Metagenomic Pathogen Sequencing in Resource-Scarce Settings: Lessons Learned and the Road Ahead

Metagenomic next-generation sequencing (mNGS) is the process of sequencing all genetic material in a biological sample. The technique is growing in popularity with myriad applications including outbreak investigation, biosurveillance, and pathogen detection in clinical samples. However, mNGS programs are costly to build and maintain, and additional obstacles faced by low- and middle-income countries (LMICs) may further widen global inequities in mNGS capacity. Over the past two decades, several important infectious disease outbreaks have highlighted the importance of establishing widespread sequencing capacity to support rapid disease detection and containment at the source. Using lessons learned from the COVID-19 pandemic, LMICs can leverage current momentum to design and build sustainable mNGS programs, which would form part of a global surveillance network crucial to the elimination of infectious diseases.

Internet addiction: Prevalence and relationship with academic burnout among undergraduates during widespread online learning.

PURPOSE: We aimed to investigate the prevalence of Internet addiction (IA) and explore its related factors among undergraduates during widespread online learning in China. DESIGN AND METHODS: The online survey was conducted in April 2020. The Young diagnostic questionnaire and academic burnout scale were respectively used to measure IA and academic burnout. FINDINGS: A total of 28.4% of 7562 participants developed IA, which correlated with academic burnout. Additionally, positive attitude and practice towards COVID-19 and exercise were protective factors of it. PRACTICE IMPLICATIONS: IA was associated with academic burnout, and better cognition of COVID-19 and positive lifestyles might reduce its risk.

Problematic Internet Use Was Associated With Psychological Problems Among University Students During COVID-19 Outbreak in China.

Background: As the coronavirus disease 2019 (COVID-19) pandemic progressed globally, school closures and home quarantine may cause an increase in problematic Internet use among students in universities. Such a traumatic stress event may also contribute to the development of posttraumatic stress disorder (PTSD), depressive, and anxiety symptoms. This study aimed to evaluate the prevalence of PTSD, depressive, and anxiety symptoms as well as the predictive role of problematic Internet use in the above-mentioned psychological problems in university students. Methods: A cross-sectional study was conducted through an online survey of 8,879 students in China between April 20 and April 26, 2020. The presence of PTSD, depressive, and anxiety symptoms and problematic Internet use were evaluated using PTSD Checklist for DSM-5, the Center for Epidemiologic Studies Depression 9-item scale, the generalized anxiety disorder 7-item scale, and the Young diagnostic questionnaire, respectively. Sociodemographic information and the knowledge, attitude, and practice (KAP) toward COVID-19 data were also collected. Results: A total of 4,834 (54.4%) participants were female, and 7,564 (85.2%) were undergraduate students. A total of 615 students (6.9%) reported PTSD symptoms; 5.2% (465) and 10.1% (896) reported moderate to severe depressive and anxiety symptoms, respectively. The problematic Internet use was significantly associated with higher risk of PTSD, depressive, and anxiety symptoms (odds ratio 2.662 [95% CI, 2.239-3.165], odds ratio 4.582 [95% CI, 3.753-5.611], odds ratio 3.251 [95% CI, 2.814-3.757], respectively; all P < 0.001). Lower attitude and practice scores also contributed to the risk of depressive, anxiety, and PTSD symptoms (P < 0.05). Conclusions: Psychological problems should be paid more attention, and problematic Internet use may be a predictor when screening high-risk students for psychological problems. Our results will aid in timely psychological screening, which is meaningful in the prevention and intervention of psychological problems.

Correction: Xiao, H., et al. Social Distancing among Medical Students during the 2019 Coronavirus Disease Pandemic in China: Disease Awareness, Anxiety Disorder, Depression, and Behavioral Activities. Int. J. Environ. Res. Public Health 2020, 17, 5047.

In our recently published article [...].

Correction: Xiao, H., et al. Social Distancing among Medical Students during the 2019 Coronavirus Disease Pandemic in China: Disease Awareness, Anxiety Disorder, Depression, and Behavioral Activities. Int. J. Environ. Res. Public Health 2020, 17, 5047

In our recently published article [...]

Nomogram for Predicting COVID-19 Disease Progression Based on Single-Center Data: Observational Study and Model Development.

BACKGROUND: In late December 2019, a pneumonia caused by SARS-CoV-2 was first reported in Wuhan and spread worldwide rapidly. Currently, no specific medicine is available to treat infection with COVID-19. OBJECTIVE: The aims of this study were to summarize the epidemiological and clinical characteristics of 175 patients with SARS-CoV-2 infection who were hospitalized in Renmin Hospital of Wuhan University from January 1 to January 31, 2020, and to establish a tool to identify potential critical patients with COVID-19 and help clinical physicians prevent progression of this disease. METHODS: In this retrospective study, clinical characteristics of 175 confirmed COVID-19 cases were collected and analyzed. Univariate analysis and least absolute shrinkage and selection operator (LASSO) regression were used to select variables. Multivariate analysis was applied to identify independent risk factors in COVID-19 progression. We established a nomogram to evaluate the probability of progression of the condition of a patient with COVID-19 to severe within three weeks of disease onset. The nomogram was verified using calibration curves and receiver operating characteristic curves. RESULTS: A total of 18 variables were considered to be risk factors after the univariate regression analysis of the laboratory parameters (P<.05), and LASSO regression analysis screened out 10 risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were age (OR 1.035, 95% CI 1.017-1.054; P<.001), CK level (OR 1.002, 95% CI 1.0003-1.0039; P=.02), CD4 count (OR 0.995, 95% CI 0.992-0.998; P=.002), CD8 % (OR 1.007, 95% CI 1.004-1.012, P<.001), CD8 count (OR 0.881, 95% CI 0.835-0.931; P<.001), and C3 count (OR 6.93, 95% CI 1.945-24.691; P=.003). The areas under the curve of the prediction model for 0.5-week, 1-week, 2-week and 3-week nonsevere probability were 0.721, 0.742, 0.87, and 0.832, respectively. The calibration curves showed that the model had good prediction ability within three weeks of disease onset. CONCLUSIONS: This study presents a predictive nomogram of critical patients with COVID-19 based on LASSO and Cox regression analysis. Clinical use of the nomogram may enable timely detection of potential critical patients with COVID-19 and instruct clinicians to administer early intervention to these patients to prevent the disease from worsening.

Knowledge, attitudes, and practices towards COVID-19 among primary school students in Hubei Province, China.

This study was aimed to investigate the knowledge, attitudes, and practices (KAP) towards coronavirus disease 2019 (COVID-19) among school-aged children in the Hubei province when children were being confined to their homes. The questionnaire included questions of KAP about COVID-19, depressive and anxiety symptoms scales. Multivariable generalized linear regressions models were applied to estimate the unstandardized regression coefficients (ß) of KAP. The awareness rates about COVID-19 were 70.1%-99.5% for all 1650 valid questionnaires. 37.2% of the participants quite worried about being infected with COVID-19. Approximately 96% of them washed hands in certain situations, while 85.6% of them washed hands after coughing or sneezing. Compared to the students without depressive symptoms, those who had depressive symptoms scored lower of total KAP, knowledge, attitudes, and practice. The findings suggest that primary students had a relatively good awareness of COVID-19 during the epidemic, as well as optimistic attitudes and appropriate practices. However, some items of appropriate practices still needed to be enhanced.

Social Distancing among Medical Students during the 2019 Coronavirus Disease Pandemic in China: Disease Awareness, Anxiety Disorder, Depression, and Behavioral Activities.

BACKGROUND: During the coronavirus disease (COVID-19) pandemic, harsh social distancing measures were taken in China to contain viral spread. We examined their impact on the lives of medical students. METHODS: A nation-wide cross-sectional survey of college students was conducted from 4-12 February 2020. We enrolled medical students studying public health in Beijing and Wuhan to assess their COVID-19 awareness and to evaluate their mental health status/behaviors using a self-administered questionnaire. We used the Patient Generalized Anxiety Disorder-7 and Health Questionnaire-9 to measure anxiety disorders and depression. We used multivariable logistic regression and path analysis to assess the associations between covariates and anxiety disorder/depression. RESULTS: Of 933 students, 898 (96.2%) reported wearing masks frequently when going out, 723 (77.5%) reported daily handwashing with soap, 676 (72.5%) washed hands immediately after arriving home, and 914 (98.0%) reported staying home as much as possible. Prevalence of anxiety disorder was 17.1% and depression was 25.3%. Multivariable logistic regression showed anxiety to be associated with graduate student status (odds ratio (aOR) = 2.0; 95% confidence interval (CI): 1.2-3.5), negative thoughts or actions (aOR = 1.6; 95% CI: 1.4-1.7), and feeling depressed (aOR = 6.8; 95% CI: 4.0-11.7). Beijing students were significantly less likely to have anxiety than those in the Wuhan epicenter (aOR = 0.9; 95% CI: 0.8-1.0), but depression did not differ. Depression was associated with female students (aOR = 2.0; 95% CI: 1.2-3.3), negative thoughts or actions (aOR = 1.7; 95% CI: 1.5-1.9), and anxiety disorder (aOR = 5.8; 95% CI: 3.4-9.9). Path analysis validated these same predictors. CONCLUSIONS: Despite medical students' knowledge of disease control and prevention, their lives were greatly affected by social distancing, especially in the Wuhan epicenter. Even well-informed students needed psychological support during these extraordinarily stressful times.

The clinical course and its correlated immune status in COVID-19 pneumonia.

OBJECTIVES: To explore the clinical course and its dynamic features of immune status in COVID-19 patients and find predictors correlated with severity and prognosis of COVID-19. METHODS: The electronic medical records of 204 patients with COVID-19 pneumonia confirmed by nucleic acid testing were retrospectively collected and analyzed. RESULTS: All patients were divided into severe (69) and non-severe group (135). Lymphocyte subsets count, including CD3+ T cell, CD4+ T cell, CD8+ T cell, B cell (CD19+) and NK cell (CD16+ 56+), were significantly lower in severe group (P＜0.001). The dynamic levels of T lymphocyte in severe group were significantly lower from disease onset, but in the improved subgroup the value of T lymphocyte began to increase after about 15-day treatment and finally returned to the normal level. The cut-off value of the counts of CD3+ (576), CD4+ (391) and CD8+ (214) T cell were calculated and indicated significantly high sensitivity and specificity for severity of COVID-19. CONCLUSION: Our results shown that the decrease of CD3+, CD4+ and CD8+ T lymphocyte correlated with the course of patients with COVID-19 pneumonia, especially in severe cases. The level of T lymphocyte could be used as an indicator for prediction of severity and prognosis of patients with COVID-19 pneumonia. The application of glucocorticoid should be cautious in severe cases.

CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China.

PURPOSE: Aimed to characterize the CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia. METHODS: Asymptomatic cases with COVID-19 pneumonia confirmed by SARS-COV-2 nucleic acid testing in Renmin Hospital of Wuhan University were retrospectively enrolled. The characteristics of CT imaging and clinical feature were collected and analyzed. RESULTS: 58 asymptomatic cases with COVID-19 pneumonia admitted to our hospital between Jan 1, 2020 and Feb 23, 2020 were enrolled. All patients had history of exposure to SARS-CoV-2. On admission, patients had no symptoms and laboratory findings were normal. The predominant feature of CT findings in this cohort was ground glass opacity (GGO) (55, 94.8%) with peripheral (44, 75.9%) distribution, unilateral location (34, 58.6%) and mostly involving one or two lobes (38, 65.5%), often accompanied by characteristic signs. After short-term follow-up, 16 patients (27.6%) presented symptoms with lower lymphocyte count and higher CRP, mainly including fever, cough and fatigue. The evolution of lesions on CT imaging were observed in 10 patients (17.2%). The average days of hospitalization was19.80±10.82 days, and was significantly longer in progression patients (28.60±7.55 day). CONCLUSION: CT imaging of asymptomatic cases with COVID-19 pneumonia has definite characteristics. Since asymptomatic infections as "covert transmitter", and some patients can progress rapidly in the short term. It is essential to pay attention to the surveillance of asymptomatic patients with COVID-19. CT scan has great value in screening and detecting patients with COVID-19 pneumonia, especially in the highly suspicious, asymptomatic cases with negative nucleic acid testing.