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健康通行证:一种用于降低公共卫生危机中聚集性感染风险的非接触式登记和适应性访问控制系统。

HealthPass: a contactless check-in and adaptive access control system for lowering cluster infection risk in public health crisis.

作者信息

Luo Guofeng, Wang Yufei, Hong Linghong, He Xin, Wang Jiaru, Shen Qu, Wang Cheng, Chen Longbiao

机构信息

Fujian Key Laboratory of Sensing and Computing for Smart Cities, School of Informatics, Xiamen University, Xiamen, China.

Department of Drug Clinical Trial Institution, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.

出版信息

Front Public Health. 2024 Dec 12;12:1448901. doi: 10.3389/fpubh.2024.1448901. eCollection 2024.

Abstract

INTRODUCTION

Ensuring effective measures against the spread of the virus is paramount for educational institutions and workplaces as they resume operations amidst the ongoing public health crisis. A touchless and privacy-conscious check-in procedure for visitor assessment is critical to safeguarding venues against potential virus transmission.

METHODS

In our study, we developed an interaction-free entry system featuring anonymous visitors who voluntarily provide data. This system introduces an adaptable venue entry management mechanism that accounts for both visitors' potential risk and the venue's capacity, aiming to curb the risk of localized infections. We assess visitors' liability based on their voluntarily provided data through radar map analysis. Additionally, we evaluate the venue's situation by quantifying its risk from multiple dimensions. A queuing model is then employed to control visitor access adaptively based on visitors' liability and the venue's availability.

RESULTS

Since May, our university campus has been the operational site for the implemented system, catering to the needs of visitors across distinct venues. Using real-world implementation, we conduct a series of simulation experiments and case studies to verify the effectiveness of the HealthPass system in lowering infection risks.

DISCUSSION

The system has demonstrated its capacity to reduce infection risks by adapting visitor entry procedures based on individual risk factors and venue conditions. Our results suggest that the integration of a dynamic queuing model and real-time data analysis can effectively manage the flow of visitors while ensuring public health safety.

摘要

引言

在持续的公共卫生危机中,教育机构和工作场所在恢复运营时,确保采取有效措施防止病毒传播至关重要。一种用于访客评估的无接触且注重隐私的登记程序对于保护场所免受潜在病毒传播至关重要。

方法

在我们的研究中,我们开发了一种无交互进入系统,其特点是访客自愿提供数据且匿名。该系统引入了一种适应性强的场所进入管理机制,该机制兼顾访客的潜在风险和场所容量,旨在遏制局部感染风险。我们通过雷达图分析,根据访客自愿提供的数据评估访客的风险状况。此外,我们从多个维度量化场所风险来评估场所情况。然后采用排队模型根据访客风险状况和场所可用情况自适应地控制访客进入。

结果

自5月以来,我们大学校园一直是该实施系统的运行场所,满足不同场所访客的需求。通过实际应用,我们进行了一系列模拟实验和案例研究,以验证健康通行证系统在降低感染风险方面的有效性。

讨论

该系统已证明能够通过根据个体风险因素和场所条件调整访客进入程序来降低感染风险。我们的结果表明,动态排队模型与实时数据分析的结合可以在确保公共卫生安全的同时有效管理访客流量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ad9/11672792/3d7ffb99f314/fpubh-12-1448901-g0001.jpg

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