Literature DB >> 15697472

Controlling disease spread on networks with incomplete knowledge.

B Dybiec1, A Kleczkowski, C A Gilligan.   

Abstract

Models for control of highly infectious diseases on local, small-world, and scale-free networks are considered, with only partial information accessible about the status of individuals and their connections. We consider a case when individuals can be infectious before showing symptoms and thus before detection. For small to moderately severe incidence of infection with a small number of nonlocal links, it is possible to control disease spread by using purely local methods applied in a neighborhood centered around a detected infectious individual. There exists an optimal radius for such a control neighborhood leading to the lowest severity of the epidemic in terms of economic costs associated with disease and treatment. The efficiency of a local control strategy is very sensitive to the choice of the radius. Below the optimal radius, the local strategy is unsuccessful; the disease spreads throughout the system, necessitating treatment of the whole population. At the other extreme, a strategy involving a neighborhood that is too large controls the disease but is wasteful of resources. It is not possible to stop an epidemic on scale-free networks by preventive actions, unless a large proportion of the population is treated.

Entities:  

Year:  2004        PMID: 15697472     DOI: 10.1103/PhysRevE.70.066145

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  20 in total

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Journal:  J R Soc Interface       Date:  2010-07-28       Impact factor: 4.118

2.  Preventable H5N1 avian influenza epidemics in the British poultry industry network exhibit characteristic scales.

Authors:  A R T Jonkers; K J Sharkey; R M Christley
Journal:  J R Soc Interface       Date:  2009-10-14       Impact factor: 4.118

3.  Searching for the most cost-effective strategy for controlling epidemics spreading on regular and small-world networks.

Authors:  Adam Kleczkowski; Katarzyna Oleś; Ewa Gudowska-Nowak; Christopher A Gilligan
Journal:  J R Soc Interface       Date:  2011-06-08       Impact factor: 4.118

4.  Evidence-based controls for epidemics using spatio-temporal stochastic models in a Bayesian framework.

Authors:  Hola K Adrakey; George Streftaris; Nik J Cunniffe; Tim R Gottwald; Christopher A Gilligan; Gavin J Gibson
Journal:  J R Soc Interface       Date:  2017-11       Impact factor: 4.118

5.  Modelling control of epidemics spreading by long-range interactions.

Authors:  Bartłomiej Dybiec; Adam Kleczkowski; Christopher A Gilligan
Journal:  J R Soc Interface       Date:  2009-01-06       Impact factor: 4.118

6.  Optimizing the control of disease infestations at the landscape scale.

Authors:  Graeme A Forster; Christopher A Gilligan
Journal:  Proc Natl Acad Sci U S A       Date:  2007-03-13       Impact factor: 11.205

Review 7.  Sustainable agriculture and plant diseases: an epidemiological perspective.

Authors:  Christopher A Gilligan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-02-27       Impact factor: 6.237

8.  An epidemiological framework for modelling fungicide dynamics and control.

Authors:  Matthew D Castle; Christopher A Gilligan
Journal:  PLoS One       Date:  2012-08-10       Impact factor: 3.240

9.  Controlling epidemic spread by social distancing: do it well or not at all.

Authors:  Savi Maharaj; Adam Kleczkowski
Journal:  BMC Public Health       Date:  2012-08-20       Impact factor: 3.295

10.  Efficient control of epidemics spreading on networks: balance between treatment and recovery.

Authors:  Katarzyna Oleś; Ewa Gudowska-Nowak; Adam Kleczkowski
Journal:  PLoS One       Date:  2013-06-04       Impact factor: 3.240

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