Optimizing hybrid spreading in metapopulations.
Epidemic spreading phenomena are ubiquitous in nature and society. Examples include the spreading of diseases, information, and computer viruses. Epidemics can spread by local spreading, where infected nodes can only infect a limited set of direct target nodes and global spreading, where an infected node can infect every other node. In reality, many epidemics spread using a hybrid mixture of both types of spreading. In this study we develop a theoretical framework for studying hybrid epidemics, and examine the optimum balance between spreading mechanisms in terms of achieving the maximum outbreak size. We show the existence of critically hybrid epidemics where neither spreading mechanism alone can cause a noticeable spread but a combination of the two spreading mechanisms would produce an enormous outbreak. Our results provide new strategies for maximising beneficial epidemics and estimating the worst outcome of damaging hybrid epidemics.
1] Department of Computer Science, University College London, UK [2] Security Science Doctoral Research Training Centre, University College London, UK [3] School of Computer Science, National University of Defense Technology, Changsha, China.
Changwang
C
Zhang
Department of Computer Science, University College London, UK.
Shi
S
Zhou
1] School of Mathematical Sciences, Monash University, Melbourne, Victoria, Australia [2] School of Biological Sciences, Monash University, Melbourne, Victoria, Australia [3] Monash Academy for Cross &Interdisciplinary Mathematics, Monash University, Melbourne, Victoria, Australia.
Joel C
JC
Miller
1] Department of Computer Science, University of Copenhagen, Denmark [2] Department of Computer Science, University College London, UK.
Ingemar J
IJ
Cox
Division of Infection and Immunity, University College London, UK.
Benjamin M
BM
Chain
D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission*; D004196:Disease Outbreaks; D018562:Disease Transmission, Infectious; D058872:Epidemics; D006801:Humans; D008962:Models, Theoretical