Social Network Analysis of a Disaster Behavior Network: An Agent-Based Modeling Approach

Author(s):  
Rey C. Rodrigueza ◽  
Maria Regina Justina E. Estuar
2012 ◽  
Vol 9 (1) ◽  
pp. 1 ◽  
Author(s):  
Abdulrahman M El-Sayed ◽  
Peter Scarborough ◽  
Lars Seemann ◽  
Sandro Galea

2010 ◽  
Vol 31 (9) ◽  
pp. 893-900 ◽  
Author(s):  
Philip M. Polgreen ◽  
Troy Leo Tassier ◽  
Sriram Venkata Pemmaraju ◽  
Alberto Maria Segre

Objective.To use social network analysis to design more effective strategies for vaccinating healthcare workers against influenza.Design.An agent-based simulation.Setting.A simulation based on a 700-bed hospital.Methods.We first observed human contacts (defined as approach within approximately 0.9 m) performed by 15 categories of healthcare workers (eg, floor nurses, intensive care unit nurses, staff physicians, phlebotomists, and respiratory therapists). We then constructed a series of contact graphs to represent the social network of the hospital and used these graphs to run agent-based simulations to model the spread of influenza. A targeted vaccination strategy that preferentially vaccinated more “connected” healthcare workers was compared with other vaccination strategies during simulations with various base vaccination rates, vaccine effectiveness, probability of transmission, duration of infection, and patient length of stay.Results.We recorded 6,654 contacts by 148 workers during 606 hours of observations from January through December 2006. Unit clerks, X-ray technicians, residents and fellows, transporters, and physical and occupational therapists had the most contacts. When repeated contacts with the same individual were excluded, transporters, unit clerks, X-ray technicians, physical and occupational therapists, and social workers had the most contacts. Preferentially vaccinating healthcare workers in more connected job categories yielded a substantially lower attack rate and fewer infections than a random vaccination strategy for all simulation parameters.Conclusions.Social network models can be used to derive more effective vaccination policies, which are crucial during vaccine shortages or in facilities with low vaccination rates. Local vaccination priorities can be determined in any healthcare facility with only a modest investment in collection of observational data on different types of healthcare workers. Our findings and methods (ie, social network analysis and computational simulation) have implications for the design of effective interventions to control a broad range of healthcare-associated infections.


2009 ◽  
Vol 6 (41) ◽  
pp. 1103-1119 ◽  
Author(s):  
Lucy Asher ◽  
Lisa M. Collins ◽  
Angel Ortiz-Pelaez ◽  
Julian A. Drewe ◽  
Christine J. Nicol ◽  
...  

While the incorporation of mathematical and engineering methods has greatly advanced in other areas of the life sciences, they have been under-utilized in the field of animal welfare. Exceptions are beginning to emerge and share a common motivation to quantify ‘hidden’ aspects in the structure of the behaviour of an individual, or group of animals. Such analyses have the potential to quantify behavioural markers of pain and stress and quantify abnormal behaviour objectively. This review seeks to explore the scope of such analytical methods as behavioural indicators of welfare. We outline four classes of analyses that can be used to quantify aspects of behavioural organization. The underlying principles, possible applications and limitations are described for: fractal analysis, temporal methods, social network analysis, and agent-based modelling and simulation. We hope to encourage further application of analyses of behavioural organization by highlighting potential applications in the assessment of animal welfare, and increasing awareness of the scope for the development of new mathematical methods in this area.


2016 ◽  
Vol 7 ◽  
Author(s):  
Alistair M. Senior ◽  
Mathieu Lihoreau ◽  
Jerome Buhl ◽  
David Raubenheimer ◽  
Stephen J. Simpson

Sign in / Sign up

Export Citation Format

Share Document