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

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 Milani, Markus Perola, Samuli Ripatti and Andrea Ganna ()
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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
Hanna M. Ollila: University of Helsinki
Lili Milani: University of Tartu
Markus Perola: Finnish Institute for Health and Welfare
Samuli Ripatti: University of Helsinki
Andrea Ganna: University of Helsinki

Nature Human Behaviour, 2023, vol. 7, issue 7, 1069-1083

Abstract: 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.

Date: 2023
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DOI: 10.1038/s41562-023-01591-z

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