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Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland

Author

Listed:
  • Tuomo Hartonen

    (University of Helsinki)

  • Bradley Jermy

    (University of Helsinki)

  • Hanna Sõnajalg

    (University of Tartu)

  • Pekka Vartiainen

    (University of Helsinki)

  • Kristi Krebs

    (University of Tartu)

  • Andrius Vabalas

    (University of Helsinki)

  • Tuija Leino

    (Finnish Institute for Health and Welfare)

  • Hanna Nohynek

    (Finnish Institute for Health and Welfare)

  • Jonas Sivelä

    (Finnish Institute for Health and Welfare)

  • Reedik Mägi

    (University of Tartu)

  • Mark Daly

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Harvard Medical School)

  • Hanna M. Ollila

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Harvard Medical School
    Massachusetts General Hospital and Harvard Medical School)

  • Lili Milani

    (University of Tartu)

  • Markus Perola

    (Finnish Institute for Health and Welfare)

  • Samuli Ripatti

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    University of Helsinki)

  • Andrea Ganna

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

Abstract

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.

Suggested Citation

  • Tuomo Hartonen & Bradley Jermy & Hanna Sõnajalg & Pekka Vartiainen & Kristi Krebs & Andrius Vabalas & Tuija Leino & Hanna Nohynek & Jonas Sivelä & Reedik Mägi & Mark Daly & Hanna M. Ollila & Lili Mila, 2023. "Nationwide health, socio-economic and genetic predictors of COVID-19 vaccination status in Finland," Nature Human Behaviour, Nature, vol. 7(7), pages 1069-1083, July.
    • Handle: RePEc:nat:nathum:v:7:y:2023:i:7:d:10.1038_s41562-023-01591-z
    DOI: 10.1038/s41562-023-01591-z
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    References listed on IDEAS

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    2. Mattia Cordioli & Andrea Corbetta & Hanna Maria Kariis & Sakari Jukarainen & Pekka Vartiainen & Tuomo Kiiskinen & Matteo Ferro & Markus Perola & Mikko Niemi & Samuli Ripatti & Kelli Lehto & Lili Milan, 2024. "Socio-demographic and genetic risk factors for drug adherence and persistence across 5 common medication classes," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

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