Dynamic Analysis of the Effectiveness of Emergency Collaboration Networks for Public Health Emergencies from a Systems Thinking Perspective

In recent years, public health emergencies have become frequent worldwide. In response to these complex and evolving emergencies, the organizations involved are increasingly collaborating with each other. From a systems thinking perspective, greater attention should be given to the long-term development and continuous operation of emergency collaboration systems. By time slicing the development of the COVID-19 epidemic in Wuhan, the different phases of emergency collaboration networks can be respectively established. A new method for identifying key organization nodes and different network attack strategies is proposed, assessing network effectiveness from two dimensions: efficiency and resilience. The results indicate that, compared to random attack strategies, the efficiency and resilience of these networks are significantly affected by deliberate attack strategies, underscoring the network’s sensitivity to high-importance nodes. Based on the variations in network efficiency and resilience, the effectiveness of different forms of networks are classified into four types. The pre-emergency network is categorized as resilience-focused, the mid-emergency network as efficiency-oriented, the post-emergency network as efficient-resilient, and the overall emergency network as inefficient-fragile. Analyzing forms of network effectiveness at different phases offers a deeper understanding of the operational characteristics, dynamic changes, and existing issues within emergency collaboration networks. This study provides a vital theoretical basis and practical guidance for emergency management departments and decision-makers on how to effectively improve collaboration mechanisms between different organizations.

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Publication Details

Journal
Systems
Published
2024-11-28
DOI
https://doi.org/10.3390/systems12120533
Primary Topic
Complex Systems and Decision Making
Type
article
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article

Dynamic Analysis of the Effectiveness of Emergency Collaboration Networks for Public Health Emergencies from a Systems Thinking Perspective

Xiulai Wang, Jun Xu, Xiao Li
Systems
Complex Systems and Decision Making
article

Dynamic Analysis of the Effectiveness of Emergency Collaboration Networks for Public Health Emergencies from a Systems Thinking Perspective

Xiulai Wang, Jun Xu, Xiao Li
article en

Abstract

In recent years, public health emergencies have become frequent worldwide. In response to these complex and evolving emergencies, the organizations involved are increasingly collaborating with each other. From a systems thinking perspective, greater attention should be given to the long-term development and continuous operation of emergency collaboration systems. By time slicing the development of the COVID-19 epidemic in Wuhan, the different phases of emergency collaboration networks can be respectively established. A new method for identifying key organization nodes and different network attack strategies is proposed, assessing network effectiveness from two dimensions: efficiency and resilience. The results indicate that, compared to random attack strategies, the efficiency and resilience of these networks are significantly affected by deliberate attack strategies, underscoring the network’s sensitivity to high-importance nodes. Based on the variations in network efficiency and resilience, the effectiveness of different forms of networks are classified into four types. The pre-emergency network is categorized as resilience-focused, the mid-emergency network as efficiency-oriented, the post-emergency network as efficient-resilient, and the overall emergency network as inefficient-fragile. Analyzing forms of network effectiveness at different phases offers a deeper understanding of the operational characteristics, dynamic changes, and existing issues within emergency collaboration networks. This study provides a vital theoretical basis and practical guidance for emergency management departments and decision-makers on how to effectively improve collaboration mechanisms between different organizations.

SystemsVol. 12(12)
Nanjing University of Information Science and Technology (CN), Nanjing General Hospital of Nanjing Military Command (CN), Nanjing University (CN)
Openalex Percentile: Top 74%
Complex Systems and Decision Making
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