Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic

Hamada S. Badr, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Benjamin F. Zaitchik, Department of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA. zaitchik@jhu.edu.
Gaige H. Kerr, Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Nhat-Lan H. Nguyen, College of Arts and Sciences, University of Virginia, Charlottesville, VA, 22903, USA.
Yen-Ting Chen, Division of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.
Patrick Hinson, College of Arts and Sciences, University of Virginia, Charlottesville, VA, 22903, USA.
Josh M. Colston, Division of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.
Margaret N. Kosek, Division of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.
Ensheng Dong, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Hongru Du, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Maximilian Marshall, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Kristen Nixon, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Arash Mohegh, Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Daniel L. Goldberg, Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Susan C. Anenberg, Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Lauren M. Gardner, Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.

Document Type

Journal Article

Publication Date

6-7-2023

Journal

Scientific data

Volume

10

Issue

1

DOI

10.1038/s41597-023-02276-y

Abstract

An impressive number of COVID-19 data catalogs exist. However, none are fully optimized for data science applications. Inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 epidemiological data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, vaccine data, and key demographic characteristics.

Department

Environmental and Occupational Health

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