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Can collecting physiological data help identify patterns of COVID-19?

Using antibody testing and wearable sensor technology to predict the course of COVID-19 symptoms and recovery

Researchers at the University of California at San Francisco, with support from Federal and private funding, are analyzing associations between body temperature, heart rate, and other related metrics and the start of COVID-19 symptoms. Data are collected by TemPredict through a wearable smart ring, the Oura ring. In addition, antibody testing is being conducted to assess prior infection with COVID-19.

Researchers are using the data to build an algorithm to identify patterns of COVID-19 onset, progression, and recovery.

Westat coordinated the antibody testing component of TemPredict. To meet the need for a rapid start-up, the team quickly developed and implemented a plan to collect dried blood spot samples on 2 occasions from nearly 10,000 participants and shipped returned samples to a testing laboratory.

Westat performed the following:

  • Identified test kit components
  • Prepared instructions for self-collection
  • Arranged for kit assembly and mail-out with a vendor
  • Prepared a tracking system to coordinate all mailings, kit receipt, and second mailings
  • Received, processed, and stored returned samples
  • Shipped inventoried samples to a testing laboratory

While data processing for the study in ongoing, researchers are beginning to conduct analyses of the data to develop an algorithm that potentially assists in defining the course of COVID-19 from personal wearable device data.

The study results also will provide a proof of concept to support future work to advance the public health utility of distributed physiological information systems.

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