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Modeling the evolution of drinking behavior: A Statistical Physics perspective

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  • Crokidakis, Nuno
  • Sigaud, Lucas

Abstract

In this work we study a simple compartmental model for drinking behavior evolution. The population is divided in 3 compartments regarding their alcohol consumption, namely Susceptible individuals S (nonconsumers), Moderate drinkers M and Risk drinkers R. The transitions among those states are ruled by probabilities. Despite the simplicity of the model, we observed the occurrence of two distinct nonequilibrium phase transitions to absorbing states. One of these states is composed only by Susceptible individuals S, with no drinkers (M=R=0). On the other hand, the other absorbing state is composed only by Risk drinkers R (S=M=0). Between these two steady states, we have the coexistence of the three subpopulations S, M and R. Comparison with abusive alcohol consumption data for Brazil shows a good agreement between the model’s results and the database.

Suggested Citation

  • Crokidakis, Nuno & Sigaud, Lucas, 2021. "Modeling the evolution of drinking behavior: A Statistical Physics perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    • Handle: RePEc:eee:phsmap:v:570:y:2021:i:c:s0378437121000868
    DOI: 10.1016/j.physa.2021.125814
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    References listed on IDEAS

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    1. Bouchaib Khajji & Abderrahim Labzai & Abdelfatah Kouidere & Omar Balatif & Mostafa Rachik, 2020. "A Discrete Mathematical Modeling of the Influence of Alcohol Treatment Centers on the Drinking Dynamics Using Optimal Control," Journal of Applied Mathematics, Hindawi, vol. 2020, pages 1-13, February.
    2. Galam, Serge & Jacobs, Frans, 2007. "The role of inflexible minorities in the breaking of democratic opinion dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 381(C), pages 366-376.
    3. Hai-Feng Huo & Na-Na Song, 2012. "Global Stability for a Binge Drinking Model with Two Stages," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-15, November.
    4. F. W. S. Lima & Tarik Hadzibeganovic & Dietrich Stauffer, 2014. "Evolution of tag-based cooperation on Erdős–Rényi random graphs," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 25(06), pages 1-10.
    5. Xun-Yang Wang & Hai-Feng Huo & Qing-Kai Kong & Wei-Xuan Shi, 2014. "Optimal Control Strategies in an Alcoholism Model," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-18, March.
    6. D. Stauffer & M. Sahimi, 2007. "Can a few fanatics influence the opinion of a large segment of a society?," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 57(2), pages 147-152, May.
    7. Gorman, D.M. & Mezic, J. & Mezic, I. & Gruenewald, P.J., 2006. "Agent-based modeling of drinking behavior: A preliminary model and potential applications to theory and practice," American Journal of Public Health, American Public Health Association, vol. 96(11), pages 2055-2060.
    8. Nizamani, Sarwat & Memon, Nasrullah & Galam, Serge, 2014. "From public outrage to the burst of public violence: An epidemic-like model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 620-630.
    9. Rafael M. Brum & Nuno Crokidakis, 2017. "Dynamics of tax evasion through an epidemic-like model," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 28(02), pages 1-14, February.
    10. Shuang-Hong Ma & Hai-Feng Huo & Xin-You Meng, 2015. "Modelling Alcoholism as a Contagious Disease: A Mathematical Model with Awareness Programs and Time Delay," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-13, October.
    11. Serge Galam & Marco Alberto Javarone, 2016. "Modeling Radicalization Phenomena in Heterogeneous Populations," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-15, May.
    12. Nuno Crokidakis & Jorge S. Sá Martins, 2018. "Can honesty survive in a corrupt parliament?," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 29(10), pages 1-10, October.
    13. Crokidakis, Nuno, 2020. "COVID-19 spreading in Rio de Janeiro, Brazil: Do the policies of social isolation really work?," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    14. Huo, Hai-Feng & Xue, Hui-Ning & Xiang, Hong, 2018. "Dynamics of an alcoholism model on complex networks with community structure and voluntary drinking," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 880-890.
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