From susceptibility to frailty in social networks: The case of obesity

IF 1.4 3区社会学 Q3 DEMOGRAPHY

Mathematical Population Studies Pub Date : 2017-10-02 DOI:10.1080/08898480.2017.1348718

J. Demongeot, M. Jelassi, C. Taramasco

引用次数: 9

Abstract

ABSTRACT The obesity pandemic is represented by a discrete-time Hopfield Boolean network embedded in continuous-time population dynamics. The influence of the social environment passes through a system of differential equations, whereby obesity spreads by imitation of the most influential neighbors, those who have the highest centrality indices in the network. This property is called “homophily.” Susceptibility and frailty are redefined using network properties. Projections of the spread of obesity are validated on data collected in a French high school.

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从社会网络的易感性到脆弱性:以肥胖为例

摘要肥胖流行病由嵌入连续时间人口动力学中的离散时间Hopfield布尔网络表示。社会环境的影响通过一个微分方程系统，肥胖通过模仿最有影响力的邻居传播，这些邻居在网络中具有最高的中心性指数。这种特性被称为“同质性”。易感性和脆弱性是使用网络特性重新定义的。根据法国一所高中收集的数据，对肥胖传播的预测得到了验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Mathematical Population Studies 数学-数学跨学科应用

CiteScore

3.20

自引率

11.10%

发文量

审稿时长

>12 weeks

期刊介绍： Mathematical Population Studies publishes carefully selected research papers in the mathematical and statistical study of populations. The journal is strongly interdisciplinary and invites contributions by mathematicians, demographers, (bio)statisticians, sociologists, economists, biologists, epidemiologists, actuaries, geographers, and others who are interested in the mathematical formulation of population-related questions. The scope covers both theoretical and empirical work. Manuscripts should be sent to Manuscript central for review. The editor-in-chief has final say on the suitability for publication.