ORIGINAL RESEARCH article
Front. Public Health
Sec. Infectious Diseases: Epidemiology and Prevention
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1582024
This article is part of the Research TopicSARS-CoV-2: Virology, Epidemiology, Diagnosis, Pathogenesis and Control, Volume IIView all 8 articles
Modeling healthcare resource Dynamics and Its Application Based on Interregional Population Mobility
Provisionally accepted- 1School of Public Health, Shanxi Medical University, Taiyuan, Shanxi Province, China
- 2Shanxi Bethune Hospital, Shanxi Medical University, Taiyuan, Shanxi Province, China
- 3School of Management, Shanxi Medical University, Taiyuan, Shanxi Province, China
- 4Department of Biochemistry and Molecular Biology, School of Basic Medicine, Shanxi Medical University, Taiyuan, China
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Objective: This study aims to assess the impact of inter-regional population mobility on epidemic progression and healthcare resource congestion during acute infectious disease outbreaks, providing a scientific basis for population control and healthcare resource allocation during pandemics.Methods: Using the SARS-CoV-2 pandemic as a case study, we selected two city pairs -"Taiyuan -Jinzhong" and "Linfen -Yuncheng" as research subjects. Based on real SARS-CoV-2 transmission data and the Baidu Migration Index, we constructed a dynamic healthcare resource model incorporating population mobility factors. We quantified epidemic transmission and healthcare resource congestion using three indicators: cumulative cases, the onset time of healthcare resource congestion, and its duration. By analyzing these metrics, we explored the effect of migration rates on infection scale and healthcare resource congestion.Results: The model-fitted curves closely aligned with the actual data, with most observed data points falling within the 95% confidence interval. Our results suggest that population mobility affects both cumulative cases and healthcare resource congestion, with variation between regions. Unidirectional restrictions on population movement reduced cumulative cases in the outflow region, delayed the onset of healthcare resource congestion and shortened its duration; however, they also increased cumulative cases in the inflow region, advanced the onset of healthcare resource congestion and prolonged its duration. Bidirectional movement restrictions increased cumulative cases in highprevalence regions, but did not change the onset time of healthcare resource congestion and either maintained or increased its duration. In contrast, in low-prevalence regions, bidirectional restrictions reduced cumulative cases, maintained the onset time of healthcare resource congestion, and either shortened or maintained its duration.The healthcare resource dynamics model provides an effective framework for simulating the interplay between population mobility, epidemic transmission, and the congestion on medical resources. In the event of an infectious disease outbreak, this model can be integrated into a regionally unified platform for healthcare resource allocation. By incorporating real-time epidemic data and the healthcare capacities of different areas, the model enables targeted interventions based on the principles of zoning, classification, and time-based management. This approach helps to contain the spread of the epidemic, ease pressure on medical systems, and minimize socio-economic disruptions.
Keywords: infectious disease prevention and control1, population mobility2, healthcare resource congestion3, healthcare resource dynamical model4, SARS-COV-25
Received: 23 Feb 2025; Accepted: 12 Jun 2025.
Copyright: © 2025 Guo, Yan, Yang, Ning, Zhou, Zhang, Ma, Li, Yu and Xie. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Hongmei Yu, School of Public Health, Shanxi Medical University, Taiyuan, 030001, Shanxi Province, China
Jun Xie, Department of Biochemistry and Molecular Biology, School of Basic Medicine, Shanxi Medical University, Taiyuan, China
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