How to distribute antidote to control epidemics
Identifieur interne : 001B76 ( Istex/Corpus ); précédent : 001B75; suivant : 001B77How to distribute antidote to control epidemics
Auteurs : Christian Borgs ; Jennifer Chayes ; Ayalvadi Ganesh ; Amin SaberiSource :
- Random Structures & Algorithms [ 1042-9832 ] ; 2010-09.
English descriptors
- Teeft :
- Algorithm, Amin saberi, Antidote, Average degree, Borgs, Constant factor, Constant infection rate, Contact process, Control epidemics, Cure rate, Cure rates, Current state, Discrete time chain, Epidemic, Epidemic threshold, Epidemic thresholds, Epidemiological networks, General graph, Healthy center, High probability, Infection, Initial condition, Inoculation scheme, Last step, Lemma, Long list, Long time, Microsoft research, Mutating viruses, Next lemma, Next theorem, Nite, Nite graph, Node, Normalization condition, Original chain, Other hand, Other words, Poisson clocks, Positive probability, Quadratic equation, Random structures, Random variables, Right hand side, Rigorous analysis, Single phase, Social networks, Standard contact process, Star graph, State transitions, Stochastic processes, Survival time, Technological networks, Total amount, Wiley periodicals, Worm.
Abstract
We give a rigorous analysis of variations of the contact process on a finite graph in which the cure rate is allowed to vary from one vertex to the next, and even to depend on the current state of the system. In particular, we study the epidemic threshold in the models where the cure rate is proportional to the degree of the node or when it is proportional to the number of its infected neighbors. © 2010 Wiley Periodicals, Inc. Random Struct. Alg., 2010
Url:
DOI: 10.1002/rsa.20315
Links to Exploration step
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<titleGroup><title type="main" xml:lang="en">How to distribute antidote to control epidemics</title>
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<p>We give a rigorous analysis of variations of the contact process on a finite graph in which the cure rate is allowed to vary from one vertex to the next, and even to depend on the current state of the system. In particular, we study the epidemic threshold in the models where the cure rate is proportional to the degree of the node or when it is proportional to the number of its infected neighbors. © 2010 Wiley Periodicals, Inc. Random Struct. Alg., 2010</p>
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