Epidemic transmission on random mobile network with diverse infection periods

Li, Kezan; Yu, Hong; Zeng, Zhao-Rong; Ding, Yong; Ma, Zhongjun

doi:10.1016/j.cnsns.2014.07.016

Cited by 7 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In reality, individuals in a population often move around during the spread of infectious diseases, leading to structural changes of the underlying contact network that mimics the population [32,33]. Recently, the epidemic spreading on random walk networks [34,35,36,37,38,39,40,41] has been extensively investigated to understand the effects of individuals' motion on the epidemic dynamics. For instance, Frasca et al [35] proposed a dynamical network model with mobile individuals who are allowed to perform both local and long-distance motions.…”

Section: Introductionmentioning

confidence: 99%

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Peng

Zhang

Yang

et al. 2019

Communications in Nonlinear Science and Numerical Simulation

View full text Add to dashboard Cite

show abstract

Section: Introductionmentioning

confidence: 99%

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Peng

Zhang

Yang

et al. 2019

Communications in Nonlinear Science and Numerical Simulation

View full text Add to dashboard Cite

show abstract

“…In this case, contacts between susceptible and infectious individuals are caused by the movements of individuals. For this reason, epidemic models with explicit individual movement have * ichinose.genki@shizuoka.ac.jp; attracted much attention [5][6][7][8][9][10][11][12][13][14][15][16][17]. First, epidemic models with uncorrelated random walk have been considered [18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Reduced mobility of infected agents suppresses but lengthens disease in biased random walk

Ichinose,

Satotani,

Sayama

et al. 2018

Preprint

View full text Add to dashboard Cite

Various theoretical models have been proposed to understand the basic nature of epidemics. Recent studies focus on the effects of mobility to epidemic process. However, uncorrelated random walk is typically assumed as the type of movement. In our daily life, the movement of people sometimes tends to be limited to a certain direction, which can be described by biased random walk. Here, we developed an agent-based model of susceptible-infected-recovered (SIR) epidemic process in a 2D continuous space where agents tend to move in a certain direction in addition to random movement. Moreover, we mainly focus on the effect of the reduced mobility of infected agents. Our model assumes that, when people are infected, their movement activity is greatly reduced because they are physically weakened by the disease. By conducting extensive simulations, we found that when the movement of infected people is limited, the final epidemic size becomes small. However, that crucially depended on the movement type of agents. Furthermore, the reduced mobility of infected agents lengthened the duration of the epidemic because the infection progressed slowly.

show abstract

“…In fact, some recent study results indicate that the mobility of individuals can play a significant role in the epidemic spreading process. [11][12][13][14][15][16][17][18][19] For example, a dynamical network consisting of a time-evolving wiring of interactions among a group of random walkers is introduced to model the spread of an infectious disease in a population of mobile individuals in Ref. [20].…”

Section: Introductionmentioning

confidence: 99%

Epidemic spreading on random surfer networks with infected avoidance strategy

et al. 2016

View full text Add to dashboard Cite

In this paper, we study epidemic spreading on random surfer networks with infected avoidance (IA) strategy. In particular, we consider that susceptible individuals' moving direction angles are affected by the current location information received from infected individuals through a directed information network. The model is mainly analyzed by discrete-time numerical simulations. The results indicate that the IA strategy can restrain epidemic spreading effectively. However, when long-distance jumps of individuals exist, the IA strategy's effectiveness on restraining epidemic spreading is heavily reduced. Finally, it is found that the influence of the noises from information transferring process on epidemic spreading is indistinctive.

show abstract

Epidemic transmission on random mobile network with diverse infection periods

Cited by 7 publications

References 22 publications

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

An SIS epidemic model with vaccination in a dynamical contact network of mobile individuals with heterogeneous spatial constraints

Reduced mobility of infected agents suppresses but lengthens disease in biased random walk

Epidemic spreading on random surfer networks with infected avoidance strategy

Contact Info

Product

Resources

About