Infectious Disease Modeling of Social Contagion in Networks

被引:160
|
作者
Hill, Alison L. [1 ,2 ,3 ]
Rand, David G. [1 ,4 ,5 ]
Nowak, Martin A. [1 ,6 ,7 ]
Christakis, Nicholas A. [8 ,9 ,10 ]
机构
[1] Harvard Univ, Program Evolutionary Dynam, Cambridge, MA 02138 USA
[2] Harvard Univ, Biophys Program, Cambridge, MA 02138 USA
[3] Harvard Univ, Harvard MIT Div Hlth Sci & Technol, Cambridge, MA 02138 USA
[4] Harvard Univ, Dept Psychol, Cambridge, MA 02138 USA
[5] Harvard Univ, Berkman Ctr Internet & Soc, Cambridge, MA 02138 USA
[6] Harvard Univ, Dept Math, Cambridge, MA 02138 USA
[7] Harvard Univ, Dept Organism & Evolutionary Biol, Cambridge, MA 02138 USA
[8] Harvard Univ, Sch Med, Dept Med, Boston, MA USA
[9] Harvard Univ, Sch Med, Dept Hlth Care Policy, Boston, MA 02115 USA
[10] Harvard Univ, Dept Sociol, Cambridge, MA 02138 USA
基金
美国国家科学基金会; 加拿大自然科学与工程研究理事会;
关键词
SPREAD; OBESITY; DIFFUSION; EVOLUTION; CASCADES; BEHAVIOR; SMOKING;
D O I
10.1371/journal.pcbi.1000968
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Many behavioral phenomena have been found to spread interpersonally through social networks, in a manner similar to infectious diseases. An important difference between social contagion and traditional infectious diseases, however, is that behavioral phenomena can be acquired by non-social mechanisms as well as through social transmission. We introduce a novel theoretical framework for studying these phenomena (the SISa model) by adapting a classic disease model to include the possibility for 'automatic' (or 'spontaneous') non-social infection. We provide an example of the use of this framework by examining the spread of obesity in the Framingham Heart Study Network. The interaction assumptions of the model are validated using longitudinal network transmission data. We find that the current rate of becoming obese is 2% per year and increases by 0.5percentage points for each obese social contact. The rate of recovering from obesity is 4% per year, and does not depend on the number of non-obese contacts. The model predicts a long-term obesity prevalence of approximately 42%, and can be used to evaluate the effect of different interventions on steady-state obesity. Model predictions quantitatively reproduce the actual historical time course for the prevalence of obesity. We find that since the 1970s, the rate of recovery from obesity has remained relatively constant, while the rates of both spontaneous infection and transmission have steadily increased over time. This suggests that the obesity epidemic may be driven by increasing rates of becoming obese, both spontaneously and transmissively, rather than by decreasing rates of losing weight. A key feature of the SISa model is its ability to characterize the relative importance of social transmission by quantitatively comparing rates of spontaneous versus contagious infection. It provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviors, health states, ideas or diseases with reservoirs.
引用
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页数:15
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