Social inequalities in vaccine coverage and their effects on epidemic spreading.

IF 3.6 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Adriana Manna, Marton Karsai, Nicola Perra
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引用次数: 0

Abstract

Vaccinations are fundamental public health interventions. Yet, inequalities in vaccine uptake across socioeconomic groups can significantly undermine their impact. Moreover, heterogeneities in vaccination coverage across socioeconomic strata are typically neglected by epidemic models and considered, if at all, only at posteriori. This limitation reduces their ability to predict and assess the effectiveness of vaccination campaigns. Here, we study the impact of socioeconomic inequalities in vaccination uptake on disease burden, measured as attack rate. We consider a modeling framework based on generalized contact matrices that extend traditional age-stratified approaches to incorporate socioeconomic status (SES) variables. We simulate epidemic dynamics under two scenarios. In the first, vaccination campaigns are concurrent with epidemics. In the second, instead, vaccinations are completed before the onset of infection waves. By using both synthetic and empirical generalized contact matrices, we find that inequalities in vaccine uptake can lead to non-linear effects on disease outcomes and exacerbate disease burden in disadvantaged groups of the population. We demonstrate that simpler models ignoring SES heterogeneity produce incomplete or biased predictions of attack rates. Additionally, we show how inequalities in vaccine coverage interact with non-pharmaceutical interventions (NPIs), compounding differences across subgroups. Overall, our findings highlight the importance of integrating SES dimensions, alongside age, into epidemic models to inform more equitable and effective public health interventions and vaccination strategies.

疫苗覆盖率方面的社会不平等及其对流行病传播的影响。
接种疫苗是基本的公共卫生干预措施。然而,不同社会经济群体在疫苗接种方面的不平等可能会严重破坏其影响。此外,不同社会经济阶层的疫苗接种覆盖率的异质性通常被流行病模型所忽视,即使有考虑,也只是在事后考虑。这一限制降低了他们预测和评估疫苗接种运动有效性的能力。在这里,我们研究了接种疫苗的社会经济不平等对疾病负担的影响,以发病率来衡量。我们考虑了一个基于广义接触矩阵的建模框架,该框架扩展了传统的年龄分层方法,以纳入社会经济地位(SES)变量。我们在两种情况下模拟流行病动态。首先,疫苗接种运动与流行病同时进行。相反,在第二种情况下,疫苗接种在感染波开始之前完成。通过使用合成和经验广义接触矩阵,我们发现疫苗摄取的不平等可能导致疾病结局的非线性影响,并加剧弱势群体的疾病负担。我们证明,忽略SES异质性的简单模型会产生不完整或有偏差的发病率预测。此外,我们还展示了疫苗覆盖率的不平等如何与非药物干预(npi)相互作用,从而加剧了亚组之间的差异。总体而言,我们的研究结果强调了将SES维度与年龄一起纳入流行病模型的重要性,以便为更公平和有效的公共卫生干预措施和疫苗接种策略提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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