Department of Biology, Georgetown University, Washington DC, United States of America.
INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012 Paris, France.
PLoS Comput Biol. 2021 Mar 11;17(3):e1008642. doi: 10.1371/journal.pcbi.1008642. eCollection 2021 Mar.
The lower an individual's socioeconomic position, the higher their risk of poor health in low-, middle-, and high-income settings alike. As health inequities grow, it is imperative that we develop an empirically-driven mechanistic understanding of the determinants of health disparities, and capture disease burden in at-risk populations to prevent exacerbation of disparities. Past work has been limited in data or scope and has thus fallen short of generalizable insights. Here, we integrate empirical data from observational studies and large-scale healthcare data with models to characterize the dynamics and spatial heterogeneity of health disparities in an infectious disease case study: influenza. We find that variation in social and healthcare-based determinants exacerbates influenza epidemics, and that low socioeconomic status (SES) individuals disproportionately bear the burden of infection. We also identify geographical hotspots of influenza burden in low SES populations, much of which is overlooked in traditional influenza surveillance, and find that these differences are most predicted by variation in susceptibility and access to sickness absenteeism. Our results highlight that the effect of overlapping factors is synergistic and that reducing this intersectionality can significantly reduce inequities. Additionally, health disparities are expressed geographically, and targeting public health efforts spatially may be an efficient use of resources to abate inequities. The association between health and socioeconomic prosperity has a long history in the epidemiological literature; addressing health inequities in respiratory-transmitted infectious disease burden is an important step towards social justice in public health, and ignoring them promises to pose a serious threat.
在低、中、高收入环境中,个体的社会经济地位越低,其健康状况不佳的风险就越高。随着健康不平等的加剧,我们必须从经验上深入了解健康差异的决定因素,并在高危人群中捕捉疾病负担,以防止差异加剧。过去的工作在数据或范围上受到限制,因此没有得出普遍适用的见解。在这里,我们将观察性研究和大规模医疗保健数据中的实证数据与模型相结合,以描述传染病案例研究中健康差异的动态和空间异质性:流感。我们发现,社会和医疗保健相关决定因素的差异加剧了流感疫情,而社会经济地位较低的个人不成比例地承受着感染的负担。我们还确定了低社会经济地位人群中流感负担的地理热点,其中大部分在传统的流感监测中被忽视,并且发现这些差异主要由易感性和病假缺勤机会的变化来预测。我们的研究结果表明,重叠因素的影响是协同的,减少这种交叉性可以显著减少不平等。此外,健康差异具有地域性,从空间上定位公共卫生工作可能是一种利用资源来减轻不平等的有效方法。健康与社会经济繁荣之间的关联在流行病学文献中有很长的历史;解决呼吸道传染病负担方面的健康不平等问题是实现公共卫生社会正义的重要一步,而忽视这些问题将构成严重威胁。