Contact switching as a control strategy for epidemic outbreaks.

We study the effects of switching social contacts as a strategy to control epidemic outbreaks. Connections between susceptible and infective individuals can be broken by either individual, and then reconnected to a randomly chosen member of the population. It is assumed that the reconnecting individual has no previous information on the epidemiological condition of the new contact. We show that reconnection can completely suppress the disease, both by continuous and discontinuous transitions between the endemic and the infection-free states. For diseases with an asymptomatic phase, we analyze the conditions for the suppression of the disease, and show that-even when these conditions are not met-the increase of the endemic infection level is usually rather small. We conclude that, within some simple epidemiological models, contact switching is a quite robust and effective control strategy. This suggests that it may also be an efficient method in more complex situations.

[1]  A. J. Hall Infectious diseases of humans: R. M. Anderson & R. M. May. Oxford etc.: Oxford University Press, 1991. viii + 757 pp. Price £50. ISBN 0-19-854599-1 , 1992 .

[2]  Alessandro Vespignani,et al.  Epidemic spreading in scale-free networks. , 2000, Physical review letters.

[3]  S. Galea,et al.  SARS Control and Psychological Effects of Quarantine, Toronto, Canada , 2004, Emerging infectious diseases.

[4]  R. Bayer,et al.  HIV prevention and the two faces of partner notification. , 1992, American journal of public health.

[5]  R. Durrett,et al.  From individuals to epidemics. , 1996, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[6]  M. Kretzschmar,et al.  Modeling prevention strategies for gonorrhea and Chlamydia using stochastic network simulations. , 1996, American journal of epidemiology.

[7]  Thilo Gross,et al.  Epidemic dynamics on an adaptive network. , 2005, Physical review letters.

[8]  Thilo Gross,et al.  Robust oscillations in SIS epidemics on adaptive networks: Coarse graining by automated moment closure , 2008 .

[9]  C. Fraser,et al.  Factors that make an infectious disease outbreak controllable. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Tim S. Evans,et al.  Exact solutions for network rewiring models , 2007 .

[11]  D. Zanette,et al.  Infection Spreading in a Population with Evolving Contacts , 2007, Journal of biological physics.

[12]  A. Ghani,et al.  The Role of Sexual Partnership Networks in the Epidemiology of Gonorrhea , 1997, Sexually transmitted diseases.

[13]  H. Hull,et al.  SARS Control and Psychological Effects of Quarantine, Toronto, Canada , 2005, Emerging infectious diseases.

[14]  N. Peyrard,et al.  Cluster variation approximations for a contact process living on a graph , 2005 .

[15]  P. E. Kopp,et al.  Superspreading and the effect of individual variation on disease emergence , 2005, Nature.

[16]  M. Keeling,et al.  Networks and epidemic models , 2005, Journal of The Royal Society Interface.

[17]  W John Edmunds,et al.  Developing a realistic sexual network model of chlamydia transmission in Britain , 2006, Theoretical Biology and Medical Modelling.

[18]  Thilo Gross,et al.  Adaptive coevolutionary networks: a review , 2007, Journal of The Royal Society Interface.