Using serological data to understand unobserved SARS-CoV-2 risk in health-care settings.

Kucharski, Adam J; Nilles, Eric J

Kucharski, Adam J; Nilles, Eric J.

Kucharski AJ; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, WC1E 7HT, UK. Electronic address: adam.kucharski@lshtm.ac.uk.
Nilles EJ; Brigham and Women's Hospital, Harvard Medical School, Harvard Humanitarian Initiative, Boston, MA, USA.

Lancet Infect Dis ; 20(12): 1351-1352, 2020 12.

Article in English | MEDLINE | ID: covidwho-692214

Subject(s)

COVID-19; Coronavirus Infections; SARS-CoV-2; Coronavirus Infections/epidemiology; Delivery of Health Care; Health; Humans; Pandemics

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Coronavirus Infections / SARS-CoV-2 / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Lancet Infect Dis Journal subject: Communicable Diseases Year: 2020 Document Type: Article

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