Policy responsiveness and institutions in a federal system: Analyzing variations in state-level data transparency and equity issues during the COVID-19 pandemic.

Agency Theory Covid-19 Pandemic Data Equity Data Transparency Federalism Institutions

Journal

International journal of disaster risk reduction : IJDRR
ISSN: 2212-4209
Titre abrégé: Int J Disaster Risk Reduct
Pays: England
ID NLM: 101613236

Informations de publication

Date de publication:
Jul 2022
Historique:
received: 11 09 2021
revised: 15 02 2022
accepted: 16 05 2022
pubmed: 1 6 2022
medline: 1 6 2022
entrez: 31 5 2022
Statut: ppublish

Résumé

In the absence of a coherent federal response to COVID-19 in the United States, state governments played a significant role with varying policy responses, including in data collection and reporting. However, while accurate data collection and disaggregation is critically important since it is the basis for mitigation policy measures and to combat health disparities, it has received little scholarly attention. To address this gap, this study employs agency theory to focus on state-level determinants of data transparency practices by examining factors affecting variations in state data collection, reporting, and disaggregation of both overall metrics and race/ethnicity data. Using ordered logistic regression analyses, we find that legislatures, rather than governors, are important institutional actors and that a conservative ideology signal and socio-economic factors help predict data reporting and transparency practices. These results suggest that there is a critical need for standardized data collection protocols, the collection of comprehensive race and ethnicity data, and analyses examining data transparency and reductions in information asymmetries as a pandemic response tool-both in the United States and globally.

Identifiants

pubmed: 35637763
doi: 10.1016/j.ijdrr.2022.103066
pii: S2212-4209(22)00285-0
pmc: PMC9132784
doi:

Types de publication

Journal Article

Langues

eng

Pagination

103066

Informations de copyright

© 2022 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Alka Sapat (A)

School of Public Administration, Florida Atlantic University, USA.

Ryan J Lofaro (RJ)

School of Public Administration, Florida Atlantic University, USA.

Benjamin Trautman (B)

School of Public Administration, Florida Atlantic University, USA.

Classifications MeSH