Governance Policy Evaluation in the United States during the Pandemic: Nonpharmaceutical Interventions or Else?

Abstract

Scientific evidence suggests that nonpharmaceutical interventions (NPIs) effectively curb the spread of COVID-19 before a pharmaceutical solution. Implementing these interventions also significantly affects regular socioeconomic activities and practices of social, racial, and political justice. Local governments often face conflicting goals during policymaking. Striking a balance among competing goals during a global pandemic is a fine science of governance. How well state governments consume the scientific evidence and maintain such a balance remains less understood. This study employs a set of Bayesian hierarchical models to evaluate how state governments in the United States use scientific evidence to balance the fighting against the spread of COVID-19 disease and socioeconomic, racial, social justice, and other demands. We modeled the relationships between five NPI strategies and COVID-19 caseload information and used the modeled result to perform a balanced governance evaluation. The results suggest that governmental attitude and guidance effectively guide the public to fight back against a global pandemic. The more detailed spatiotemporally varying coefficient process model produces 612,000 spatiotemporally varying coefficients, suggesting all measures sometimes work somewhere. Summarized results indicate that states emphasizing NPIs fared well in curbing the spread of COVID-19. With over 1 million deaths due to COVID-19 in the United States, we feel the balance scale likely needs to tip toward preserving human lives. Our evaluation of governance policies is hence based on such an argument. This study aims to provide decision support for policymaking during a national emergency.

科学证据表明, 在药物解决方案出现之前, 非药物干预(NPI)有效遏制了新冠肺炎的传播。实施这些干预措施也会对正常的社会经济活动和社会、种族和政治正义实践产生重大影响。地方政府在决策过程中经常面临相互矛盾的目标。在全球疫情期间, 在相互竞争的目标之间取得平衡是一门治理科学。美国州政府在多大程度上采纳了科学证据并保持这种平衡, 目前还不太清楚。本研究采用一组贝叶斯分层模型, 评估了各个州政府如何利用科学证据, 来平衡抗击新冠肺炎传播和社会经济、种族、社会正义等需求。我们对五种NPI策略与新冠肺炎病例数量之间的关系进行了建模, 并利用模型结果对平衡治理进行了评估。结果表明, 政府的态度和指导有效引导了公众反击全球疫情。通过更详细的时空变化系数过程模型, 制作了612,000个时空变化系数, 表明了所有措施都在某些时候、某些地方有效。综合结果表明, 强调NPI的州在遏制新冠肺炎传播方面表现良好。由于新冠肺炎在美国造成100多万人死亡, 我们认为, 平衡可能需要侧重保护人类生命。我们对治理政策的评估就是基于这样一个观点。本研究旨在为国家紧急状态下的决策提供决策支持。

La evidencia científica sugiere que las intervenciones no farmacéuticas (NPIs) frenan en efecto la dispersión del COVID-19 antes de que ocurra una solución farmacéutica. Implementar estas intervenciones también afecta significativamente las actividades y prácticas socioeconómicas regulares de la justicia social, racial y política. A menudo los gobiernos locales enfrentan objetivos contrapuestos al momento de la aplicación de políticas. Arribar a un equilibrio entre objetivos contrapuestos durante una pandemia global es indicador de una fina ciencia de gobierno. Todavía se desconoce cómo los gobiernos estatales asimilan la evidencia científica y sostienen ese equilibrio. El presente estudio emplea un conjunto de modelos jerárquicos bayesianos para evaluar el modo como los gobiernos estatales usan en Estados Unidos esa evidencia para equilibrar la lucha contra la propagación de la enfermedad del COVID-19, y las demandas socioeconómicas, raciales, justicia social y otras. Modelamos la relación entre cinco estrategias NPI y la información sobre el número de casos, y usamos el resultado de la aplicación del modelo para efectuar una evaluación equilibrada de la gobernanza. Los resultados sugieren que la actitud y orientación gubernamentales guían efectivamente al público para responder apropiadamente en la lucha contra una pandemia global. El modelo más detallado del proceso de coeficientes variables espaciotemporalmente produce 612.000 coeficientes variables espaciotemporalmente, lo cual sugiere que todas las medidas a veces funcionan en alguna parte. Los resultados resumidos indican que los estados que enfatizan las NPIs lograron buenos resultados en su intento por frenar la propagación del COVID-19. Con más de un millón de muertes en Estados Unidos por el COVID-19, nos parece que la balanza debe inclinarse a preservar vidas humanas. Por eso, nuestra evaluación de las políticas de gobernanza se basa en una argumentación de ese tipo. Este estudio apunta a servir de apoyo en la toma de decisiones para la formulación de políticas durante una emergencia nacional.

关键词:

• 平衡化治理
• 贝叶斯空间模型
• 新冠肺炎
• 政策评估

Palabras clave:

• COVID-19
• evaluación de políticas públicas
• gobernanza equilibrada
• modelos espaciales bayesianos

Key Words:

• balanced governance
• Bayesian spatial models
• COVID-19
• policy evaluation

Disclosure Statement

No potential conflict of interest was reported by the authors.

Supplemental Material

Supplemental data for this article can be accessed on the publisher’s site at: https://doi.org/10.1080/24694452.2023.2292807

Additional information

Notes on contributors

Danlin Yu

DANLIN YU is Professor of Urban Geography and GIS in the Department of Earth and Environmental Studies, Montclair State University, Montclair, NJ 07043. E-mail: [email protected]. His research interests include spatial and spatiotemporal data analysis, urban geography, and complex system reconstruction and simulation.

Shenyang Guo

SHENYANG GUO is Frank J. Bruno Distinguished Professor at the Brown School of Washington University in St Louis, St. Louis, MO 63130. E-mail: [email protected]. His research interests include quantitative research methods, child welfare, child mental health, and intervention research.

Yuanyuan Yang

YUANYUAN YANG is a PhD Student in the Brown School of Social Work at Washington University in St. Louis, St. Louis, MO 63130. E-mail: [email protected]. Her research interests include asset-based poverty policy and social determinants of children’s mental health.

Linyun Fu

LINYUN FU is a PhD Student in the Crown Family School of Social Work, Policy, and Practice at the University of Chicago, Chicago, IL 60637. E-mail: [email protected]. Her research interests include program and policy evaluation, intervention research, and child mental health.

Timothy McBride

TIMOTHY McBRIDE is a Professor at the Brown School, Washington University in St. Louis, St. Louis, MO 63130. E-mail: [email protected]. His research interests include health insurance policy, Medicaid, Medicare, health economics, rural health, and long-term care.

Ruopeng An

RUOPENG AN is an Associate Professor in the Brown School and the Division of Computational and Data Sciences at Washington University in St. Louis, St. Louis, MO 63124. E-mail: [email protected]. His research assesses population-level policies, local food and built environment, and socioeconomic determinants that affect individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people with disabilities.