Analysis of Cognition, Protection, Psychological, and Job-search Intentions Among Medical and Nonmedical College Students During COVID-19 Epidemic.

Context: Since December 2019, medical practitioners discovered a novel coronavirus causing an acute respiratory-tract infection in some hospitals in Wuhan, Hubei Province. COVID-19 has spread globally, making it an epidemic worldwide at present. Understanding the mental-health responses of college students to COVID-19 can help a school staff to better guide students seeking education. Objective: The study aimed to explore the differences between nonmedical and medical college students during the COVID-19 epidemic in their cognitive interest about the disease, preventive behaviors, psychological effects, and job-search intentions, hoping to provide more targeted measures for virus-coping education for college students. Design: The research team conducted a cross-sectional study, using an anonymous online questionnaire. Setting: The study took place at Shanghai, China. Participants: Participants were 1648 college students studying different specialties in various provinces of China, 485 nonmedical students and 1163 medical students. Outcome Measures: The survey's questions covered the respondents': (1) general demographic characteristics, (2) cognitive interest and knowledge about COVID-19 and its infectiousness as well as efforts at active learning about infectious diseases and viruses, (3) awareness of precautionary behaviors against COVID-19, (4) effects on mental health, and (5) effects on job-search intentions. The research team used descriptive statistics and Chi-square tests to analyze the survey data. Results: Among nonmedical students: (1) 297 participants (61.2%) were interested in learning about COVID-19, (2) 321 participants (66.2%) took the initiative to learn about the virus, (3) 301 participants (62.1%) took the initiative to learn about infectious disease, and (4) 151 participants (31.1%) watched medical-themed movies or TV series about COVID-19. Among medical students, the corresponding proportions were 772 participants (66.4%), 855 participants (73.5%), 791 participants (68.1%), and 791 participants (68.1%), respectively. Among nonmedical students, 223 participants (46.0%) had N95 masks available, 429 participants (88.5%) had disinfectant supplies available, 271 participants (55.9%) wore goggles in public places, 75 participants (15.5%) chose public transportation, and 77 participants (15.9%) were exposed to public places in the week prior to the survey. Among medical students, the corresponding proportions were 470 participants (40.4%), 935 participants (80.4%), 575 participants (49.4%), 243 participants (20.9%), and 297 participants (25.5%), respectively. Furthermore, COVID-19 had a stronger effect on medical students' psychology and job-search ambitions. Conclusions: The news about COVID-19 piqued the interest of medical students. Nonmedical students had stronger protective behavior than medical students. The COVID-19 outbreak had a significant influence on medical students' lives, studies, and moods. In addition, COVID-19 had a greater impact on the job-search intentions of medical students.

Comparative Analysis of Early-Stage Clinical Features Between COVID-19 and Influenza A H1N1 Virus Pneumonia.

Introduction: Influenza virus pneumonia and COVID-19 are two different types of respiratory viral pneumonia but with very similar clinical manifestations. The aim of the present study was to help clinicians gain a better understanding about differences between Influenza virus pneumonia and COVID-19 by comparative analysis of the early-stage clinical features. Methods: Clinical data of patients with confirmed diagnosis of COVID-19 and influenza A pneumonia identified in our hospital were collected and analyzed retrospectively to identify the clinical features that could differentiate between the two types of viral pneumonia. Results: The two types of viral pneumonia mainly affected adults, especially people over 50 years, with no gender difference between them. Fever, cough, sputum and muscle soreness were the most common symptoms of COVID-19. Some patients with COVID-19 may also exhibit digestive tract symptoms. Elevation of C-reactive protein (CRP) was a more common phenomenon in patients with COVID-19 than that in patients with influenza A H1N1 virus pneumonia. In addition, eosinophil count was decreased and the monocyte percentage was increased in COVID-19 patients. The grid-form shadow was a typical presentation of COVID-19 on the lung CT image, and the disease usually progressed quickly within a week. Conclusion: Influenza pneumonia and COVID-19 are two different types of respiratory viral pneumonia with very similar clinical manifestations. The percentage of monocytes is increased and the eosinophil count is decreased in COVID-19. Glass-ground density exudation shadow located peripherally is the typical sign of COVID-19 on the lung CT image, and the shadow often with grid-form sign. These features may not be typically observed in patients with influenza pneumonia. Chest CT scan combined with nucleic acid detection is an effective and accurate method for diagnosing COVID-19. Blood routine test has a limited diagnostic value in differentiating the two forms of pneumonia.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study.

Background: The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19. Methods: We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19. Findings: We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 109 per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 109 per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19. Interpretation: The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease. Funding: National Natural Science Foundation of China.