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Seroprevalence convergence masks persistent socioeconomic disparities in SARS-CoV-2 infection risk in Canada

Epidemics·August 4Open Access
Infectious DiseasesPractice changingCOVID-19SARS-CoV-2 InfectionDynamic Mathematical Modelling Of Serial Cross-Sectional DataSerosurveillanceAdultAnti-Nucleocapsid Antibody Testing

Summary

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What was studied

Using serial cross-sectional anti-nucleocapsid seroprevalence data from Canadian Blood Services donors (April 2021–April 2023), this study assessed whether seroprevalence convergence across socioeconomic strata truly reflected reduced SARS-CoV-2 infection risk, or masked persistent disparities in force of infection by area-level material deprivation quintile.

Key findings

Pre-Omicron, the most deprived quintile (Q5) had a 71% higher force of infection than the least deprived (Q1; IRR 1.71, 95% CI 1.60–1.83). After Omicron, relative disparity compressed (Q5 vs Q1 IRR: 1.12, 95% CI 1.11–1.14) due to disproportionate amplification in less-deprived groups (48.5-fold increase in Q1 vs 31.8-fold in Q5), but Q5 continued to have the highest absolute infection rate throughout.

Study limitations

- Blood donors are not representative of the general population, potentially introducing selection bias in seroprevalence estimates. - Area-level material deprivation is an ecological proxy and may not capture individual-level socioeconomic variation. - The model assumes a sero-reversion framework; unmeasured heterogeneity in antibody waning across deprivation strata could affect estimates.

Clinical implications

Seroprevalence convergence across income groups should not be interpreted as equity in infection risk — lower-income communities continued to face higher absolute SARS-CoV-2 exposure even during Omicron. Public health interventions targeting socioeconomically deprived populations remain warranted even when aggregate surveillance data appear to show parity.

Related Questions

Explore related topics

How did socioeconomic disparities in COVID-19 infection risk change during the Omicron wave?What are the limitations of using seroprevalence data to assess health equity in infectious disease?How should public health programs target high-deprivation communities when aggregate COVID-19 data show convergence?

Publication Details

Year
2026
Journal
Epidemics
Source
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