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Epidemic spreading in populations of mobile agents with adaptive behavioral response

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Author(s):
Ventura, Paulo Cesar ; Aleta, Alberto ; Rodrigues, Francisco A. ; Moreno, Yamir
Total Authors: 4
Document type: Journal article
Source: CHAOS SOLITONS & FRACTALS; v. 156, p. 10-pg., 2022-03-01.
Abstract

A B S T R A C T Despite the advanced stage of epidemic modeling, there is a major demand for methods to incorpo-rate behavioral responses to the spread of a disease, such as social distancing and adoption of preven-tion methods. Mobility plays an important role on epidemic dynamics and is also affected by behavioral changes, but there are many situations in which real mobility data is incomplete or inaccessible. We present a model for epidemic spreading in temporal networks of mobile agents that incorporates local behavioral responses. Susceptible agents are allowed to move towards the opposite direction of infected agents in their neighborhood. We show that this mechanism considerably decreases the stationary preva-lence when the spatial density of agents is low. However, for higher densities, the mechanism causes an abrupt phase transition, where a new bistable phase appears. We develop a semi-analytic approach for the case when the mobility is fast compared to the disease dynamics, and use it to argue that the bistability is caused by the emergence of spatial clusters of susceptible agents. Finally, we characterize the temporal networks formed in the fast mobility regime, showing how the degree distributions and other metrics are affected by the behavioral mechanism. Our work incorporates results previously known from adaptive networks into population of mobile agents, which can be further developed to be used in mobility-driven models.(c) 2022 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 19/11183-5 - Single and coupled dynamics in multiplex populations
Grantee:Paulo Cesar Ventura da Silva
Support Opportunities: Scholarships abroad - Research Internship - Doctorate
FAPESP's process: 16/24555-0 - Propagation of information in multilayer networks
Grantee:Paulo Cesar Ventura da Silva
Support Opportunities: Scholarships in Brazil - Doctorate
FAPESP's process: 19/23293-0 - Prediction and inference in complex systems
Grantee:Francisco Aparecido Rodrigues
Support Opportunities: Regular Research Grants
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC