Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?
Community vulnerability and mobility: What matters most in spatio-temporal modeling of the COVID-19 pandemic?
复制标题
社区脆弱性和流动性：在19ci-the Covid-19大流行中最重要的是最重要的？
DOI：
10.1016/j.socscimed.2021.114395
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发表时间：
2021-10
期刊：
影响因子：
--
通讯作者：
Prentice CR
中科院分区：
文献类型：
--
作者：
Carroll R;Prentice CR
社区脆弱性被广泛认为是建模疾病时要考虑的一个重要方面。尽管COVID-19对弱势群体的影响不成比例，但以社区流动性衡量的人类行为对理解疾病传播同样有影响。在本研究中，我们试图了解四种复合测量方法中哪一种在解释疾病传播和死亡率方面表现最好，并且我们探索了流动性在多大程度上解释了感兴趣结果的差异。我们比较了两种社区流动性措施、三种社区脆弱性综合措施和一种结合脆弱性和人类行为的综合措施，以评估它们在美国COVID-19大流行建模中的相对可行性。通过时间依赖的固定效应系数，实现了常用贝叶斯时空泊松病映射模型的扩展，并在拟合优度以及估计精度和可行性方面进行了比较。对拟合优度度量的比较几乎一致表明，基于人类行为的模型更优越。居住流动时间测量表明，流动性与COVID-19大流行之间存在两种独特且看似相反的关系：研究结果表明，在大流行早期，COVID-19的存在减少，流动性减少；在大流行后期，COVID-19的存在增加，流动性减少。早期的迹象可能受到国家发布的大量居家令和自我隔离的影响，而后期的迹象可能是由于在一个限制有限的国家举行假日聚会而出现的。这项研究采用了创新的统计方法，并提供了挑战普遍接受的观念的结果，即脆弱性和剥夺是理解健康结果差异的关键。我们表明，人类行为对理解疾病传播同样重要，如果不是更重要的话。我们鼓励研究人员在这里开展的工作的基础上，继续探索其他行为如何影响COVID-19的传播。
Community vulnerability is widely viewed as an important aspect to consider when modeling disease. Although COVID-19 does disproportionately impact vulnerable populations, human behavior as measured by community mobility is equally influential in understanding disease spread. In this research, we seek to understand which of four composite measures perform best in explaining disease spread and mortality, and we explore the extent to which mobility account for variance in the outcomes of interest. We compare two community mobility measures, three composite measures of community vulnerability, and one composite measure that combines vulnerability and human behavior to assess their relative feasibility in modeling the US COVID-19 pandemic. Extensions – via temporally dependent fixed effect coefficients – of the commonly used Bayesian spatio-temporal Poisson disease mapping models are implemented and compared in terms of goodness of fit as well as estimate precision and viability. A comparison of goodness of fit measures nearly unanimously suggests the human behavior-based models are superior. The duration at residence mobility measure indicates two unique and seemingly inverse relationships between mobility and the COVID-19 pandemic: the findings indicate decreased COVID-19 presence with decreased mobility early in the pandemic and increased COVID-19 presence with decreased mobility later in the pandemic. The early indication is likely influenced by a large presence of state-issued stay at home orders and self-quarantine, while the later indication likely emerges as a consequence of holiday gatherings in a country under limited restrictions. This study implements innovative statistical methods and furnishes results that challenge the generally accepted notion that vulnerability and deprivation are key to understanding disparities in health outcomes. We show that human behavior is equally, if not more important to understanding disease spread. We encourage researchers to build upon the work we start here and continue to explore how other behaviors influence the spread of COVID-19.
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