(A337) State Failure as a Factor in International Global Medical Operations: Network Modeling

Abstract

Introduction

In order to counteract disasters and emergencies, it is necessary to build cooperation and collaboration among all entities and actors. Field teams of rescuers require support from the State experiencing a disaster. The responses to the earthquake in Haiti demonstrated a lack of cooperation and collaboration and the rescuers encountered concomitant difficulties. Thus, the problems in the field are not only related to natural and technological aspects, but also social and political contexts. It is time to explore the role of the impact of State power on national and international disasters and emergencies. One modern and fruitful instrument for analysis of these complicated social and group processes is Complex Network modeling. Complex Network tools have been applied successfully to understanding and counteracting such threats as they relate to the spread of infectious diseases and/or to terrorist activities. Another significant utilization of the Complex Network approach is to develop good governance, management, and organizational processes in national and corporate landscapes.

Methods

Based on a Complex Network Scope, a novel, three-layer network model of public connections for diverse State regimes for further simulation is proposed. Quantitative assessments and practical processes should be implemented for countering global disasters using international and interdisciplinary teams. Contrary to the known hierarchical layer approach for knowledge acquisition, this new model describes an overall national Society Network by dividing the approach into the three layers: (1) Formal (State), as hierarchical governments structures; (2) Informal (presented by different long-term sustainable link groups); and (3) Informal (aquatinters with short term links (“weak ties”).

Results

According to each of these layers, one of three types of network topologies exist: (1) hierarchical; (2) scale-free; and (3) random, respectively.