Evidence map›Paper›PMID 37286690›Full record

ArticleScientific data2023

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

Hamada S Badr, Benjamin F Zaitchik, Gaige H Kerr, Nhat-Lan H Nguyen, Yen-Ting Chen, Patrick Hinson, Josh M Colston, Margaret N Kosek, Ensheng Dong, Hongru Du and 6 more

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Hamada S BadrDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID 0000-0002-9808-2344
Benjamin F ZaitchikDepartment of Earth and Planetary Sciences, Johns Hopkins University, Baltimore, MD, 21218, USA. zaitchik@jhu.edu.ORCID 0000-0002-0698-0658
Gaige H KerrDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Nhat-Lan H NguyenCollege of Arts and Sciences, University of Virginia, Charlottesville, VA, 22903, USA.
Yen-Ting ChenDivision of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.
Patrick HinsonCollege of Arts and Sciences, University of Virginia, Charlottesville, VA, 22903, USA.
Josh M ColstonDivision of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.ORCID 0000-0003-4567-5813
Margaret N KosekDivision of Infectious Diseases and International Health, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA.
Ensheng DongDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID 0000-0002-9785-5739
Hongru DuDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Maximilian MarshallDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Kristen NixonDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.
Arash MoheghDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Daniel L GoldbergDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.
Susan C AnenbergDepartment of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, 20052, USA.ORCID 0000-0002-9668-603X
Lauren M GardnerDepartment of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA.ORCID 0000-0003-1083-3850

Funding

Technology CoreU19AI135995 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI Kristian Graugaard Andersen · 2018 to 2026
$32.0M
NIAID NIH HHS U19 AI135995
6 · The paper itself

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.

Indexed as

COVID-19Air PollutionEnvironmentHumansPandemics

Identifiers

PMID37286690
PMCPMC10245354

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.