Containing the COVID-19 pandemic requires rapidly identifying infected individuals.
Subtle changes in physiological parameters (such as heart rate, respiratory rate,
and skin temperature), discernible by wearable devices, could act as early digital
biomarkers of infections. Our primary objective was to assess the performance of statistical
and algorithmic models using data from wearable devices to detect deviations compatible
with a SARS-CoV-2 infection. We searched MEDLINE, Embase, Web of Science, the Cochrane
Central Register of Controlled Trials (known as CENTRAL), International Clinical Trials
Registry Platform, and ClinicalTrials.gov on July 27, 2021 for publications, preprints,
and study protocols describing the use of wearable devices to identify a SARS-CoV-2
infection.
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This phylogenetic tree represents the clade distribution of global SARS-CoV-2 viral genomes since the beginning of the pandemic. In the center is the reference Wuhan-1 strain, with outside samples now separated by nucleotide divergence. The last few months have led to an explosion of new variants with further mutations in the viral spike resulting in further antibody evasion, and also carrying changes in many other viral proteins. Some recently sequenced viral genomes from samples collected in Southeast Asia (not shown in this figure) display over a hundred nucleotides changes when compared to Wuhan-1. The graph was generated with nextstrain.org
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Heroes vs. Villains: How Gamification Helped in the Fight Against COVID-19
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Researchers in Luxembourg showed for the first time that vocal recordings of COVID-19 affected people could be used to monitor related symptoms of the disease.
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