Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF
Copyright © 2024 Liu, Liu, Li, Li, Luo and Chen..
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.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2024 |
|---|---|
| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
|---|---|
| Enthalten in: |
Frontiers in public health - 12(2024) vom: 22., Seite 1339611 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Liu, Jin [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Entropy-TOPSIS-IF |
|---|
| Anmerkungen: |
Date Completed 25.03.2024 Date Revised 25.03.2024 published: Electronic-eCollection Citation Status MEDLINE |
|---|
| doi: |
10.3389/fpubh.2024.1339611 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM370051750 |
|---|
| LEADER | 01000caa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM370051750 | ||
| 003 | DE-627 | ||
| 005 | 20240325235450.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 240323s2024 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3389/fpubh.2024.1339611 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1347.xml |
| 035 | |a (DE-627)NLM370051750 | ||
| 035 | |a (NLM)38515601 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Liu, Jin |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF |
| 264 | 1 | |c 2024 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 25.03.2024 | ||
| 500 | |a Date Revised 25.03.2024 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024 Liu, Liu, Li, Li, Luo and Chen. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a TOPSIS | |
| 650 | 4 | |a entropy-TOPSIS-IF | |
| 650 | 4 | |a fuzzy theory | |
| 650 | 4 | |a multicriteria decision making | |
| 650 | 4 | |a preparedness on pandemics | |
| 650 | 4 | |a public health preparedness | |
| 700 | 1 | |a Liu, Allen Wood |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Xingye |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Hui |e verfasserin |4 aut | |
| 700 | 1 | |a Luo, Wenwei |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Wei |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Frontiers in public health |d 2013 |g 12(2024) vom: 22., Seite 1339611 |w (DE-627)NLM23377548X |x 2296-2565 |7 nnns |
| 773 | 1 | 8 | |g volume:12 |g year:2024 |g day:22 |g pages:1339611 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.3389/fpubh.2024.1339611 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 12 |j 2024 |b 22 |h 1339611 | ||