Ideas for how informaticians can get involved with COVID-19 research

Jason H. Moore; Ian Barnett; Mary Regina Boland; Yong Chen; George Demiris; Graciela Gonzalez-Hernandez; Daniel S. Herman; Blanca E. Himes; Rebecca A. Hubbard; Dokyoon Kim; Jeffrey S. Morris; Danielle L. Mowery; Marylyn D. Ritchie; Li Shen; Ryan Urbanowicz; John H. Holmes

doi:10.1186/s13040-020-00213-y

BioData Mining (May 2020)

Ideas for how informaticians can get involved with COVID-19 research

Jason H. Moore,
Ian Barnett,
Mary Regina Boland,
Yong Chen,
George Demiris,
Graciela Gonzalez-Hernandez,
Daniel S. Herman,
Blanca E. Himes,
Rebecca A. Hubbard,
Dokyoon Kim,
Jeffrey S. Morris,
Danielle L. Mowery,
Marylyn D. Ritchie,
Li Shen,
Ryan Urbanowicz,
John H. Holmes

Affiliations

Jason H. Moore: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Ian Barnett: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Mary Regina Boland: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Yong Chen: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
George Demiris: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Graciela Gonzalez-Hernandez: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Daniel S. Herman: Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania
Blanca E. Himes: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Rebecca A. Hubbard: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Dokyoon Kim: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Jeffrey S. Morris: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Danielle L. Mowery: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Marylyn D. Ritchie: Department of Genetics, Perelman School of Medicine, University of Pennsylvania
Li Shen: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
Ryan Urbanowicz: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania
John H. Holmes: Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania

DOI: https://doi.org/10.1186/s13040-020-00213-y
Journal volume & issue: Vol. 13, no. 1
pp. 1 – 16

Abstract

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Abstract The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare for COVID-19 patients. Critical to this effort is the participation of informaticians who typically work on other basic science or clinical problems. The goal of this editorial is to highlight some examples of COVID-19 research areas that could benefit from informatics expertise. Each research idea summarizes the COVID-19 application area, followed by an informatics methodology, approach, or technology that could make a contribution. It is our hope that this piece will motivate and make it easy for some informaticians to adopt COVID-19 research projects.

Published in BioData Mining

ISSN: 1756-0381 (Online)
Publisher: BMC
Country of publisher: United Kingdom
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Science: Mathematics: Analysis
Website: https://biodatamining.biomedcentral.com/

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