Epidemiological modelling of the 2005 French riots: a spreading wave and the role of contagion

Bonnasse‐Gahot, Laurent; Berestycki, Henri; Depuiset, Marie Aude; Gordon, Mirta B.; Oberwittler, Dietrich; Rodríguez, Nancy; Nadal, Jean-Pierre

doi:10.1038/s41598-017-18093-4

Cited by 74 publications

(88 citation statements)

References 48 publications

(87 reference statements)

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“…Beyond psychology, many authors have noted that riots often occur in temporal and spatial clusters (e.g., Bohstedt & Williams, 1988;Bonnasse-Gahot et al, 2018;Charlesworth, 1983). This clustering has been taken to indicate so-called "contagion" or interdependence-that is, that riots in one location influence the occurrence of riots in other locations (e.g., National Advisory Commission on Civil Disorders, 1968).…”

Section: Introductionmentioning

confidence: 99%

A social identity model of riot diffusion: From injustice to empowerment in the 2011 London riots

Drury

Stott

Ball

et al. 2020

Euro J Social Psych

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Previous research has shown that riots spread across multiple locations, but has not explained underlying psychological processes. We examined rioting in three locations during the August 2011 disorders in England to test a social identity model of riot diffusion. We triangulated multiple sources to construct a narrative of events; and we analysed interviews with 68 participants to examine experiences. In line with the model, we found evidence for two pathways of influence: “cognitive” and “strategic”. For some participants, previous rioting was highly self‐relevant, and shared identity was the basis of their subsequent involvement. For others, previous rioting was empowering because it demonstrated the vulnerability of a common enemy (the police). In each location, interaction dynamics mediated the link between initial perceptions and collective action. The utility of this social identity approach is that it is able to account for both the boundaries and the sequence of urban riot diffusion.

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Section: Introductionmentioning

confidence: 99%

A social identity model of riot diffusion: From injustice to empowerment in the 2011 London riots

Drury

Stott

Ball

et al. 2020

Euro J Social Psych

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“…Moreover, sinceB has a zero at every entry where B has a zero, it follows that P SB p I = 0 on L. This in turn implies Comprom. 6 Mixed that the p I dynamics on L are given by the network SIS dynamics (7). Since solutions of (7) either converge to the IFE point p I * = 0 or to the EE (5) as t → ∞ [14], it follows that every invariant set of L consists only of equilibria of (3) (see Remark 1).…”

Section: A the ω-Limit Set Of Solutionsmentioning

confidence: 99%

Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks

Pagliara

Leonard

2021

IEEE Trans. Automat. Contr.

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Contagious processes, such as spread of infectious diseases, social behaviors, or computer viruses, affect biological, social, and technological systems. Epidemic models for large populations and finite populations on networks have been used to understand and control both transient and steady-state behaviors. Typically it is assumed that after recovery from an infection, every agent will either return to its original susceptible state or acquire full immunity to reinfection. We study the network SIRI (Susceptible-Infected-Recovered-Infected) model, an epidemic model for the spread of contagious processes on a network of heterogeneous agents that can adapt their susceptibility to reinfection. The model generalizes existing models to accommodate realistic conditions in which agents acquire partial or compromised immunity after first exposure to an infection. We prove necessary and sufficient conditions on model parameters and network structure that distinguish four dynamic regimes: infection-free, epidemic, endemic, and bistable. For the bistable regime, which is not accounted for in traditional models, we show how there can be a rapid resurgent epidemic after what looks like convergence to an infection-free population. We use the model and its predictive capability to show how control strategies can be designed to mitigate problematic contagious behaviors.

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“…In the context of corporate competition, spatial network analysis was utilized to show [26] that the spatial locations of firms are positively correlated with the population density, and that firm competition networks are governed by cumulative advantage rules and geographic distance (which is equivalent to the BLV). In the contexts of civil unrest and riots [25,27], it has been shown, both theoretically and empirically that social unrest dynamics is based on the hypothesis that widespread unrest arises from internal processes of positive feedback and cascading effects in the form of contagion and social diffusion over spatially interdependent regions connected through social and mass communication networks. So that social instability can be considered as a spatial epidemics phenomenon, similar to other spatially extended dynamical systems in the physical and biological sciences, such as earthquakes, forest fires, and epidemics.…”

Section: Literature Reviewmentioning

confidence: 99%

Gang confrontation: The case of Medellin (Colombia)

Botero¹,

Guo²,

Mosquera³

et al. 2019

PLoS ONE

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Protracted conflict is one of the largest human challenges that have persistently undermined economic and social progress. In recent years, there has been increased emphasis on using statistical and physical science models to better understand both the universal patterns and the underlying mechanics of conflict. Whilst macroscopic power-law fractal patterns have been shown for death-toll in wars and self-excitation models have been shown for roadside ambush attacks, very few works deal with the challenge of complex dynamics between gangs at the intra-city scale. Here, based on contributions to the historical memory of the conflict in Colombia, Medellin’s gang-confrontation-network is presented. It is shown that socio-economic and violence indexes are moderate to highly correlated to the structure of the network. Specifically, the death-toll of conflict is strongly influenced by the leading eigenvalues of the gangs’ conflict adjacency matrix, which serves a proxy for unstable self-excitation from revenge attacks. The distribution of links based on the geographic distance between gangs in confrontation leads to the confirmation that territorial control is a main catalyst of violence and retaliation among gangs. As a first attempt to explore the time evolution of the confrontation network, the Boltzmann-Lotka-Volterra (BLV) dynamic interaction network analysis is applied to quantify the spatial embeddedness of the dynamic relationship between conflicting gangs in Medellin. However, the non-stationary character of the violence in Medellin during the observation period restricts the application of the BLV model and results suggest that more involved and comprehensive models are needed to described the dynamics of Medellin’s armed conflict.

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Epidemiological modelling of the 2005 French riots: a spreading wave and the role of contagion

Cited by 74 publications

References 48 publications

A social identity model of riot diffusion: From injustice to empowerment in the 2011 London riots

A social identity model of riot diffusion: From injustice to empowerment in the 2011 London riots

Adaptive Susceptibility and Heterogeneity in Contagion Models on Networks

Gang confrontation: The case of Medellin (Colombia)

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