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Optimizing COVID-19 testing resources use with wearable sensors.

Giorgio Quer1, Arinbjörn Kolbeinsson2, Jennifer M Radin1

  • 1Scripps Research Translational Institute, La Jolla, California, United States of America.

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Wearable technology can significantly reduce infectious days for viral illnesses like COVID-19. This approach, combined with testing strategies, lowers the number of undetected infectious days and potentially reduces overall testing costs.

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Area of Science:

  • Epidemiology
  • Public Health
  • Wearable Technology

Background:

  • Timely identification of pre-symptomatic and asymptomatic infectious cases is crucial for controlling viral spread.
  • Current routine testing programs are effective but costly and burdensome.
  • Wearable technology offers a passive monitoring solution to identify high-risk individuals for testing.

Purpose of the Study:

  • To model and compare the effectiveness of routine testing versus wearable-informed testing strategies.
  • To estimate the number of tests required and the duration of infectious, undetected periods.
  • To assess the potential of wearable technology in reducing viral transmission.

Main Methods:

  • Development of a parametric Markov chain model.
  • Simulation of routine testing and wearable-informed testing strategies.
  • Estimation of infectious and undetected days under different testing scenarios.

Main Results:

  • Routine testing resulted in 4.1 infectious and undetected days (with 2 tests/month).
  • Wearable testing reduced infectious days by 46% (with symptoms) and 27% (without symptoms).
  • Wearable technology can decrease required tests and costs while maintaining similar infectious day reduction.

Conclusions:

  • Wearable technology integrated into testing strategies significantly reduces infectious and transmissible periods.
  • This approach offers a cost-effective and less burdensome alternative to frequent routine testing.
  • The model is adaptable for various viral illnesses by adjusting parameters.