This study uses simulation over real and artiﬁcial networks to compare the eventual adoption outcomes of network interventions, operationalised as idealised contagion processes with different sets of seeds. While the performance depends on the details of both the network and behaviour adoption mechanism, interventions with seeds that are central to the network are more effective than random selection in the majority of simulations, with faster or more complete adoption throughout the network. These results provide additional theoretical justiﬁcation for utilizing relevant network information in the design of public health behaviour interventions.
|Number of pages||16|
|Early online date||16 May 2018|
|Publication status||Published - Jun 2018|
- Network interventions
- agent-based modelling