Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks
ObjectivesThe objective was to aggregate the various scenarios that occur during nonconventional public health emergencies (NCPHEs) and analyze the evolutionary patterns of NCPHEs to better avoid risks and reduce social impacts. The aim was to enhance strategies for handling NCPHEs.Study designNews...
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1489904/full |
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| author | Yutao Zhu Qing Yang Lingmei Fu Chun Cai Jinmei Wang Ling He |
| author_facet | Yutao Zhu Qing Yang Lingmei Fu Chun Cai Jinmei Wang Ling He |
| author_sort | Yutao Zhu |
| collection | DOAJ |
| description | ObjectivesThe objective was to aggregate the various scenarios that occur during nonconventional public health emergencies (NCPHEs) and analyze the evolutionary patterns of NCPHEs to better avoid risks and reduce social impacts. The aim was to enhance strategies for handling NCPHEs.Study designNews reports were crawled to obtain the scenario elements of NCPHEs and categorized into the spreading stage or derivation stage. Finally, the key scenario nodes and scenario evolution process were analyzed in combination with a corresponding emergency response assessment of each scenario by experts.MethodsDempster–Shafer (DS) theory and Bayesian networks (BNs) were applied for data reasoning, and a spread-derived coupled scenario–response theoretical model of NCPHEs for major public health emergencies was constructed. The scenario evolution path of COVID-19 was derived by combining seven types of major scenario states and corresponding emergency response measures extracted from 952 spreading scenarios.ResultsThe 26 NCPHE spread scenarios and 41 NCPHE derivation scenarios were summarized. Optimized and pessimistic NCPHE scenario pathways were generated by combining the seven major spreading scenarios to help decision makers predict the development of NCPHEs and take timely and effective emergency response measures for key scenario nodes.ConclusionThis study provides a new approach for understanding and managing NCPHEs, emphasizing the need to consider the specificity and complexity of such emergencies when developing decision-making strategies. Our contextual derivation model and emergency decision-making system provide practical tools with which to enhance NCPHE response capabilities and promote public health and safety. |
| format | Article |
| id | doaj-art-badb76e941e04dc0aa81dc9c8faad478 |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-badb76e941e04dc0aa81dc9c8faad4782025-02-07T06:49:27ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-02-011310.3389/fpubh.2025.14899041489904Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networksYutao Zhu0Qing Yang1Lingmei Fu2Chun Cai3Jinmei Wang4Ling He5School of Management, Wuhan University of Technology, Wuhan, ChinaSchool of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, ChinaCollege of Emergency Management, Nanjing Tech University, Nanjing, ChinaSchool of Automotive Engineering, Wuhan University of Technology, Wuhan, ChinaSchool of Safety Science and Emergency Management, Wuhan University of Technology, Wuhan, ChinaSchool of Management, Wuhan University of Technology, Wuhan, ChinaObjectivesThe objective was to aggregate the various scenarios that occur during nonconventional public health emergencies (NCPHEs) and analyze the evolutionary patterns of NCPHEs to better avoid risks and reduce social impacts. The aim was to enhance strategies for handling NCPHEs.Study designNews reports were crawled to obtain the scenario elements of NCPHEs and categorized into the spreading stage or derivation stage. Finally, the key scenario nodes and scenario evolution process were analyzed in combination with a corresponding emergency response assessment of each scenario by experts.MethodsDempster–Shafer (DS) theory and Bayesian networks (BNs) were applied for data reasoning, and a spread-derived coupled scenario–response theoretical model of NCPHEs for major public health emergencies was constructed. The scenario evolution path of COVID-19 was derived by combining seven types of major scenario states and corresponding emergency response measures extracted from 952 spreading scenarios.ResultsThe 26 NCPHE spread scenarios and 41 NCPHE derivation scenarios were summarized. Optimized and pessimistic NCPHE scenario pathways were generated by combining the seven major spreading scenarios to help decision makers predict the development of NCPHEs and take timely and effective emergency response measures for key scenario nodes.ConclusionThis study provides a new approach for understanding and managing NCPHEs, emphasizing the need to consider the specificity and complexity of such emergencies when developing decision-making strategies. Our contextual derivation model and emergency decision-making system provide practical tools with which to enhance NCPHE response capabilities and promote public health and safety.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1489904/fullunconventional public health emergenciesscenario evolutionBayesian networksemergency responseCOVID-19 |
| spellingShingle | Yutao Zhu Qing Yang Lingmei Fu Chun Cai Jinmei Wang Ling He Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks Frontiers in Public Health unconventional public health emergencies scenario evolution Bayesian networks emergency response COVID-19 |
| title | Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks |
| title_full | Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks |
| title_fullStr | Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks |
| title_full_unstemmed | Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks |
| title_short | Scenario construction and evolutionary analysis of nonconventional public health emergencies based on Bayesian networks |
| title_sort | scenario construction and evolutionary analysis of nonconventional public health emergencies based on bayesian networks |
| topic | unconventional public health emergencies scenario evolution Bayesian networks emergency response COVID-19 |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1489904/full |
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