Socioeconomic bias in influenza surveillance

Scarpino, Samuel V.; Scott, James G.; Eggo, Rosalind M; Clements, Bruce W.; Dimitrov, Nedialko B.; Meyers, Lauren Ancel

doi:10.1371/journal.pcbi.1007941

Cited by 20 publications

(16 citation statements)

References 69 publications

(96 reference statements)

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“…While this negative association may be the result of lower exposure in impoverished areas (as suggested by [ 18 ]), it is likely that there exist spatial and social heterogeneities in surveillance caused by healthcare utilization. Indeed, Scarpino et al have shown that the most impoverished areas are blindspots in the US influenza sentinel surveillance system, ILINet, and models based on these data make the best predictions in affluent areas, while making the worst predictions in impoverished locations [ 32 ]. To better understand and respond to influenza epidemics and pandemics, we must improve our capability to detect and monitor outbreaks in at-risk populations.…”

Section: Introductionmentioning

confidence: 99%

Health inequities in influenza transmission and surveillance

2021

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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.

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Section: Introductionmentioning

confidence: 99%

Health inequities in influenza transmission and surveillance

2021

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“…Metabolic health, being particularly emphasized in our study, is not the only disadvantage in the low socio-economic brackets of our society. Influenza-related complications and hospitalization rates [89] have demonstrated that preventative and therapeutic health care, limited sick leave, and household structure might also play a role that needs to be considered.…”

Section: Discussionmentioning

confidence: 99%

Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containment

et al. 2021

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We propose and study an epidemiological model on a social network that takes into account heterogeneity of the population and different vaccination strategies. In particular, we study how the COVID-19 epidemics evolves and how it is contained by different vaccination scenarios by taking into account data showing that older people, as well as individuals with comorbidities and poor metabolic health, and people coming from economically depressed areas with lower quality of life in general, are more likely to develop severe COVID-19 symptoms, and quicker loss of immunity and are therefore more prone to reinfection. Our results reveal that the structure and the spatial arrangement of subpopulations are important epidemiological determinants. In a healthier society the disease spreads more rapidly but the consequences are less disastrous as in a society with more prevalent chronic comorbidities. If individuals with poor health are segregated within one community, the epidemic outcome is less favorable. Moreover, we show that, contrary to currently widely adopted vaccination policies, prioritizing elderly and other higher-risk groups is beneficial only if the supply of vaccine is high. If, however, the vaccination availability is limited, and if the demographic distribution across the social network is homogeneous, better epidemic outcomes are achieved if healthy people are vaccinated first. Only when higher-risk groups are segregated, like in elderly homes, their prioritization will lead to lower COVID-19 related deaths. Accordingly, young and healthy individuals should view vaccine uptake as not only protecting them, but perhaps even more so protecting the more vulnerable socio-demographic groups.

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“…In a cohort study of people receiving care through the U.S. Department of Veterans Affairs, Black and Hispanic patients had both higher rates of testing and higher rates of positivity (37). Disparity in surveillance quality across socioeconomic strata, where communities that experience disproportionate risk also have the poorest quality surveillance, is hardly unique to COVID-19 (38).…”

Section: Discussionmentioning

confidence: 99%

Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020

Holden

Richardson

Arevalo

et al. 2021

Preprint

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Background Availability of SARS-CoV-2 testing in the United States (U.S.) has fluctuated through the course of the COVID-19 pandemic, including in the U.S. state of Illinois. Despite substantial ramp-up in test volume, access to SARS-CoV-2 testing remains limited, heterogeneous, and insufficient to control spread. Methods We compared SARS-CoV-2 testing rates across geographic regions, over time, and by demographic characteristics (i.e., age and racial/ethnic groups) in Illinois during March through December 2020. We compared age-matched case fatality ratios and infection fatality ratios through time to estimate the fraction of SARS-CoV-2 infections that have been detected through diagnostic testing. Results By the end of 2020, initial geographic differences in testing rates had closed substantially. Case fatality ratios were higher in non-Hispanic Black and Hispanic/Latino populations in Illinois relative to non-Hispanic White populations, suggesting that tests were insufficient to accurately capture the true burden of COVID-19 disease in the minority populations during the initial epidemic wave. While testing disparities decreased during 2020, Hispanic/Latino populations consistently remained the least tested at 1.87 tests per 1000 population per day compared with 2.58 and 2.87 for non-Hispanic Black and non-Hispanic White populations, respectively, at the end of 2020. Despite a large expansion in testing since the beginning of the first wave of the epidemic, we estimated that over half (50-80%) of all SARS-CoV-2 infections were not detected by diagnostic testing and continued to evade surveillance. Conclusions Systematic methods for identifying relatively under-tested geographic regions and demographic groups may enable policymakers to regularly monitor and evaluate the shifting landscape of diagnostic testing, allowing officials to prioritize allocation of testing resources to reduce disparities in COVID-19 burden and eventually reduce SARS-CoV-2 transmission.

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Socioeconomic bias in influenza surveillance

Cited by 20 publications

References 69 publications

Health inequities in influenza transmission and surveillance

Health inequities in influenza transmission and surveillance

Socio-demographic and health factors drive the epidemic progression and should guide vaccination strategies for best COVID-19 containment

Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020

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