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Efficiency of quarantine and self-protection processes in epidemic spreading control on scale-free networks
- Source :
- Chaos (Woodbury, N.Y.). 28(1)
- Publication Year :
- 2018
-
Abstract
- One of the most effective mechanisms to contain the spread of an infectious disease through a population is the implementation of quarantine policies. However, its efficiency is affected by different aspects, for example, the structure of the underlining social network where highly connected individuals are more likely to become infected; therefore, the speed of the transmission of the decease is directly determined by the degree distribution of the network. Another aspect that influences the effectiveness of the quarantine is the self-protection processes of the individuals in the population, that is, they try to avoid contact with potentially infected individuals. In this paper, we investigate the efficiency of quarantine and self-protection processes in preventing the spreading of infectious diseases over complex networks with a power-law degree distribution [ P(k)∼k-ν] for different ν values. We propose two alternative scale-free models that result in power-law degree distributions above and below the exponent ν = 3 associated with the conventional Barabasi-Albert model. Our results show that the exponent ν determines the effectiveness of these policies in controlling the spreading process. More precisely, we show that for the ν exponent below three, the quarantine mechanism loses effectiveness. However, the efficiency is improved if the quarantine is jointly implemented with a self-protection process driving the number of infected individuals significantly lower.
- Subjects :
- Computer science
Population
General Physics and Astronomy
01 natural sciences
Communicable Diseases
Models, Biological
010305 fluids & plasmas
law.invention
law
0103 physical sciences
Quarantine
Econometrics
Humans
Computer Simulation
010306 general physics
education
Epidemics
Mathematical Physics
education.field_of_study
Applied Mathematics
Scale-free network
Self protection
Statistical and Nonlinear Physics
Numerical Analysis, Computer-Assisted
Complex network
Degree distribution
Communicable disease transmission
Exponent
Subjects
Details
- ISSN :
- 10897682
- Volume :
- 28
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Chaos (Woodbury, N.Y.)
- Accession number :
- edsair.doi.dedup.....296a73e9631903b975752a6ae5200882