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Bayesian modelling of population trends in alcohol consumption provides empirically based country estimates for South Africa.

Annibale CoisRichard MatzopoulosVictoria Pillay-van WykDebbie Bradshaw
Published in: Population health metrics (2021)
The methodology provides a viable alternative to current approaches to reconcile survey estimates of individual alcohol consumption patterns with aggregate administrative data. It provides sex- and age-specific estimates of prevalence of drinkers and distribution of average daily consumption among drinkers in populations. Reliance on locally sourced data instead of global and regional trend estimates better reflects local nuances and is adaptable to the inclusion of additional data. This provides a powerful tool to monitor consumption, develop burden of disease estimates and inform and evaluate public health interventions.
Keyphrases
  • alcohol consumption
  • public health
  • electronic health record
  • south africa
  • big data
  • physical activity
  • risk factors
  • machine learning
  • data analysis
  • hepatitis c virus
  • hiv infected
  • men who have sex with men