Health inequities in influenza transmission and surveillance

Abstract

The lower an individual's socio-economic 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 generating 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, behavioral, and physiological determinants exacerbates influenza epidemics, and that low SES individuals disproportionately bear the burden of infection. We also identify geographical hotspots of disproportionate influenza burden in low SES populations, and find that these differences are most predicted by variation in healthcare utilization and susceptibility. The negative association between health and socio-economic prosperity has a long history in the epidemiological literature. Addressing health inequities in respiratory infectious disease burden is an important step towards social justice in public health, and ignoring them promises to pose a serious threat to the entire population. Our results highlight that the effect of overlapping behavioral social, and physiological factors is synergistic and that reducing this intersectionality can significantly reduce inequities. Additionally, health disparities are expressed geographically, as targeting public health efforts spatially may be an efficient use of resources to abate inequities.

Increased travel times to United States SARS-CoV-2 testing sites: a spatial modeling study

“…Inequalities in geographic accessibility to healthcare in the US have been documented to cause negative health outcomes for seasonal influenza transmission and other diseases 5 . Further, travel time negatively impacts healthcare-seeking behavior 6 .…”

Distinct patterns of SARS-CoV-2 transmission in two nearby communities in Wisconsin, USA

“…Whereas Milwaukee County’s cumulative incidence was best predicted with the model using high transmission heterogeneity ( Fig 5B ). A greater role for superspreading events in Milwaukee versus Dane County could be explained by higher population density, higher poverty rates, and worse healthcare access ( Table 1 ), all of which may increase contact rates and impede physical distancing efforts 34 – 38 . Assuming moderate transmission heterogeneity in Dane County, estimated R 0 prior to 25 March was 2.24 [1.86, 2.65] and the median estimated cumulative incidence at the end of the study period (26 April) was 4,546 infections [1,187, 23,709] compared to 405 positive tests.…”

Exposure and susceptibility: The Twin Pillars of infection

“…Such an emphasis risks misrepresenting the magnitude of effect that such measures are likely to have on disease outcome, particularly compared to vaccine‐mediated changes in susceptibility or effective exposure reduction (Figure 1). Similarly, lower income individuals are more susceptible to infection with influenza regardless of exposure (Cohen et al, 2008), which contributes heavily to socioeconomic disparities in influenza rates in the United States (Zipfel et al, 2021). Strikingly, ameliorating these susceptibility differences could reduce disease burden at least as much as exposure‐based control (Zipfel et al, 2021).…”

“…Similarly, lower income individuals are more susceptible to infection with influenza regardless of exposure (Cohen et al, 2008), which contributes heavily to socioeconomic disparities in influenza rates in the United States (Zipfel et al, 2021). Strikingly, ameliorating these susceptibility differences could reduce disease burden at least as much as exposure‐based control (Zipfel et al, 2021). In the case of soil‐transmitted helminths, the best and most geographically equitable interventions involve both exposure reduction via water and hygiene initiatives (breaking the transmission cycle; Koski & Scott, 2001) and immune supplementation through increased nutritional availability, with potentially synergistic results (Sweeny, Clerc, et al, 2021).…”