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DOI: 10.1101/2023.05.23.23290384

Information bias of vaccine effectiveness estimation due to informed consent for national registration of COVID-19 vaccination: estimation and correction using a data augmentation model

H.van Werkhoven B. de Gier S. A. McDonald ...+3 M. Knol
Background: Registration in the Dutch national COVID-19 vaccination register requires consent from the vaccinee. This causes misclassification of non-consenting vaccinated persons as being unvaccinated. We quantified and corrected the resulting information bias in the estimation of vaccine effectiveness (VE). Methods: National data were used for the period dominated by the SARS-CoV-2 Delta variant (11 July to 15 November 2021). VE ((1-relative risk)*100%) against COVID-19 hospitalization and ICU admission was estimated for individuals 12-49, 50-69, and [≥]70 years of age using negative binomial regression. Anonymous data on vaccinations administered by the Municipal Health Services were used to determine informed consent percentages and estimate corrected VEs by iterative data augmentation. Absolute bias was calculated as the absolute change in VE; relative bias as uncorrected / corrected relative risk. Results: A total of 8,804 COVID-19 hospitalizations and 1,692 COVID-19 ICU admissions were observed. The bias was largest in the 70+ age group where the non-consent proportion was 7.0% and observed vaccination coverage was 87%: VE of primary vaccination against hospitalization changed from 75.5% (95% CI 73.5-77.4) before to 85.9% (95% CI 84.7-87.1) after correction (absolute bias -10.4 percentage point, relative bias 1.74). VE against ICU admission in this group was 88.7% (95% CI 86.2-90.8) before and 93.7% (95% CI 92.2-94.9) after correction (absolute bias -5.0 percentage point, relative bias 1.79). Conclusions: VE estimates can be substantially biased with modest non-consent percentages for registration of vaccination. Data on covariate specific non-consent percentages should be available to correct this bias.