Literature DB >> 15588638

A generalized model of social and biological contagion.

P S Dodds1, D J Watts.   

Abstract

We present a model of contagion that unifies and generalizes existing models of the spread of social influences and microorganismal infections. Our model incorporates individual memory of exposure to a contagious entity (e.g. a rumor or disease), variable magnitudes of exposure (dose sizes), and heterogeneity in the susceptibility of individuals. Through analysis and simulation, we examine in detail the case where individuals may recover from an infection and then immediately become susceptible again (analogous to the so-called SIS model). We identify three basic classes of contagion models which we call epidemic threshold, vanishing critical mass, and critical mass classes, where each class of models corresponds to different strategies for prevention or facilitation. We find that the conditions for a particular contagion model to belong to one of the these three classes depend only on memory length and the probabilities of being infected by one and two exposures, respectively. These parameters are in principle measurable for real contagious influences or entities, thus yielding empirical implications for our model. We also study the case where individuals attain permanent immunity once recovered, finding that epidemics inevitably die out but may be surprisingly persistent when individuals possess memory.

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Year:  2005        PMID: 15588638     DOI: 10.1016/j.jtbi.2004.09.006

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  38 in total

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2.  Modelling behavioural contagion.

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3.  Complex dynamics of synergistic coinfections on realistically clustered networks.

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4.  Inhibiting diffusion of complex contagions in social networks: theoretical and experimental results.

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Journal:  Data Min Knowl Discov       Date:  2015-03       Impact factor: 3.670

5.  Conflict and convention in dynamic networks.

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Review 6.  Coevolution spreading in complex networks.

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Journal:  Phys Rep       Date:  2019-07-29       Impact factor: 25.600

7.  Connecting the invisible dots: reaching lesbian, gay, and bisexual adolescents and young adults at risk for suicide through online social networks.

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8.  Hierarchical effects facilitate spreading processes on synthetic and empirical multilayer networks.

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Journal:  PLoS One       Date:  2021-06-09       Impact factor: 3.240

9.  Modeling the adoption of innovations in the presence of geographic and media influences.

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Journal:  PLoS One       Date:  2012-01-19       Impact factor: 3.240

10.  Response thresholds alone cannot explain empirical patterns of division of labor in social insects.

Authors:  Yuko Ulrich; Mari Kawakatsu; Christopher K Tokita; Jonathan Saragosti; Vikram Chandra; Corina E Tarnita; Daniel J C Kronauer
Journal:  PLoS Biol       Date:  2021-06-17       Impact factor: 8.029

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