Summary of regression results: GLM-2.
<div><p>The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their official COVID-19 communications. As such, the Forecast Hub is a critical centralized resource to p...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , , , |
| Published: |
2025
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1852021128708489216 |
|---|---|
| author | Saad Mohammad Abrar (21162498) |
| author2 | Naman Awasthi (21162501) Daniel Smolyak (21162504) Nekabari Sigalo (21162507) Vanessa Frias Martinez (21162510) |
| author2_role | author author author author |
| author_facet | Saad Mohammad Abrar (21162498) Naman Awasthi (21162501) Daniel Smolyak (21162504) Nekabari Sigalo (21162507) Vanessa Frias Martinez (21162510) |
| author_role | author |
| dc.creator.none.fl_str_mv | Saad Mohammad Abrar (21162498) Naman Awasthi (21162501) Daniel Smolyak (21162504) Nekabari Sigalo (21162507) Vanessa Frias Martinez (21162510) |
| dc.date.none.fl_str_mv | 2025-04-22T20:03:28Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0319383.t004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/dataset/Summary_of_regression_results_GLM-2_/28843431 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified higher prediction errors critical centralized resource specific social groups comprehensive fairness analysis 19 forecast hub forecast hub ethnic groups 19 pandemic 19 modelers 19 forecasts 19 communications xlink "> urbanization level potential harms minority racial disease control |
| dc.title.none.fl_str_mv | Summary of regression results: GLM-2. |
| dc.type.none.fl_str_mv | Dataset info:eu-repo/semantics/publishedVersion dataset |
| description | <div><p>The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their official COVID-19 communications. As such, the Forecast Hub is a critical centralized resource to promote transparent decision making. While the Forecast Hub has provided valuable predictions focused on accuracy, there is an opportunity to evaluate model performance across social determinants such as race and urbanization level that have been known to play a role in the COVID-19 pandemic. In this paper, we carry out a comprehensive fairness analysis of the Forecast Hub model predictions and we show statistically significant diverse predictive performance across social determinants, with minority racial and ethnic groups as well as less urbanized areas often associated with higher prediction errors. We hope this work will encourage COVID-19 modelers and the CDC to report fairness metrics together with accuracy, and to reflect on the potential harms of the models on specific social groups and contexts.</p></div> |
| eu_rights_str_mv | openAccess |
| id | Manara_afd4e8232abea44fea4bc5cd88a61dfe |
| identifier_str_mv | 10.1371/journal.pone.0319383.t004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28843431 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Summary of regression results: GLM-2.Saad Mohammad Abrar (21162498)Naman Awasthi (21162501)Daniel Smolyak (21162504)Nekabari Sigalo (21162507)Vanessa Frias Martinez (21162510)Science PolicyBiological Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedhigher prediction errorscritical centralized resourcespecific social groupscomprehensive fairness analysis19 forecast hubforecast hubethnic groups19 pandemic19 modelers19 forecasts19 communicationsxlink ">urbanization levelpotential harmsminority racialdisease control<div><p>The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their official COVID-19 communications. As such, the Forecast Hub is a critical centralized resource to promote transparent decision making. While the Forecast Hub has provided valuable predictions focused on accuracy, there is an opportunity to evaluate model performance across social determinants such as race and urbanization level that have been known to play a role in the COVID-19 pandemic. In this paper, we carry out a comprehensive fairness analysis of the Forecast Hub model predictions and we show statistically significant diverse predictive performance across social determinants, with minority racial and ethnic groups as well as less urbanized areas often associated with higher prediction errors. We hope this work will encourage COVID-19 modelers and the CDC to report fairness metrics together with accuracy, and to reflect on the potential harms of the models on specific social groups and contexts.</p></div>2025-04-22T20:03:28ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0319383.t004https://figshare.com/articles/dataset/Summary_of_regression_results_GLM-2_/28843431CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/288434312025-04-22T20:03:28Z |
| spellingShingle | Summary of regression results: GLM-2. Saad Mohammad Abrar (21162498) Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified higher prediction errors critical centralized resource specific social groups comprehensive fairness analysis 19 forecast hub forecast hub ethnic groups 19 pandemic 19 modelers 19 forecasts 19 communications xlink "> urbanization level potential harms minority racial disease control |
| status_str | publishedVersion |
| title | Summary of regression results: GLM-2. |
| title_full | Summary of regression results: GLM-2. |
| title_fullStr | Summary of regression results: GLM-2. |
| title_full_unstemmed | Summary of regression results: GLM-2. |
| title_short | Summary of regression results: GLM-2. |
| title_sort | Summary of regression results: GLM-2. |
| topic | Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified higher prediction errors critical centralized resource specific social groups comprehensive fairness analysis 19 forecast hub forecast hub ethnic groups 19 pandemic 19 modelers 19 forecasts 19 communications xlink "> urbanization level potential harms minority racial disease control |