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Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus
Health authorities encouraged the use of digital contact tracing mobile applications (apps) during the COVID-19 pandemic, but the level of adoption was low because apps offered few direct benefits to counterbalance risks to personal privacy. Adoption of such apps could improve if they provided benef...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678787/ https://www.ncbi.nlm.nih.gov/pubmed/35861290 http://dx.doi.org/10.1177/00333549221112532 |
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author | Loh, Po-Shen Bershteyn, Anna Yee, Shannon K. |
author_facet | Loh, Po-Shen Bershteyn, Anna Yee, Shannon K. |
author_sort | Loh, Po-Shen |
collection | PubMed |
description | Health authorities encouraged the use of digital contact tracing mobile applications (apps) during the COVID-19 pandemic, but the level of adoption was low because apps offered few direct benefits to counterbalance risks to personal privacy. Adoption of such apps could improve if they provided benefits to users. NOVID (COVID-19 Radar), a smartphone app, provided users with personalized data on social proximity of COVID-19 cases and exposed contacts. We analyzed uptake of NOVID at the Georgia Institute of Technology (Georgia Tech) during the 2020-2021 academic year. Data included anonymous NOVID users who self-identified with Georgia Tech and their first- and second-degree network contacts. NOVID achieved 13%-30% adoption at Georgia Tech. Because of technical challenges, adoption waned after an initial peak. The largest increases in adoption (from 41 to 3704) followed administrative promotion of NOVID. Adoption increased modestly (from 2512 to 2661) after faculty- and student-led promotion, such as distribution of door hangers and a public seminar. Two-thirds of on-campus NOVID users were connected to a large network of other users, enabling them to receive data on social proximity of COVID-19 cases and exposed contacts. Network cohesion was observed to emerge rapidly when adoption rates passed just 10%, consistent with estimates from network theory. The key lesson learned in this case study is that top-down administrative promotion outperforms bottom-up grassroots promotion. Relatively high levels of adoption and network cohesion, despite technical challenges during the Georgia Tech pilot of NOVID, illustrate the promise of digital contact tracing when apps provide privacy and inherently beneficial personalized data to their users, especially in regions where Google Apple Exposure Notification is not available. |
format | Online Article Text |
id | pubmed-9678787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-96787872022-11-22 Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus Loh, Po-Shen Bershteyn, Anna Yee, Shannon K. Public Health Rep Novel Digital Tools Health authorities encouraged the use of digital contact tracing mobile applications (apps) during the COVID-19 pandemic, but the level of adoption was low because apps offered few direct benefits to counterbalance risks to personal privacy. Adoption of such apps could improve if they provided benefits to users. NOVID (COVID-19 Radar), a smartphone app, provided users with personalized data on social proximity of COVID-19 cases and exposed contacts. We analyzed uptake of NOVID at the Georgia Institute of Technology (Georgia Tech) during the 2020-2021 academic year. Data included anonymous NOVID users who self-identified with Georgia Tech and their first- and second-degree network contacts. NOVID achieved 13%-30% adoption at Georgia Tech. Because of technical challenges, adoption waned after an initial peak. The largest increases in adoption (from 41 to 3704) followed administrative promotion of NOVID. Adoption increased modestly (from 2512 to 2661) after faculty- and student-led promotion, such as distribution of door hangers and a public seminar. Two-thirds of on-campus NOVID users were connected to a large network of other users, enabling them to receive data on social proximity of COVID-19 cases and exposed contacts. Network cohesion was observed to emerge rapidly when adoption rates passed just 10%, consistent with estimates from network theory. The key lesson learned in this case study is that top-down administrative promotion outperforms bottom-up grassroots promotion. Relatively high levels of adoption and network cohesion, despite technical challenges during the Georgia Tech pilot of NOVID, illustrate the promise of digital contact tracing when apps provide privacy and inherently beneficial personalized data to their users, especially in regions where Google Apple Exposure Notification is not available. SAGE Publications 2022-07-21 /pmc/articles/PMC9678787/ /pubmed/35861290 http://dx.doi.org/10.1177/00333549221112532 Text en © 2022, Association of Schools and Programs of Public Health |
spellingShingle | Novel Digital Tools Loh, Po-Shen Bershteyn, Anna Yee, Shannon K. Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title | Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title_full | Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title_fullStr | Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title_full_unstemmed | Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title_short | Lessons Learned in Piloting a Digital Personalized COVID-19 “Radar” on a University Campus |
title_sort | lessons learned in piloting a digital personalized covid-19 “radar” on a university campus |
topic | Novel Digital Tools |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9678787/ https://www.ncbi.nlm.nih.gov/pubmed/35861290 http://dx.doi.org/10.1177/00333549221112532 |
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