Bibliographic Details
| Title: |
Research on Intelligent Emergency Resource Allocation Mechanism for Public Health Emergencies: A Case Study on the Prevention and Control of COVID-19 in China |
| Authors: |
Ruhao Ma, Fansheng Meng, Haiwen Du |
| Source: |
Systems, Vol 11, Iss 6, p 300 (2023) |
| Publisher Information: |
MDPI AG, 2023. |
| Publication Year: |
2023 |
| Collection: |
LCC:Systems engineering
LCC:Technology (General) |
| Subject Terms: |
public health emergency, emergency resource allocation, intelligent technology, Systems engineering, TA168, Technology (General), T1-995 |
| More Details: |
The outbreak of COVID-19 posed a significant challenge to the emergency management system for public health emergencies, especially in China, where the epidemic began. As intelligent technology has injected new vitality into emergency management, applying intelligent technology to optimize emergency resource allocation (ERA) has become a focus of research in the post-epidemic era. Based on China’s experience in preventing and controlling COVID-19, this paper first analyzes the characteristics and process of ERA in public health emergencies, and then synthesizes the relevant Chinese studies in recent years to identify the intelligent technologies affecting ERA in China using word frequency analysis technology. We also construct an intelligent emergency resource allocation mechanism in four areas: medical intelligence, management intelligence, decision-making intelligence, and supervision intelligence. Finally, we use the entropy-TOPSIS method to evaluate the impact of intelligent technologies on ERA, and we rank the criticality of intelligent technologies. The experimental results show that (i.) medical intelligence and management intelligence are the keys to developing intelligent ERA, and (ii.) among the identified essential intelligent technologies, artificial intelligence (AI), and big data technology have a more significant and critical role in emergency resource intelligence allocation. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
2079-8954 |
| Relation: |
https://www.mdpi.com/2079-8954/11/6/300; https://doaj.org/toc/2079-8954 |
| DOI: |
10.3390/systems11060300 |
| Access URL: |
https://doaj.org/article/625488c489a4451d9fe5276b6ef6b20c |
| Accession Number: |
edsdoj.625488c489a4451d9fe5276b6ef6b20c |
| Database: |
Directory of Open Access Journals |
