Time for a Drink? A Mathematical Model of Non-human Primate Alcohol Consumption

Sharon Moore, Ami Radunskaya, Elizabeth Zollinger, Kathleen A. Grant, Steven Gonzales, Erich J. Baker

    Research output: Contribution to journalArticle


    We simulate a non-human primate's alcohol drinking pattern in order to better understand temporal patterning of alcoholic drinks that can lead to the excessive intakes associated with alcohol use disorder. A stochastic mathematical model of alcohol consumption pattern is developed, where model parameters are calibrated to an individual monkey's drinking history. The model predicts a time series that simulates a monkey's alcohol intake in time, and we analyze this drinking pattern to understand the variations in day and night drinking, the lengths of drinks (intake in 5 or more consecutive secs), and lengths of bouts (1 or more drinks per 5 min occasion). This time series can predict a lifetime categorical drinking level (light, binge, heavy, or very heavy), thus correlating an individual monkey's parameters with distinct long term drinking classifications.

    Original languageEnglish (US)
    Article number6
    JournalFrontiers in Applied Mathematics and Statistics
    StatePublished - Feb 22 2019


    • Markov process
    • alcohol consumption
    • drinking classification
    • mathematical model
    • model fitting
    • stochastic

    ASJC Scopus subject areas

    • Applied Mathematics
    • Statistics and Probability

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