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Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF.
Liu, Jin; Liu, Allen Wood; Li, Xingye; Li, Hui; Luo, Wenwei; Chen, Wei.
Afiliação
  • Liu J; College of Information Engineering, Shanghai Maritime University, Shanghai, China.
  • Liu AW; Shanghai Experimental School International Division, Shanghai, China.
  • Li X; College of Information Engineering, Shanghai Maritime University, Shanghai, China.
  • Li H; Faculty of Education and Human Development, The Education University of Hong Kong, Hong Kong, Special Administrative Region, Tai Po, China.
  • Luo W; College of Early Childhood Education, Shanghai Normal University, Shanghai, China.
  • Chen W; College of International Education, Shanghai Business School, Shanghai, China.
Front Public Health ; 12: 1339611, 2024.
Article em En | MEDLINE | ID: mdl-38515601
ABSTRACT

Introduction:

Metropolitan governance's efficacy is regularly gauged by its capability for public health preparedness, a critical component, particularly in the post-pandemic climate, as global cities reassess their mitigation abilities. This process has broader implications, curbing mortality rates and amplifying sustainability. Current methodologies for preparedness assessment lean primarily on either Subjective Evaluation-Based Assessment (SBA), predicated on experts' input on various capacity indicators, or they opt for Data-Based quantitative Assessments (DBA), chiefly utilizing public statistic data.

Methods:

The manuscript discusses an urgent need for integrating both SBA and DBA to adequately measure Metropolitan Public Health Pandemics Preparedness (MPHPP), thus proposing a novel entropy-TOPSIS-IF model for comprehensive evaluation of MPHPP. Within this proposed model, experts' subjective communication is transformed into quantitative data via the aggregation of fuzzy decisions, while objective data is collected from public statistics sites. Shannon's entropy and TOPSIS methods are enacted on these data sets to ascertain the optimal performer after normalization and data isotropy. Results and

discussion:

The core contribution of the entropy-TOPSIS-IF model lies in its assessment flexibility, making it universally applicable across various contexts, regardless of the availability of expert decisions or quantitative data. To illustrate the efficacy of the entropy-TOPSIS-IF model, a numerical application is presented, examining three Chinese metropolises through chosen criteria according to the evaluations of three experts. A sensitivity analysis is provided to further affirm the stability and robustness of the suggested MPHPP evaluation model.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Pública / Pandemias Idioma: En Revista: Front Public Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Saúde Pública / Pandemias Idioma: En Revista: Front Public Health Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China País de publicação: CH / SUIZA / SUÍÇA / SWITZERLAND