Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic.
Sci Data
; 10(1): 367, 2023 06 07.
Article
in English
| MEDLINE | ID: covidwho-20232780
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.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
COVID-19
Type of study:
Observational study
/
Prognostic study
Topics:
Vaccines
Limits:
Humans
Language:
English
Journal:
Sci Data
Year:
2023
Document Type:
Article
Affiliation country:
S41597-023-02276-y
Similar
MEDLINE
...
LILACS
LIS