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Deep Learning Study Finds Growing Global Rheumatoid Arthritis Burden and Local Hotspots

Researchers link the rise to population aging, smoking prevalence, uneven health infrastructure, delayed diagnoses, inequitable access to biologic therapies

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Overview

  • The study applied a novel transformer-based deep learning framework to GBD data from 953 global and local locations spanning 1980–2021 to map incidence, prevalence, mortality and DALYs
  • High and high-middle SDI countries shoulder a disproportionate share of the burden, with DALY-related inequality surging 62.6% from 1990 to 2021 and the widest gaps in Finland, Ireland and New Zealand
  • Subnational hotspots emerged in 2021, with West Berkshire in the UK showing the highest incidence rate and Zacatecas in Mexico recording the highest DALY rate
  • Forecasts to 2040 predict continued increases in low-middle SDI regions driven by aging and population growth, while high SDI areas may see modest DALY declines if early-diagnosis and treatment access are sustained
  • Policy simulations indicate that effective tobacco control could cut rheumatoid arthritis deaths by 16.8% and DALYs by 20.6% in regions with high smoking prevalence