Storymodelers Lab, Graduate Program in International Studies, Virginia Modeling, Analysis, and Simulation Center, Old Dominion University, Norfolk, VA, United States.
Storymodelers Lab, Virginia Modeling Analysis and Simulation Center, Old Dominion University, Suffolk, VA, United States.
Front Public Health. 2023 May 3;11:1042570. doi: 10.3389/fpubh.2023.1042570. eCollection 2023.
Equitable and effective vaccine uptake is a key issue in addressing COVID-19. To achieve this, we must comprehensively characterize the context-specific socio-behavioral structural determinants of vaccine uptake. However, to quickly focus public health interventions, state agencies and planners often rely on already existing indexes of "vulnerability." Many such "vulnerability indexes" exist and become benchmarks for targeting interventions in wide ranging scenarios, but they vary considerably in the factors and themes that they cover. Some are even uncritical of the use of the word "vulnerable," which should take on different meanings in different contexts. The objective of this study is to compare four vulnerability indexes produced by private, federal, and state institutions to assess the application of these measures to the needs of the COVID-19 pandemic and other emergent crises. We focus on federal, state, and private industries' vulnerability indexes for the Commonwealth of Virginia. Qualitative comparison is done by considering each index's methodologies to see how and why they defined and measured "vulnerability." We also quantitatively compare them using percent agreement and illustrate the overlaps in localities identified as among the most vulnerable on a choropleth map. Finally, we provide a short case study that explores vaccine uptake in the six localities that were identified by at least three indexes as most vulnerable, and six localities with very low vaccine coverage that were identified by two or fewer indexes as highly vulnerable. By comparing the methodologies and index (dis)agreements, we discuss the appropriateness of using pre-existing vulnerability indexes as a public health decision-making tool for emergent crises, using COVID-19 vaccine uptake as a case study. The inconsistencies reflected by these indexes show both the need for context-specific and time-sensitive data collection in public health and policy response, and a critical critique of measured "vulnerability."
公平有效地接种疫苗是应对 COVID-19 的关键问题。为此,我们必须全面描述具体情况下影响疫苗接种的社会行为结构决定因素。然而,为了快速集中公共卫生干预措施,州政府机构和规划者通常依赖于现有的“脆弱性”指标。存在许多此类“脆弱性指标”,并且成为在广泛场景中进行干预的基准,但它们在涵盖的因素和主题方面存在很大差异。其中一些甚至对使用“脆弱”一词不加批判,因为这个词在不同的上下文中应该有不同的含义。本研究的目的是比较四个由私营、联邦和州机构制定的脆弱性指标,以评估这些措施在 COVID-19 大流行和其他紧急危机中的应用。我们专注于弗吉尼亚州的联邦、州和私营部门的脆弱性指标。通过考虑每个指数的方法,进行定性比较,以了解它们如何以及为何定义和衡量“脆弱性”。我们还使用百分比一致性进行定量比较,并在专题地图上说明被确定为最脆弱的地区的重叠情况。最后,我们提供了一个简短的案例研究,探讨了至少有三个指标将六个地方确定为最脆弱的地方以及至少有两个指标将六个地方确定为高风险地区的疫苗接种情况。通过比较方法和指标(不一致),我们讨论了在紧急情况下使用现有脆弱性指标作为公共卫生决策工具的适当性,以 COVID-19 疫苗接种为案例研究。这些指标反映的不一致性既表明了公共卫生和政策应对需要针对具体情况和时间敏感的数据收集,也表明了对衡量“脆弱性”的批判性批判。