Health inequities in influenza transmission and surveillance

Abstract

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.

Changing socio-economic and ethnic disparities in influenza/A/H1N1 infection early in the 2009 UK epidemic: a descriptive analysis

“…There are two important possible factors, which would be consistent with observations: firstly, sustained transmission may be more likely to start within more deprived regions and South Asian populations due to variation in surveillance and interaction with healthcare. Similar to recent findings from Zipfel et al [26] in the United States, which suggest that lower visibility [27] and poor access to health care combine with isolation of particular groups on social networks to create inequalities in population risk regardless of individual level transmission risk. A second explanation could be that when sustained transmission occurs, transmission rates are generally higher in South Asian and deprived populations.…”

Large university with high COVID-19 incidence is not associated with excess cases in non-student population

“…Senior status and educational attainment may underlie COVID-19 risk tolerance or the ability to work from home, respectively. These factors may also be linked to socioeconomic status, which is known to impact health outcomes for respiratory viruses in the US 28 , 29 . Non-student Centre County residents reported a higher median household income compared to neighboring counties and students in Centre County, which may indicate they were more able to quarantine and work from home.…”

Networks, cultures, and institutions: Toward a social immunology

“…In their systematic review of presenteeism, Webster and co-authors (2019) find an overall prevalence of 35–97% and a range of 37–97% in healthcare settings. There are multiple potential structural antecedents of presenteeism, such as high workloads and limitations on sick leave, which is known to increase influenza burden in low SES individuals and communities ( Zipfel et al., 2021 ). Of particular interest within the social immunology framework, however, are perceptions on the part of the sick individual, namely that presenteeism is the organizational norm or that they are simply “not sick enough” to justify using sick leave ( Webster et al., 2019 ), which are both related to cultural norms.…”