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Simulating network intervention strategies: Implications for adoption of behaviour

Published online by Cambridge University Press:  16 May 2018

JENNIFER BADHAM Open the ORCID record for JENNIFER BADHAM [Opens in a new window] ,
FRANK KEE  and
RUTH F. HUNTER
JENNIFER BADHAM
Affiliation:
UKCRC Centre of Excellence (Northern Ireland), Queens University Belfast, University Rd, Belfast BT7 1NN, United Kingdom (e-mail: research@criticalconnections.com.au, f.kee@qub.ac.uk, ruth.hunter@qub.ac.uk)
FRANK KEE
Affiliation:
UKCRC Centre of Excellence (Northern Ireland), Queens University Belfast, University Rd, Belfast BT7 1NN, United Kingdom (e-mail: research@criticalconnections.com.au, f.kee@qub.ac.uk, ruth.hunter@qub.ac.uk)
RUTH F. HUNTER
Affiliation:
UKCRC Centre of Excellence (Northern Ireland), Queens University Belfast, University Rd, Belfast BT7 1NN, United Kingdom (e-mail: research@criticalconnections.com.au, f.kee@qub.ac.uk, ruth.hunter@qub.ac.uk)
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Abstract

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This study uses simulation over real and artificial networks to compare the eventual adoption outcomes of network interventions, operationalized as idealized contagion processes with different sets of seeds. While the performance depends on the details of both the network and behaviour adoption mechanisms, 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 behavior interventions.

Keywords

social contagionnetwork interventionssimulation

Information

Type
Research Article
Information
Network Science , Volume 6 , Issue 2 , June 2018 , pp. 265 - 280
Copyright
Copyright © Cambridge University Press 2018 

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