Quantifying meaningful usage of a SARS-CoV-2 exposure notification app on the campus of the University of Arizona
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Abstract
Objective
To measure meaningful, local exposure notification usage without in-app analytics.
Methods
We surveyed app usage via case investigation interviews at the University of Arizona, with a focus on the period from September 9 to November 28, 2020, after automating the issuance of secure codes to verify positive test results. As independent validation, we compared the number of verification codes issued to the number of local cases.
Results
Forty six percent (286/628) of infected persons interviewed by university case investigators reported having the app, and 55% (157/286) of these app users shared their positive SARS-CoV-2 test result in the app prior to the case investigation interview, comprising 25% (157/628) of those interviewed. This is corroborated by a 33% (565/1,713) ratio of code issuance (inflated by some unclaimed codes) to cases. Combining the 25% probability that those who test positive rapidly share their test result with a 46% probability that a person they infected can receive exposure notifications, an estimated 11.4% of transmission pairs exhibit meaningful app usage. High usage was achieved without the use of “push” notifications, in the context of a marketing campaign that leveraged social influencers.
Conclusions
Usage can be assessed, without in-app analytics, within a defined local community such as a college campus rather than an entire jurisdiction. With marketing, high uptake in dense social networks like universities makes exposure notification an impactful complement to traditional contact tracing. Integrating verification code delivery into patient results portals was successful in making the exposure notification process rapid.
3 question summary box
What is the current understanding of this subject?
The extent to which exposure notification technology reduces SARS-CoV-2 transmission depends on usage among infected persons.
What does this report add to the literature?
A novel metric estimates meaningful usage, and demonstrates potential transmission reduction on a college campus. Clear benefit was seen from simplifying verification of positive test results with automation.
What are the implications for public health practice?
Defined communities can benefit from local deployment and marketing even in the absence of statewide deployment. Lifting current restrictions on deployment would allow more entities such as campuses to copy the model shown here to be successful.
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SciScore for 10.1101/2021.02.02.21251022: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2021.02.02.21251022: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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