, and olfactory social signals, the lack of social touch significantly increased anxiety-like behaviors and changed social behaviors. There were correspondingly higher levels of the pro-inflammatory cytokine interleukin-6 in the hippocampus in mice with no access to physical contact. Our study demonstrated the necessity of social touch for the maintenance of mental health in mice and could have important implications for human social interactions.


Subject(s)
Housing, Animal , Touch , Animals , Anxiety/psychology , Behavior, Animal , Male , Mice , Social Behavior , Social Isolation/psychology , Stress, Psychological
14.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-329182

ABSTRACT

Disasters usually pose a big threat to work continuity and job stability, thus having important consequences for workers’ labor market outcomes (i.e., unemployment, work absence, and lay off). Furthermore, according to the prior literature on disaster management, disaster-induced labor market disruptions tend to affect female workers more because they are more prone to constraints (such as the availability of childcare services and domestic services) and work-family conflict, suggesting increased gender inequality during disasters. In such a case, telework has emerged as a silver lining by providing workers with higher flexibility in work scheduling and helping them alleviate work-family conflict. This paper investigates whether and to what extent telework can reduce the gender inequality induced by disasters, taking the COVID-19 disaster as an example. Results show that: 1) The COVID-19 disaster leads to a larger increase in unemployment, work absence, and layoff for female workers than their male counterparts. 2) Telework can not only effectively mitigate the negative effect of the COVID-19 disaster on the labor market, but also help to reduce the gender inequality in labor market outcomes via two means: i) the higher telework rate among female workers (i.e., endowment effect) and ii) the stronger marginal effect of telework on female workers (i.e., coefficient effect). Taken together, the endowment effect of telework reduces gender inequality by 25.48% and the coefficient effect of telework reduces gender inequality by 31.94%. 3) The mitigating effect of telework is stronger in geographic areas with better digital infrastructure. Our findings are robust to other measures of constraints or alternative telework measures, which suggests that the generalizability of our results to future disasters or disruptions when physical presence in the workplace could be a challenge for workers. Our study contributes to the emerging literature on how information technologies can be leveraged to mitigate the disaster-induced gender inequality in the labor market.

15.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329048

ABSTRACT

Background: The human microbiome plays an important role in modulating the host metabolism and immune system. Connections and interactions have been found between the microbiome of the gut and oral-pharynx in the context of SARS-CoV-2 and other viral infections, hence, to broaden our understanding of host-viral responses in general and to deepen our knowledge of COVID-19, we performed a large-scale, systematic evaluation of the effect of SARS-CoV-2 infection on human microbiota in patients with varying disease severity. Results We processed 521 samples from 203 COVID-19 patients with varying disease severity and 94 samples from 31 healthy donors, consisting of 213 pharyngeal swabs, 250 sputum, and 152 faecal samples, and obtained meta-transcriptomes as well as SARS-CoV-2 sequences from each sample. Detailed assessment of these samples revealed altered microbial composition and function in the upper respiratory tract (URT) and gut of COVID-19 patients, and these changes are significantly associated with disease severity. Moreover, URT and gut microbiota show different patterns of alteration, where gut microbiome seems to be more variable and in direct correlation with viral load;and microbial community in upper respiratory tract renders high risk of antibiotic resistance. Longitudinally, microbial composition remains relatively stable during the study period. Conclusions Our study has revealed different trends and the relative sensitivity of microbiome in different body sites to SARS-CoV-2 infection. Furthermore, while the use of antibiotics is often essential for prevention and treatment of secondary infections, our results indicate a need to evaluate potential antibiotic resistance in the management of COVID-19 patients in the ongoing pandemic. Moreover, longitudinal follow-up to monitor the restoration of the microbiome could enhance our understanding of the long-term effects of COVID-19.

16.
Sustainability ; 14(4):2474, 2022.
Article in English | MDPI | ID: covidwho-1707883

ABSTRACT

Our research aims to establish an evaluation framework and evaluate the sustainability of scientific research in universities. Based on the concept of Education for Sustainable Development and the function of scientific research activities, an evaluation framework was constructed including three dimensions: the sustainable trend of scientific research activity, research performance related to the topic of sustainable development, and sustainability of scientific research contributions. Descriptive analysis, Data Envelopment Analysis, and a Statistical Index Method were used to calculate the sustainability of scientific research of world-class universities in China. Results show that China’s world-class universities published more articles related to sustainable development than the best-performing universities in the UK and USA. They make sustainable contributions to society through cultivating Ph.D. graduates, publishing research papers, and transforming science and technology. However, the sustainable trend of the scientific research of universities is still to be improved. The result of resource efficiency is relatively low, and attention should be paid to the waste of human and financial resources. In addition, universities should improve their ability to withstand external risks to minimize the influence of external public emergencies such as COVID-19.

17.
Addiction ; 2022 Feb 07.
Article in English | MEDLINE | ID: covidwho-1704933

ABSTRACT

AIMS: To estimate the associations between high-risk alcohol consumption and (1) severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroconversion, (2) self-reported new SARS-CoV-2 infection and (3) symptomatic COVID-19. DESIGN: Prospective cohort study. SETTING: Indiana University Bloomington (IUB), IN, USA. PARTICIPANTS: A total of 1027 IUB undergraduate students (64% female), aged 18 years or older, residing in Monroe County, Indiana, seronegative for SARS-CoV-2 at study baseline. MEASUREMENTS: Primary exposure was high-risk alcohol consumption measured with an Alcohol Use Disorders Identification Test (AUDIT) questionnaire score of 8 or more. Primary outcome was SARS-CoV-2 seroconversion since baseline, assessed with two SARS-CoV-2 antibody tests, at baseline (September 2020) and end-line (November 2020). Secondary outcomes were (a) self-reported new SARS-CoV-2 infection at the study end-line and (b) self-reported symptomatic COVID-19 at baseline. FINDINGS: Prevalence of high-risk alcohol consumption was 32 %. In models adjusted for demographics, students with high-risk alcohol consumption status had 2.44 [95% confidence interval (CI) = 1.35, 4.25] times the risk of SARS-CoV-2 seroconversion and 1.84 (95% CI = 1.04, 3.28) times the risk of self-reporting a positive SARS-CoV-2 infection, compared with students with no such risk. We did not identify any association between high-risk alcohol consumption and symptomatic COVID-19 (prevalence ratio = 1.17, 95% CI = 0.93, 1.47). Findings from sensitivity analyses corroborated these results and suggested potential for a dose-response relationship. CONCLUSIONS: Among American college students, high-risk alcohol consumption appears to be associated with higher risk for severe acute respiratory syndrome coronavirus 2 seroconversion/infection.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324347

ABSTRACT

The objective of the study is to examine coronavirus disease (COVID-19) related discussions, concerns, and sentiments that emerged from tweets posted by Twitter users. We analyze 4 million Twitter messages related to the COVID-19 pandemic using a list of 25 hashtags such as "coronavirus," "COVID-19," "quarantine" from March 1 to April 21 in 2020. We use a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigram, bigrams, salient topics and themes, and sentiments in the collected Tweets. Popular unigrams include "virus," "lockdown," and "quarantine." Popular bigrams include "COVID-19," "stay home," "corona virus," "social distancing," and "new cases." We identify 13 discussion topics and categorize them into five different themes, such as "public health measures to slow the spread of COVID-19," "social stigma associated with COVID-19," "coronavirus news cases and deaths," "COVID-19 in the United States," and "coronavirus cases in the rest of the world". Across all identified topics, the dominant sentiments for the spread of coronavirus are anticipation that measures that can be taken, followed by a mixed feeling of trust, anger, and fear for different topics. The public reveals a significant feeling of fear when they discuss the coronavirus new cases and deaths than other topics. The study shows that Twitter data and machine learning approaches can be leveraged for infodemiology study by studying the evolving public discussions and sentiments during the COVID-19. Real-time monitoring and assessment of the Twitter discussion and concerns can be promising for public health emergency responses and planning. Already emerged pandemic fear, stigma, and mental health concerns may continue to influence public trust when there occurs a second wave of COVID-19 or a new surge of the imminent pandemic.

19.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324346

ABSTRACT

The study aims to understand Twitter users' discourse and psychological reactions to COVID-19. We use machine learning techniques to analyze about 1.9 million Tweets (written in English) related to coronavirus collected from January 23 to March 7, 2020. A total of salient 11 topics are identified and then categorized into ten themes, including "updates about confirmed cases," "COVID-19 related death," "cases outside China (worldwide)," "COVID-19 outbreak in South Korea," "early signs of the outbreak in New York," "Diamond Princess cruise," "economic impact," "Preventive measures," "authorities," and "supply chain." Results do not reveal treatments and symptoms related messages as prevalent topics on Twitter. Sentiment analysis shows that fear for the unknown nature of the coronavirus is dominant in all topics. Implications and limitations of the study are also discussed.

20.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-315682

ABSTRACT

Background: In the high incidence period of COVID-19, it is very important to quickly classify and evaluate the prognosis of patients through limited clinical antibody data. Methods Chemiluminescence immunoassay was used to detect serum IgM and IgG concentrations in 1951 patients diagnosed with COVID-19, and R language was used to analyze the influence of factors such as antibody, age, gender and concomitant diseases on the prognosis of SARS-CoV-2 patients. Results The results showed that the incidence of COVID-19 was consistent with the characteristics of the elderly, and patients with hypertension, diabetes, stroke, hypoalbuminemia and anemia were at increased risk of critical illness ( p  < 0.05). The analysis of antibodies results showed that there were no significant difference in antibodies concentration between COVID-19 patients of different ages. While there were no significant difference in antibodies concentration between mild and severe patients, the expression levels of serum IgM and IgG in critically ill patients decreased ( p  = 0.000 and 0.013), and high IgM and IgG concentration could reduce the incidence of critical illness ( p  = 0.003 and 0.015). Except in the 41–60 and 91–100 age groups, the simultaneous low expression of IgM and IgG in COVID-19 patients was significantly positively correlated with the severity of illness ( p   =  0.000). Conclusions IgM and IgG were important prognostic factors for COVID-19 patients. It was hence vital to carry out special clinical classification for the management and early intervention for patients with low IgM/IgG concentrations and with concomitant diseases.

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