BISoN: Biologically-Inspired Social Network Framework for Coordinated and Adaptive Emergency Response
Unfortunately, this opportunity is currently unavailable. Please check back at a later date.
Emergency preparedness and response coordination is a multi-organisational effort, where shared goals – warning, evacuation and recovery – are heavily interdependent. When an extreme event occurs, professionals from multiple organisations must respond to it by coordinating their respective knowledge, skills, and abilities to overcome problems generated by the crisis. This is a major challenge. A number of high-profile studies illustrate that coordination is often insufficient among responding government agencies, volunteers, businesses and humanitarian organisations Effective coordination of the emergency response effort depends strongly on the transfer, use, and quality of shared information about risks, vulnerabilities, and hazards among coordinating agencies. The traditional approaches to coordination were to delegate more authority to a single actor. The idea was to secure coordination by control from the top – a ‘coordination by command’ approach (Donini and Niland, 1994). This notion has been contentious mainly due to the difficulties of selecting a suitable governing body. Contemporary thinkers contend that it may be timely to consider whether an organisation should be reconceived as constituting a social network (Moore, Eng et al., 2003; Stephenson-Jr., 2004). A leading researcher in this field has argued that “coordination is multilayered, involving the orchestration of relationships not only at headquarters but also at the regional, national and field levels” (Minear, 2002). Hierarchical models of resource allocation and coordination emphasise the power and dependencies, which develop during inter-organisational transactions. Research within resource dependency has also argued that there is a positive association between organisations’ network centrality and their supposed influence in community affairs (Galaskiewicz, 1985).
It is no surprise that significant failures during recent high-profile crises have arisen from rapidly changing circumstances on the ground, and from the challenges of managing a dynamic situation across different response agencies that have distinct modes of operation. At the fundamental level, crisis response can be visualised as an interaction network with a flow of information between nodes, each representing an individual actor or agency. Observations of interaction networks in life, engineering, and the physical sciences suggest that the key functional properties of these networks are the flow of information they can support, the robustness of the flow to node failure, and the efficiency of the network (defined in terms of the time for information to pass between two points). Studies have shown that certain network designs perform better than others in each of these respects. This points to the premise that loosely knit collections of individuals constituting ad-hoc social networks have neither an overarching executive nor a hierarchical command and control structure tying them together. Rather, the connections among decision-makers at the different organisations form a network where all nodes have substantial autonomy with respect to their own social networks, telecommunications networks, resources, and decision-making. The Partner Organisation, the NSW State Emergency Service (SES) wants to join with the University of Sydney to create more effective, efficient and robust information network systems for decision-making during crisis events, and for post-crisis analysis. Our aim is to quantify existing structures and extending the analytical approaches to social network theory using structures inspired by biological networks.
Want to find out more?
The opportunity ID for this research opportunity is: 1352
Other opportunities with Professor Liaquat Hossain
- Modeling Coordination through Social Networks
- Modeling Performance through Social Networks
- Studying Traders' Behaviour through Social Networks
- Social Networks on Preventive Healthcare: New approaches to Early Detection of Chronic Disease
- Early Detection of Insurance Fraud through Social Networks
- PhD project on Exploring Childhood Obesity through Social Networks
- PhD project on Adaptive multi-agency response coordination for managing distributed disease outbreaks
- Dynamic Modeling of Bacterial and Organizational Colony Networks for Coordinated Response to Influenza
- Dynamics of Peer Counselling, Mothers and Family Social Networks for infant and young child feeding
- Complex Coordination Dynamics in Disaster Response
- Self-Assembly and Self-Organization in Complex Distributed Systems
- Parallel Stochastic Optimization Algorithms
- MicroRNAs as Regulators of Cellular Programs
- Resilience and distributed systems for a healthy society
- Estimation and Inference in Environment Sensing Networks
- Biological metaphors and resilience
- Complex Networks and Performance
- Modeling biological interactions: from individuals to ecosystems
- Nutrition and the origin of phenotype
- Securing the future of water and soil
- Quantifying the return on investment in the Environment, Public Health and Individual Wellbeing.
- Exploring the link between international trade and the global obesity epidemic
- Sustainable Community Healthcare Networks
- Visualisation of High Dimensional Data.
- Do genes have memory?
- The evolutionary ecology of complex microbial communities
- Complex Brain Networks and Nutrition
- New approaches to Early Detection of Chronic Disease
- Social and Healthcare Network Effects on Delivery and Quality Of Care
- Physical, Mental and Psychological Health through Personal Networks
- Modeling Complex Coordination of Public Health Care