Nationwide health, socio-economic and genetic predictors of Covid-19 vaccination status in Finland
Bibliographic Data
Understanding factors associated with COVID-19 vaccination can highlight issues in public health systems. Using machine learning, we considered the effects of 2,890 health, socio-economic and demographic factors in the entire Finnish population aged 30–80 and genome-wide information from 273,765 individuals. The strongest predictors of vaccination status were labour income and medication purchase history. Mental health conditions and having unvaccinated first-degree relatives were associated with reduced vaccination. A prediction model combining all predictors achieved good discrimination (area under the receiver operating characteristic curve, 0.801; 95% confidence interval, 0.799–0.803). The 1% of individuals with the highest predicted risk of not vaccinating had an observed vaccination rate of 18.8%, compared with 90.3% in the study population. We identified eight genetic loci associated with vaccination uptake and derived a polygenic score, which was a weak predictor in an independent subset. Our results suggest that individuals at higher risk of suffering the worst consequences of COVID-19 are also less likely to vaccinate
2019-20 coronavirus outbreak · Disease · Environmental health · Outbreak · Pathology · Sociology · Vaccination · Demography · Influenza Virus Research Studies · Medicine · SARS-CoV-2 and COVID-19 Research · Vaccine Coverage and Hesitancy · Virology
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| Unique citing works | 5 |
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| Citation types | Neutral: 5 |