Unsupervised learning for county-level typological classification for COVID-19 research
The analysis of county-level COVID-19 pandemic data faces computational and analytic challenges, particularly when considering the heterogeneity of data sources with variation in geographic, demographic, and socioeconomic factors between counties. This study presents a method to join relevant data f...
Main Authors: | Lai, Yuan, Charpignon, Marie-Laure, Ebner, Daniel K., Celi, Leo Anthony G. |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Urban Studies and Planning |
Format: | Article |
Published: |
Elsevier BV
2020
|
Online Access: | https://hdl.handle.net/1721.1/127198 |
Similar Items
-
Data sharing in the era of COVID-19
by: Cosgriff, Christopher V, et al.
Published: (2020) -
Structural Racism and COVID-19 in the USA: a County-Level Empirical Analysis
by: Tan, Shin B., et al.
Published: (2022) -
COVID-19: Putting the General Data Protection Regulation to the Test
by: McLennan, Stuart, et al.
Published: (2020) -
Social inequality and the syndemic of chronic disease and COVID-19: county-level analysis in the USA
by: Islam, N, et al.
Published: (2021) -
Modeling between-population variation in COVID-19 dynamics in Hubei, Lombardy, and New York City
by: Wilder, Bryan, et al.
Published: (2020)