Interdisciplinary Online Hackathons as an Approach to Combat the COVID-19 Pandemic: Case Study

This case study describes the conduction of a remote online health hackathon centered on challenges posed by the COVID-19 pandemic. 48 participants and 52 mentors based in 8 different countries participated and developed 14 projects. P

Detection of SARS-CoV-2 in saliva and characterization of oral symptoms in COVID-19 patients

Researchers analysed ACE2 expression in the salivary glands of SARS-CoV-2 patients. They also carried out a questionnaire survey on oral-related symptoms of COVID-19 patients.

Magnitude of asymptomatic COVID-19 cases throughout the course of infection: A systematic review and meta-analysis

Asymptomatic SARS-CoV-2 infections are responsible for the potentially significant transmission of COVID-19. There is a need for more robust and well-designed studies to have a relevant public health intervention.

Clinical features and medical care factors associated with mortality in French nursing homes during the COVID-19 outbreak

Two nursing homes were hospital-dependent, had connections with infection prevention and control departments, and had permanent physicians.

Modeling Predictive Age-Dependent and Age-Independent Symptoms and Comorbidities of Patients Seeking Treatment for COVID-19: Model Development and Validation Study

Predictors can be used to stratify patients based on how much medical attention they are expected to require. This could help health care workers devote valuable resources to prevent the escalation of the disease in vulnerable populations.

Researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19-related publications.

SARS-CoV-2 emerged in Wuhan, Hubei, China. In December 2019, coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome. All-cause death was the primary endpoint.

A Comprehensive Overview of the COVID-19 Literature: Machine Learning-Based Bibliometric Analysis

Researchers rapidly mobilized to study numerous aspects of the disease such as its evolution, clinical manifestations, effects, treatments, and vaccinations. This led to a rapid increase in the number of COVID-19-related publications.

Communicative Blame in Online Communication of the COVID-19 Pandemic: Computational Approach of Stigmatizing Cues and Negative Sentiment Gauged With Automated Analytic Techniques

The study aims to identify social stigma and negative sentiment toward blameworthy agents in social communities. Data sources comprised of ten news websites, eleven discussion forums, one social network, and two principal media sharing networks in Taiwan

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