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Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model
BACKGROUND: Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences—such as contact r...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156851/ https://www.ncbi.nlm.nih.gov/pubmed/30253772 http://dx.doi.org/10.1186/s12916-018-1152-1 |
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author | Munday, James D. van Hoek, Albert Jan Edmunds, W. John Atkins, Katherine E. |
author_facet | Munday, James D. van Hoek, Albert Jan Edmunds, W. John Atkins, Katherine E. |
author_sort | Munday, James D. |
collection | PubMed |
description | BACKGROUND: Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences—such as contact rates and susceptibility—affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood. METHODS: To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data. RESULTS: Our model suggests realistic differences in two key factors contributing to the rates of transmission—contact rate and susceptibility—between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake. CONCLUSION: Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12916-018-1152-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6156851 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-61568512018-09-27 Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model Munday, James D. van Hoek, Albert Jan Edmunds, W. John Atkins, Katherine E. BMC Med Research Article BACKGROUND: Social and cultural disparities in infectious disease burden are caused by systematic differences between communities. Some differences have a direct and proportional impact on disease burden, such as health-seeking behaviour and severity of infection. Other differences—such as contact rates and susceptibility—affect the risk of transmission, where the impact on disease burden is indirect and remains unclear. Furthermore, the concomitant impact of vaccination on such inequalities is not well understood. METHODS: To quantify the role of differences in transmission on inequalities and the subsequent impact of vaccination, we developed a novel mathematical framework that integrates a mechanistic model of disease transmission with a demographic model of social structure, calibrated to epidemiologic and empirical social contact data. RESULTS: Our model suggests realistic differences in two key factors contributing to the rates of transmission—contact rate and susceptibility—between two social groups can lead to twice the risk of infection in the high-risk population group relative to the low-risk population group. The more isolated the high-risk group, the greater this disease inequality. Vaccination amplified this inequality further: equal vaccine uptake across the two population groups led to up to seven times the risk of infection in the high-risk group. To mitigate these inequalities, the high-risk population group would require disproportionately high vaccination uptake. CONCLUSION: Our results suggest that differences in contact rate and susceptibility can play an important role in explaining observed inequalities in infectious diseases. Importantly, we demonstrate that, contrary to social policy intentions, promoting an equal vaccine uptake across population groups may magnify inequalities in infectious disease risk. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12916-018-1152-1) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-26 /pmc/articles/PMC6156851/ /pubmed/30253772 http://dx.doi.org/10.1186/s12916-018-1152-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Munday, James D. van Hoek, Albert Jan Edmunds, W. John Atkins, Katherine E. Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title | Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title_full | Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title_fullStr | Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title_full_unstemmed | Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title_short | Quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
title_sort | quantifying the impact of social groups and vaccination on inequalities in infectious diseases using a mathematical model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6156851/ https://www.ncbi.nlm.nih.gov/pubmed/30253772 http://dx.doi.org/10.1186/s12916-018-1152-1 |
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