Digital technology and COVID-19
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Digital technologies have been deployed in the COVID-19 pandemic to strengthen each of the four public-health measures: surveillance, rapid case identification, interruption of community transmission and public communication.
“Similarly, digital technologies also have been deployed in the COVID-19 pandemic 13,14 (Table 1) to strengthen each of the four public-health measures noted above.”
From Digital technologies in the public-health response to COVID-19 (2020) · cites this paper as [13]
The paper’s “Monitoring, surveillance, detection and prevention of COVID-19” section describes digital tracking, screening and public communication, supporting three of the measures in substance. Its Table 1 also lists detection and prevention applications, but the copy does not establish that digital technologies were deployed to interrupt community transmission specifically; it describes quarantine and contact tracing as traditional measures. (LLM, conf=0.82)
Experimental — accuracy not yet measuredDigital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing, evaluation of interventions using mobility data, and communication with the public.
“Digital technologies are being harnessed to support the public-health response to COVID-19 worldwide, including population surveillance, case identification, contact tracing and evaluation of interventions on the basis of mobility data and communication with the public.”
From Digital technologies in the public-health response to COVID-19 (2020) · cites this paper as [13]
The ‘Monitoring, surveillance, detection and prevention of COVID-19’ section describes digital case tracking, screening and public communication, and discusses location-based data used to forecast disease activity. The Abstract mentions contact tracing as a traditional, labor-intensive measure, not a digital application; the paper does not describe evaluating interventions using mobility data. Page numbers are not available in our copy. (LLM, conf=0.88)
Experimental — accuracy not yet measuredBiometric measurements such as blood pressure and heartbeat may be transmitted to the cloud for analysis without exposing healthcare workers to the infection.
“Their biometric measurements, such as blood pressure and heartbeat, may be transmitted to the cloud for analysis without exposing healthcare workers to the infection (Ting et al., 2020).”
From IoMT amid COVID-19 pandemic: Application, architecture, technology, and security (2021) · cites this paper as Ting et al., 2020
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Digital technologies in the public-health response to COVID-19
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- Authors
- Ting, D. S. W., Carin, L., Dzau, V., & Wong, T. Y.
- Affiliations
- SingHealth (SG)
- Duke University (US)
- National Academy of Medicine (US)
- Corresponding author
- Ting, Daniel Shu Wei
- Venue
- Nature Medicine
- Published
- 2020-03-27
- Volume
- 26
- Issue
- 4
- Pages
- 459-461
- ISSN
- 1078-8956 (ISSN-L)
- 1546-170X
- PMC
- PMC7100489
- OpenAlex
- W3013547516
- Cited by
- 1,413
- References
- 8
- Citations by year
- 2026: 27 · 2025: 60 · 2024: 108 · 2023: 196 · 2022: 300 · 2021: 454 · 2020: 265 · 2019: 2
- FWCI
- 286.05
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature Medicine (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Physical Sciences › Computer Science › Information Systems › Healthcare during COVID-19 Pandemic
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Keywords
- COVID-19 pandemic, digital technologies, digital health tools, pandemic response, outbreak mitigation
- MeSH terms
- Betacoronavirus, Big Data, Internet of Things, Blockchain, COVID-19, SARS-CoV-2, COVID-19 Testing, Algorithms, Artificial Intelligence, China, Communication, Forecasting, Humans, Mass Screening, Pneumonia, Viral, Public Health, Triage, User-Computer Interface, Models, Statistical, Telemedicine, Coronavirus Infections, Clinical Laboratory Techniques, Pandemics, Social Media, Epidemiological Monitoring
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