A task-oriented framework for dynamic generation of public health emergency plans in major infectious disease response
- 1School of Management, Zhengzhou Shengda University
- 2School of Economics and Management, Dalian University of Technology
Abstract
Public health emergency plans for major infectious diseases provide essential operational guidance for emergency response, but they suffer from high content homogeneity and limited operability, which reduces their effectiveness in real-world implementation. Although previous studies have explored task decomposition and emergency plan generation, there remains a lack of approaches that systematically extract task semantics from real emergency texts and dynamically construct executable task structures. To address this gap, this study proposes an Hierarchical Task Network(HTN)-Verb task-oriented framework for major infectious disease emergency response, in which emergency-response verbs are treated as the core carriers of task semantics to enable unified modeling of public health emergency plan texts and actual response records. The framework integrates verb-driven hierarchical task decomposition, dynamic plan generation based on practice feedback, and multi-dimensional task relationship modeling with priority-based conflict resolution. The proposed method is evaluated through a grassroots case study of Village A. Results show that emergency plans generated using the HTN-Verb framework achieve substantially higher overall effectiveness and operability than the original public health emergency plan text. The proposed approach provides a feasible pathway for transforming static emergency plans into structured and executable task networks, with practical implications for improving grassroots emergency response efficiency.
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BibTeX
@article{li2026taskoriented,
title = {{A task-oriented framework for dynamic generation of public health emergency plans in major infectious disease response}},
author = {Fangzhou Li and Ming Cong and Yue Feng and Lili Rong},
journal = {Frontiers in Public Health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1831748},
url = {https://www.frontiersin.org/articles/10.3389/fpubh.2026.1831748/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A task-oriented framework for dynamic generation of public health emergency plans in major infectious disease response
AU - Fangzhou Li
AU - Ming Cong
AU - Yue Feng
AU - Lili Rong
PY - 2026
DA - 2026/10/27
JO - Frontiers in Public Health
DO - 10.3389/fpubh.2026.1831748
UR - https://www.frontiersin.org/articles/10.3389/fpubh.2026.1831748/full
AB - Public health emergency plans for major infectious diseases provide essential operational guidance for emergency response, but they suffer from high content homogeneity and limited operability, which reduces their effectiveness in real-world implementation. Although previous studies have explored task decomposition and emergency plan generation, there remains a lack of approaches that systematically extract task semantics from real emergency texts and dynamically construct executable task structures. To address this gap, this study proposes an Hierarchical Task Network(HTN)-Verb task-oriented framework for major infectious disease emergency response, in which emergency-response verbs are treated as the core carriers of task semantics to enable unified modeling of public health emergency plan texts and actual response records. The framework integrates verb-driven hierarchical task decomposition, dynamic plan generation based on practice feedback, and multi-dimensional task relationship modeling with priority-based conflict resolution. The proposed method is evaluated through a grassroots case study of Village A. Results show that emergency plans generated using the HTN-Verb framework achieve substantially higher overall effectiveness and operability than the original public health emergency plan text. The proposed approach provides a feasible pathway for transforming static emergency plans into structured and executable task networks, with practical implications for improving grassroots emergency response efficiency.
SN - 2296-2565
ER -