
Using Quantifiable Behavioral Traits to Predict a Country's COVID19 Infection Rates
COVID19 has shown that indicators that are a function of a nation's economy and healthcare infrastructure are inaccurate in predicting a country's outcomes should a health pandemic occur. Our poster suggests the utilization of quantifiable traits like Individualism, Power Distance, Masculinity, Uncertainty avoidance, long-term orientation, and Indulgence to predict a country's COVID19 infection rates. This is accomplished by applying machine learning techniques like CART imputation and Poisson regression against COVID and behavioral datasets.
Files
Metadata
Work Title | Using Quantifiable Behavioral Traits to Predict a Country's COVID19 Infection Rates |
---|---|
Access | |
Creators |
|
Keyword |
|
License | CC BY 4.0 (Attribution) |
Work Type | Poster |
Publisher |
|
Publication Date | April 2021 |
Subject |
|
Language |
|
Publisher Identifier (DOI) |
|
Related URLs | |
Deposited | July 16, 2021 |
Versions
Analytics
Collections
This resource is currently not in any collection.