Health inequities in influenza transmission and surveillance.

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 cap...

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Main Authors: Casey M Zipfel, Vittoria Colizza, Shweta Bansal
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-03-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1008642
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spelling doaj-e7a32480499c48a293ef23c27ad5eadf2021-07-29T04:34:28ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-03-01173e100864210.1371/journal.pcbi.1008642Health inequities in influenza transmission and surveillance.Casey M ZipfelVittoria ColizzaShweta BansalThe 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.https://doi.org/10.1371/journal.pcbi.1008642
collection DOAJ
language English
format Article
sources DOAJ
author Casey M Zipfel
Vittoria Colizza
Shweta Bansal
spellingShingle Casey M Zipfel
Vittoria Colizza
Shweta Bansal
Health inequities in influenza transmission and surveillance.
PLoS Computational Biology
author_facet Casey M Zipfel
Vittoria Colizza
Shweta Bansal
author_sort Casey M Zipfel
title Health inequities in influenza transmission and surveillance.
title_short Health inequities in influenza transmission and surveillance.
title_full Health inequities in influenza transmission and surveillance.
title_fullStr Health inequities in influenza transmission and surveillance.
title_full_unstemmed Health inequities in influenza transmission and surveillance.
title_sort health inequities in influenza transmission and surveillance.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2021-03-01
description 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.
url https://doi.org/10.1371/journal.pcbi.1008642
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