Digital technologies in the public-health response to COVID-19

Jobie Budd, Benjamin S. Miller, Erin M. Manning, Vasileios Lampos, Mengdie Zhuang, Michael Edelstein, Geraint Rees, Vincent C. Emery, Molly M. Stevens, Neil Keegan, Michael J. Short, Deenan Pillay, Ed Manley, Ingemar J. Cox, David Heymann, Anne M. Johnson, Rachel A. McKendry

Research output: Contribution to journalReview articlepeer-review

521 Scopus citations

Abstract

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. These rapid responses leverage billions of mobile phones, large online datasets, connected devices, relatively low-cost computing resources and advances in machine learning and natural language processing. This Review aims to capture the breadth of digital innovations for the public-health response to COVID-19 worldwide and their limitations, and barriers to their implementation, including legal, ethical and privacy barriers, as well as organizational and workforce barriers. The future of public health is likely to become increasingly digital, and we review the need for the alignment of international strategies for the regulation, evaluation and use of digital technologies to strengthen pandemic management, and future preparedness for COVID-19 and other infectious diseases.

Original languageEnglish
Pages (from-to)1183-1192
Number of pages10
JournalNature Medicine
Volume26
Issue number8
DOIs
StatePublished - 1 Aug 2020
Externally publishedYes

Bibliographical note

Funding Information:
A.M.J., I.J.C., V.C.E., B.S.M., E.M.M., D.P., M.M.S., N.K. and R.A.M. received funding from the EPSRC for i-sense IRC in Agile Early Warning Sensing Systems for Infectious Diseases and AMR (EP/R00529X/1), and collaborate with Google, Microsoft and Telefonica, as well as diagnostic companies. N.K., R.A.M. and M.M.S. received funding from IRC Next Steps Plus: Ultra-Sensitive Enhanced NanoSensing of Anti-Microbial Resistance (u-sense, EP/R018391/1). A.M.J. received funding from NIHR. G.R. undertakes paid consultancy work for Google Health, and undertakes research on predictive analytics in brain imaging funded by the Wellcome Trust. M.M.S. is a consultant for 30T/Edixomed, Simmons and Simmons and Origin Sciences, and receives research grant funding from CRUK, The Wellcome Trust, EPSRC/MRC/UKRI, H2020 and ERC, as well as other grants.

Publisher Copyright:
© 2020, Springer Nature America, Inc.

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