Schools, workplaces, sports and entertainment venues, places of worship, and other institutions across the U.S. are increasingly developing plans on how they can resume operations as shelter-in-place restrictions loosen in response to COVID-19.
The allure of returning to some sense of normalcy comes with the desire to do so quickly, and a variety of measures have taken hold to support a return to work. This includes tactics like checking the temperatures of people entering a building or implementing environmental controls — from social distancing and wearing masks to improved air circulation — none of which are sufficient on their own.
To avoid further illness and economic devastation, organizations must consider comprehensive return-to-work efforts that include testing as the cornerstone of their strategy. Testing is imperative for reducing risk as much as possible.
Testing with Collective Go™
As part of Collective Go™, we’ve built in the ability to support verifiable ongoing testing in order to facilitate the widespread levels of testing necessary for organizations of all types. This includes an established criteria for testing type and frequency, made adaptable in order to account for community factors as well as workplaces, using daily-updated data and models.
The most frequent question Collective Health continues to hear from companies is ‘who do we test, how often, and where do we find tests?’ Though testing capacity and quality has improved, there is still an acute need to help organizations simplify the process by identifying who needs testing, streamlining access to it, and managing the results of tests.
To learn more about testing with Collective Go™ , download the full summary.
- Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area. JAMA. 2020. Source
- Arons MM, Hatfield KM, Reddy SC, et al. Presymptomatic SARS-CoV-2 infections and transmission in a skilled nursing facility. N Engl J Med. 2020. Source
- Menni, C., Valdes, A.M., Freidin, M.B. et al. Real-time tracking of self-reported symptoms to predict potential COVID-19. Nat Med. 2020. Source
- UCSF/UC Berkeley BioHub COVID-19 Testing Project, Source
- Johns Hopkins Center for Health Security, Source