Statistical analysis of effective Covid-19 government response policies
Insights From Pre-Omicron Pandemic Data
Dados Bibliográficos
| ID | 7158798 |
|---|---|
| Autores | Benoit Ahanda (0009-0009-9533-2561, Bradley University, autor correspondente), Caleb Brinkman (0009-0008-7925-3647, Bradley University), Türkay Yolcu (0009-0002-5435-9417, Bradley University) |
| Ano | 2026 |
| Volume | 9 |
| Fascículo | 1 |
| Data de publicação | 2026-02-01 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Journal of Computational Social Science (JOURNAL) |
| Identificadores do periódico | ISSN: 2432-2725 • E-ISSN: 2432-2717 |
| Editora | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s42001-025-00441-4 |
| OpenAlex | W7108461320 |
| Idioma | EN |
| Referências citadas | 27 |
Cluster analysis · Pandemic · Politics · Public policy · Regression analysis · COVID-19 Digital Contact Tracing · COVID-19 epidemiological studies · Misinformation and Its Impacts
Finding Groups in Data
Regularization and Variable Selection Via the Elastic Net
The Bayesian Lasso
Sampling-Based Approaches to Calculating Marginal Densities
How Covid-19 shaped mental health
Regularization Paths for Generalized Linear Models via Coordinate Descent
Regression Shrinkage and Selection Via the Lasso
Effects of Social Mobility and Stringency Measures on the Covid-19 Outcomes
Evidence of the effectiveness of travel-related measures during the early phase of the Covid-19 pandemic
A global panel database of pandemic policies (Oxford Covid-19 Government Response Tracker)
Polarized Politics
I'm Not Sure What to Believe
| Velocidade de citação | historical |
|---|---|
| Altamente citado | Não |