Stochastic simulation of HIV population dynamics through complex network modelling
We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and gi...
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Main Authors: | , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
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Online Access: | https://hdl.handle.net/10356/84333 http://hdl.handle.net/10220/10126 |
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Institution: | Nanyang Technological University |
Language: | English |