A holistic approach for suppression of COVID-19 spread in workplaces and universities.

Sarah F Poole, Jessica Gronsbell, Dale Winter, Stefanie Nickels, Roie Levy, Bin Fu, Maximilien Burq, Sohrab Saeb, Matthew D Edwards, Michael K Behr, Vignesh Kumaresan, Alexander R Macalalad, Sneh Shah, Michelle Prevost, Nigel Snoad, Michael P Brenner, Lance J Myers, Paul Varghese, Robert M Califf, Vindell Washington, Vivian S Lee, Menachem Fromer
Author Information
  1. Sarah F Poole: Verily Life Sciences, South San Francisco, CA, United States of America. ORCID
  2. Jessica Gronsbell: Verily Life Sciences, South San Francisco, CA, United States of America.
  3. Dale Winter: Verily Life Sciences, South San Francisco, CA, United States of America.
  4. Stefanie Nickels: Verily Life Sciences, South San Francisco, CA, United States of America.
  5. Roie Levy: Verily Life Sciences, South San Francisco, CA, United States of America.
  6. Bin Fu: Verily Life Sciences, South San Francisco, CA, United States of America.
  7. Maximilien Burq: Verily Life Sciences, South San Francisco, CA, United States of America.
  8. Sohrab Saeb: Verily Life Sciences, South San Francisco, CA, United States of America.
  9. Matthew D Edwards: Verily Life Sciences, South San Francisco, CA, United States of America.
  10. Michael K Behr: Verily Life Sciences, South San Francisco, CA, United States of America.
  11. Vignesh Kumaresan: Verily Life Sciences, South San Francisco, CA, United States of America.
  12. Alexander R Macalalad: Verily Life Sciences, South San Francisco, CA, United States of America. ORCID
  13. Sneh Shah: Verily Life Sciences, South San Francisco, CA, United States of America.
  14. Michelle Prevost: Verily Life Sciences, South San Francisco, CA, United States of America.
  15. Nigel Snoad: Verily Life Sciences, South San Francisco, CA, United States of America. ORCID
  16. Michael P Brenner: Google Research, Mountain View, CA, United States of America.
  17. Lance J Myers: Verily Life Sciences, South San Francisco, CA, United States of America.
  18. Paul Varghese: Verily Life Sciences, South San Francisco, CA, United States of America.
  19. Robert M Califf: Verily Life Sciences, South San Francisco, CA, United States of America.
  20. Vindell Washington: Verily Life Sciences, South San Francisco, CA, United States of America.
  21. Vivian S Lee: Verily Life Sciences, South San Francisco, CA, United States of America.
  22. Menachem Fromer: Verily Life Sciences, South San Francisco, CA, United States of America. ORCID

Abstract

As society has moved past the initial phase of the COVID-19 crisis that relied on broad-spectrum shutdowns as a stopgap method, industries and institutions have faced the daunting question of how to return to a stabilized state of activities and more fully reopen the economy. A core problem is how to return people to their workplaces and educational institutions in a manner that is safe, ethical, grounded in science, and takes into account the unique factors and needs of each organization and community. In this paper, we introduce an epidemiological model (the "Community-Workplace" model) that accounts for SARS-CoV-2 transmission within the workplace, within the surrounding community, and between them. We use this multi-group deterministic compartmental model to consider various testing strategies that, together with symptom screening, exposure tracking, and nonpharmaceutical interventions (NPI) such as mask wearing and physical distancing, aim to reduce disease spread in the workplace. Our framework is designed to be adaptable to a variety of specific workplace environments to support planning efforts as reopenings continue. Using this model, we consider a number of case studies, including an office workplace, a factory floor, and a university campus. Analysis of these cases illustrates that continuous testing can help a workplace avoid an outbreak by reducing undetected infectiousness even in high-contact environments. We find that a university setting, where individuals spend more time on campus and have a higher contact load, requires more testing to remain safe, compared to a factory or office setting. Under the modeling assumptions, we find that maintaining a prevalence below 3% can be achieved in an office setting by testing its workforce every two weeks, whereas achieving this same goal for a university could require as much as fourfold more testing (i.e., testing the entire campus population twice a week). Our model also simulates the dynamics of reduced spread that result from the introduction of mitigation measures when test results reveal the early stages of a workplace outbreak. We use this to show that a vigilant university that has the ability to quickly react to outbreaks can be justified in implementing testing at the same rate as a lower-risk office workplace. Finally, we quantify the devastating impact that an outbreak in a small-town college could have on the surrounding community, which supports the notion that communities can be better protected by supporting their local places of business in preventing onsite spread of disease.

References

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MeSH Term

COVID-19
Contact Tracing
Disease Outbreaks
Humans
Physical Distancing
Universities
Workplace

Word Cloud

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