Experience of distance education for project-based learning in data science.

Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information: The online version contains supplementary material available at 10.1007/s42081-022-00154-2.

Experience of distance education for project-based learning in data science

Data science plays an important role in many fields. Project-based learning is an effective teaching approach because students can learn data science practices based on real-world problems and real-world data. Because of a pandemic of COVID-19, we provided project-based learning as distance education (synchronic distance education). In this study, we explain how we developed and conducted it and provide survey results from students. The survey showed about 30% of the students found it difficult to communicate with each other and with teachers. However, it suggested that they could communicate to some extent even by remote group work. We found that, in remote communication, it is important to see the faces of all the students (and teachers) on the Zoom screen when they discuss using screen sharing. There remain some challenges such as timing to start talking and casual questions to teachers. Although some issues should be improved, distance education for project-based learning in data science can be implemented effectively. Supplementary Information The online version contains supplementary material available at 10.1007/s42081-022-00154-2.

Definitions and elements of endpoints in phase III randomized trials for the treatment of COVID-19: a cross-sectional analysis of trials registered in ClinicalTrials.gov.

BACKGROUND: There are several challenges in designing clinical trials for the treatment of novel infectious diseases, such as COVID-19. In particular, the definition of endpoints related to the severity, time frame, and clinical course remains unclear. Therefore, we conducted a cross-sectional analysis of phase III randomized trials for COVID-19 registered at ClinicalTrials.gov . METHODS: We collected the data from ClinicalTrials.gov on March 31, 2021, by specifying the following search conditions under Advanced Search: Condition or disease: (COVID-19) OR (SARS-CoV-2); Study type: Interventional Studies; Study Results: All Studies; Recruitment: Not yet recruiting, Recruiting, Enrolling by invitation, Active, Not recruiting, Suspended, Completed; Sex: All; and Phase: Phase 3. From the downloaded search results, we selected trials that met the following criteria: Primary Purpose: Treatment; Allocation: Randomized. We manually transcribed information not included in the downloaded file, such as Primary Outcome Measures, Secondary Outcome Measures, Time Frame, and Inclusion Criteria. In the analysis, we examined primary and secondary endpoints in trials with severe and non-severe patients, including the types of endpoints, time frame, clinical course, and sample size. RESULTS: A total of 406 trials were included in the analysis. The median numbers of endpoints in trials with severe and non-severe patients were 9 and 7, respectively. Approximately 25% of the trials used multiple primary endpoints. Regardless of the type of endpoint, the time frames were longer in the trials with severe patients than in the trials with non-severe patients. In the evaluation of the clinical course, worsening was often considered in binary endpoints, and improvement was considered in time-to-event endpoints. The sample size was the largest in clinical trials using binary endpoints. CONCLUSIONS: Endpoints can differ with respect to severity, and the clinical course and time frame are important for defining endpoints. This study provides information that can facilitate the achievement of a consensus for the endpoints in evaluating COVID-19 treatments.

Mass Screening of Asymptomatic Persons for Severe Acute Respiratory Syndrome Coronavirus 2 Using Saliva.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly evolved to become a global pandemic, largely owing to the transmission of its causative virus through asymptomatic carriers. Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of polymerase chain reaction testing. In addition, although self-collected saliva samples have significant logistical advantages in mass screening, their utility as an alternative specimen in asymptomatic persons is yet to be determined. METHODS: We conducted a mass screening study to compare the utility of nucleic acid amplification, such as reverse-transcription polymerase chain reaction testing, using nasopharyngeal swab (NPS) and saliva samples from each individual in 2 cohorts of asymptomatic persons: the contact-tracing cohort and the airport quarantine cohort. RESULTS: In this mass screening study including 1924 individuals, the sensitivities of nucleic acid amplification testing with NPS and saliva specimens were 86% (90% credible interval, 77%-93%) and 92% (83%-97%), respectively, with specificities >99.9%. The true concordance probability between the NPS and saliva tests was estimated at 0.998 (90% credible interval, .996-.999) given the recent airport prevalence of 0.3%. In individuals testing positive, viral load was highly correlated between NPS and saliva specimens. CONCLUSION: Both NPS and saliva specimens had high sensitivity and specificity. Self-collected saliva specimens are valuable for detecting SARS-CoV-2 in mass screening of asymptomatic persons.