Detection of COVID-19 using multimodal data from a wearable device: results from the first TemPredict Study.

Early detection of diseases such as COVID-19 could be a critical tool in reducing disease transmission by helping individuals recognize when they should self-isolate, seek testing, and obtain early medical intervention. Consumer wearable devices that continuously measure physiological metrics hold promise as tools for early illness detection. We gathered daily questionnaire data and physiological data using a consumer wearable (Oura Ring) from 63,153 participants, of whom 704 self-reported possible COVID-19 disease. We selected 73 of these 704 participants with reliable confirmation of COVID-19 by PCR testing and high-quality physiological data for algorithm training to identify onset of COVID-19 using machine learning classification. The algorithm identified COVID-19 an average of 2.75 days before participants sought diagnostic testing with a sensitivity of 82% and specificity of 63%. The receiving operating characteristic (ROC) area under the curve (AUC) was 0.819 (95% CI [0.809, 0.830]). Including continuous temperature yielded an AUC 4.9% higher than without this feature. For further validation, we obtained SARS CoV-2 antibody in a subset of participants and identified 10 additional participants who self-reported COVID-19 disease with antibody confirmation. The algorithm had an overall ROC AUC of 0.819 (95% CI [0.809, 0.830]), with a sensitivity of 90% and specificity of 80% in these additional participants. Finally, we observed substantial variation in accuracy based on age and biological sex. Findings highlight the importance of including temperature assessment, using continuous physiological features for alignment, and including diverse populations in algorithm development to optimize accuracy in COVID-19 detection from wearables.

Genomic surveillance to combat COVID-19: challenges and opportunities.

Although the development and increasingly widespread availability of effective and safe vaccines provides the greatest hope for the future recovery from the increasingly devastating COVID-19 pandemic, there are other preventive efforts that offer an immediate route to decreasing morbidity and mortality. Genomic surveillance is emerging as a vital necessity to achieve effective mitigation and containment. Since SARS-CoV-2 variants have already been detected, it is crucial to obtain reliable evidence about whether they are more contagious, virulent, or more resistant to the available COVID-19 vaccines well before they spread throughout the world. Genomic surveillance leverages applications of next-generation sequencing, creates the availability of whole genome data, and advances phylogenetic methods. These methods offer novel means to detect variants that are phenotypically or antigenically different. Genomic surveillance will facilitate greater early anticipation as well as initiation of effective strategies to mitigate and contain outbreaks of SARS-CoV-2 variants and other novel viruses.

A simplified SARS-CoV-2 detection protocol for research laboratories.

Widespread testing is required to limit the current public health crisis caused by the COVID-19 pandemic. Multiple tests protocols have been authorized by the food and drugs administration (FDA) under an emergency use authorization (EUA). The majority of these protocols are based on the gold-standard RT-qPCR test pioneered by the U.S. Centers for Disease Control and Prevention (CDC). However, there is still a widespread lack of testing in the US and many of the clinical diagnostics protocols require extensive human labor and materials that could face supply shortages and present biosafety concerns. Given the need to develop alternative reagents and approaches to provide nucleic-acid testing in the face of heightened demand and potential shortages, we have developed a simplified SARS-CoV-2 testing protocol adapted for its use in research laboratories with minimal molecular biology equipment and expertise. The protocol utilizes TRIzol to purify the viral RNA from different types of clinical specimens, requires minimal BSL-1 precautions and, given its high sensitivity, can be easily adapted to pooling samples strategies.