A Review of Construction Methods Based on Agent Modeling in the Field of Public Health Control

Main Article Content

Mingyuan Wu
Beijing Normal-Hong Kong Baptist University, Zhuhai, China

DOI: https://doi.org/10.70267/shbe.2026233241

Keywords

agent-based modeling, public health control, infectious disease modeling, decision support

Abstract

Public health control involves complex and dynamic processes shaped by individual heterogeneity, social interaction, spatial context, and policy intervention. Traditional aggregate models often have limited capacity to represent these micro -level mechanism s and their emergent population -level effects. Against this background, agent-based modeling (ABM) has become an important methodological approach in public health research. This review systematically examines the construction methods of ABM in the field o f public health control, with a focus on its conceptual foundations, core modeling procedures, major methodological choices, and their implications for public health decision -making. The review shows that public health ABMs are commonly structured around f our key components: agent and population specification, environment and spatial structure design, contact mechanism and social network construction, and disease state transition modeling. These construction choices directly shape the model’s explanatory ca pacity, realism, and policy relevance. The study further finds that, despite the flexibility and analytical strengths of ABM, current research still faces challenges in reporting transparency, data support, calibration, and validation. Overall, examining ABM from the perspective of construction methods can strengthen methodological rigor and improve its value for public health policy design and decision support.  

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Published
Aug 11, 2026
Conference Proceedings Volume
Vol. 18 (2026): Proceedings of 2026 International Conference on Smart Healthcare and Biomedical Engineering (ICSHBE 2026)
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Articles
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How to Cite

Wu, Mingyuan. “A Review of Construction Methods Based on Agent Modeling in the Field of Public Health Control”. Exploring Science Academic Conference Series, vol. 18, Aug. 2026, pp. 233-41, https://doi.org/10.70267/shbe.2026233241.