COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread
Open accessAbstract
Confirmed cases of coronavirus disease 2019 (COVID-19) exceed those of severe acute respiratory syndrome (SARS), and, at time of publication, now stand at over 73,435 confirmed cases and over 2000 deaths globally, nearly all in China. By comparison, SARS killed 774 people in 2003, again mostly in China, the epicentre of both outbreaks. Both COVID-19 and SARS spread across continents, infect animals and humans, and use similar mechanics to enter and infect the cell. On the frontline, tactical response to COVID-19 is similar to that of SARS but one major difference exists: in the 17 years since SARS, a powerful new tool has emerged that could potentially be instrumental in keeping this virus within reasonable limits—namely, artificial intelligence (AI).
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Digital 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 [14]
In “COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread” (page not provided), the paper describes digital outbreak tracking, AI-assisted case identification, contact-tracing systems, and travel data used to predict where cases may appear. It does not describe using mobility data to evaluate interventions or digital technologies to communicate with the public, so those parts of the attributed claim are unsupported. (LLM, conf=0.86)
Experimental — accuracy not yet measuredDigital 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 [14]
In the section “COVID-19 and artificial intelligence: protecting health-care workers and curbing the spread” (page unavailable), McCall describes digital outbreak tracking, AI-assisted rapid identification of possible COVID-19 cases, and models that might inform border checks. The paper does not describe digital technology deployed for public communication, and it presents some transmission-control uses as potential rather than established. It therefore does not support the claim that deployment strengthened each of the four measures. (LLM, conf=0.86)
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- Authors
- McCall, B.
- Corresponding author
- McCall, Becky
- ORCID
- McCall, Becky
- Venue
- The Lancet Digital Health
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 2
- Issue
- 4
- Pages
- e166-e167
- ISSN
- 2589-7500 (ISSN-L)
- PMC
- PMC7129544
- OpenAlex
- W3008401431
- Cited by
- 396
- References
- 0
- Citations by year
- 2026: 5 · 2025: 16 · 2024: 22 · 2023: 48 · 2022: 74 · 2021: 123 · 2020: 107
- FWCI
- 25.92
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The Lancet Digital Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Informationszentrum Lebenswissenschaften (ZB MED) (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Physical Sciences › Computer Science › Information Systems › Healthcare during COVID-19 Pandemic
- Keywords
- COVID-19 pandemic, artificial intelligence, healthcare workers, infection control, SARS, pandemic response, disease spread, zoonotic transmission, viral entry
- MeSH terms
- COVID-19, Artificial Intelligence, Humans, Infectious Disease Transmission, Patient-to-Professional
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