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Social inequalities in vaccine coverage and their effects on epidemic spreading
Title / Series / Name
PLoS Computational Biology
Publication Volume
21
Publication Issue
10
Pages
Editors
Keywords
Computational Biology
Computer Simulation
Epidemics/statistics & numerical data
Humans
Social Class
Socioeconomic Factors
Vaccination Coverage/statistics & numerical data
Vaccination/statistics & numerical data
SDG 3 - Good Health and Well-being
Computer Simulation
Epidemics/statistics & numerical data
Humans
Social Class
Socioeconomic Factors
Vaccination Coverage/statistics & numerical data
Vaccination/statistics & numerical data
SDG 3 - Good Health and Well-being
URI
https://hdl.handle.net/20.500.14018/28327
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.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2025-10
Language
ISBN
Identifiers
10.1371/journal.pcbi.1013585