适应性疫情管理策略在施工现场的应用:基于代理模型的方法

学术   科学   2024-08-09 07:16   湖北  

作者:李成谦 a, 方琦 b, 陈珂 c, 包智康 d, 江泽浩 c, *, 刘文黎 c

单位:a 湖南大学; b 中南大学; c华中科技大学; d 英国Heriot-Watt University

引用:Chengqian LI, Qi FANG, Ke CHEN, Zhikang BAO, Zehao JIANG, Wenli LIU. Adaptive pandemic management strategies for construction sites: An agent-based modeling approach. Frontiers of Engineering Management, https://doi.org/10.1007/s42524-024-3061-7

文章链接:

https://journal.hep.com.cn/fem/EN/10.1007/s42524-024-3061-7

https://link.springer.com/article/10.1007/s42524-024-3061-7

导语:在面对突发疫情时,项目管理人员需要根据实际情况分析预测当前管理策略的潜在后果,并迅速调整和制定优化策略。这突显了制定主动管理策略以增强疫情应对能力的必要性。然而,现有研究主要集中于疫情的负面影响,往往忽视了为施工现场开发适应性管理方法。通过基于代理模型的方法,本研究模拟了工人的移动模式以及在不同风险场景和管理措施下的疫情传播情况。研究结果表明,诸如佩戴口罩、管理集体活动和实施入场控制等措施可以显著减少施工现场的疫情传播,其中入场控制的效果最为显著。

关键词:疫情传播;基于代理模型;安全管理;管理策略


1.

引言

 “人传人”传染病的爆发,如SARS、埃博拉病毒、MERS-CoV和COVID-19,对施工项目的执行造成了显著影响。这些疫情导致施工时间延长、费用增加和质量下降(Luo等,2020)。由于施工工作劳动强度大且需要近距离接触,工人面临更高的感染风险。一项分析超过73万次COVID-19检测结果的研究显示,建筑工人几乎在所有职业组中无症状感染率最高(Allan-Blitz等,2020)。多家公共卫生机构指出,施工现场是疫情爆发的前三大职业场所之一,包括华盛顿州卫生部(2022)、密歇根政府(2022)和纳什维尔田纳西论坛报(2020)。因此,迫切需要主动和前瞻性的管理策略,以增强施工活动中的疫情应对能力。

目前,关于疫情对施工现场不利影响的研究主要依赖于统计数据分析。Alsharef等(2021)通过对34名行业人员的访谈发现,负面影响包括项目重大延误、材料采购困难、生产率降低、材料成本增加等问题。Sierra等(2022)对文献进行了综合评审,指出承包商面临的主要挑战包括现场健康和安全问题、潜在法律责任、劳动力可用性、供应链和分包商的不稳定性以及疫情持续和不可预测的进展带来的不确定性。然而,这些研究主要采用事后因果推断方法(Alfadil等,2022),如档案分析、实地研究和问卷调查,可能无法提供针对特定场景的细节和反事实问题的应对措施。

事后因果推断通过分析历史案例中的因果关系来识别显著变量并量化其影响(Gradu等,2022)。然而,这种方法只能阐明过去案例的疫情防控结果,缺乏对疫情应对的预测性洞见。相比之下,基于代理的建模(Agent-based Modeling, ABM)是一种专注于个体行为及其在复杂系统中应用的特殊方法,包括人类行为、生态系统和经济系统(An等,2021)。这种建模方法具有多个优势。首先,ABM可以模拟不同个体或代理之间的互动及其对环境的反应,从而更精确地反映管理策略的效果。其次,ABM通过蒙特卡罗方法模拟大量随机个体行为和互动,对随机场景具有韧性(Nail-i等,2019)。这使得在考虑系统内在复杂性和多样性时更全面,避免过度依赖单一案例。最后,ABM作为数据驱动因果推断方法的有力补充和验证工具(Casini和Manzo,2016)。

借助ABM的优势,本研究提出了一种基于时空交叉的新颖模拟方法,以推导施工现场的疫情传播风险。研究重点在于轨迹数据分析、模式识别和工人轨迹模拟。由于施工现场具有半封闭空间、稳定人员编制和高密度互动等特点,这种方法尤为重要。通过增强的建模能力,项目经理可以获得更为明智的疫情应对策略指导。因此,本研究利用ABM模拟施工现场的疫情传播动态,向项目经理提供针对特定场景和反事实的洞见,使其能够采取实际措施预防”人传人”传染病。


2.

研究方法

如图1所示,基于代理的模型创建涉及两个相互关联并互相影响的部分:工人日常活动的模拟和疫情传播的动态。


图1. 技术流程图


2.1 时空轨迹学习与聚类

工人运动轨迹的分析和聚类是模拟人际传染病爆发的重要步骤。首先,对收集到的原始轨迹数据进行清洗和预处理。通过工人携带的RFID标签获取运动数据,这些标签在工人穿越施工现场的不同区域时被自动检测和记录。在预处理中,剔除异常值、过滤重复数据并对轨迹进行分段,然后提取和标记位置信息。这些位置被映射到预定义区域,如“办公室”、“施工区”、“材料存放区”、“钢筋加工区”等。

接着,基于“位置标签-占用时间”配对,制定时空频率分布表,量化工人在各施工区域占用时间的分布。表中的每个值(区域占用强度,AOI)表示在特定时间间隔内,工人在某一区域所占时间的比例。

然后,使用层次聚类分析(Köhn和Hubert,2014)对时空频率分布表进行模式识别。利用欧氏距离量化不同施工区域时间间隔分布向量的相似性,生成距离矩阵,并通过迭代聚类过程,将相似的分布向量聚合成簇。最后,使用Kneedle算法(Antunes等,2018)确定最优的聚类数量,揭示常见的时间框架和工人经常占用的特定区域。

图2. 时空轨迹的层次聚类过程


2.2 事件与过程建模

本节探讨活动建模的关键要素,这是建立疫情传播时空关联的前提。每个工人代理的活动包括触发预定条件、移动到另一个位置和等待下一个事件。多个活动的串联决定了工人代理的日常运动轨迹(如早上6:30在宿舍醒来→6:45在食堂吃早餐→7:00在施工现场开始工作等)。不同类别的工人表现出不同的行为模式,例如木工和钢筋工的运动轨迹明显不同。

图3. 施工现场工人的移动动因


a)  触发预定条件

病毒传播是由于工人位置的动态变化,因此空间移动模型在评估疫情风险中至关重要。工人的轨迹通常受几个因素影响:首先是时间驱动因素。工人通常遵循固定的通勤时间表,空间位置主要由当前时间决定。在模拟中,代理根据层次聚类结果在特定时间移动到预定的地点。其次是活动驱动因素。不同工种的工人在施工现场的运动模式差异显著。例如,钢筋工主要在材料存放和加工区活动,而办公室人员通常在办公区活动。通过分析工人在各区域的停留时间和区域间的过渡概率,模拟这些运动模式。最后是紧急驱动因素。当工人被怀疑感染时,启动紧急协议,将其密切接触者转移到指定隔离设施。

b)  移动到另一个位置

当触发预定条件时,工人代理将获得指定目的地的信息。社会力模型(Lakoba等,2005)用于模拟工人代理的运动轨迹,模型中工人在行走时受到三种力的影响:期望力(fi0)、工人间的排斥力(fij)和工人与障碍物间的排斥力(fiw)。公式如下:                                          

其中fi(t)表示工人所受的合力。

图4. 施工现场工人的移动驱动合力

c)     等待下一个事件

到达活动目的地后,工人在现场停留一段时间,直到满足下一个活动的前提条件,开始新的活动序列。

2.3   健康状态传输模拟

施工现场的疫情管理策略应根据所在城市的疫情风险水平制定。进入施工现场时,工人感染的概率取决于城市的疫情状况。通过已知的死亡数据和年龄特定的感染致死率计算城市的总感染人数,从而推算出城市的感染率。

a)     疫情发展

在传染病背景下,工人主要通过密切接触相互传染。本研究采用马尔可夫链模型(Xu等,2022)描绘病态工人自愈或病情恶化过程中状态的转变。工人状态转变的概率可以通过公式计算:

其中,Fix→y(t)表示工人i从状态x转变为状态y的时间小于t的概率,λ为指数分布模型中的预定参数。

b)     风险分析与政策制定

在进行风险分析之前,首先确定项目经理最关心的不良结果,例如施工延误、成本超支和严重感染。施工延误可通过公式估算:

其中,△Ti表示工人i因感染的隔离和治疗时间,σ是非关键过程冗余的折减因子。


3.

实验结果与讨论

3.1 不同疫情情景的影响模拟

本实验旨在模拟施工现场发生的传染病传播及其进展,并评估各种防疫策略的有效性。考虑到COVID-19的全球影响及其严重后果,本研究将其作为代表性模型。为了更深入了解工人轨迹及其对疫情传播的影响,本研究进行了对照实验。实验旨在通过两种不同的运动模式模拟疫情传播:随机行走和目标导向移动。大多数关于施工现场疫情的研究假设工人随机移动,而本研究强调目标导向移动的重要性,更符合工人的实际运动模式。目标导向移动涉及工人以特定目标为导向,如去食堂用餐或前往施工区工作。

图5. 不同移动模式下的感染人数

结果显示,两种模式下的感染数量有显著差异。在随机行走模式下,感染数量呈正态分布,而在目标导向移动模式下,数据呈离散两极化特征。这种差异可以归因于随机行走模式下工人不规则的移动,增加了与不同个体的互动,促进了病毒传播。而在目标导向移动模式下,工人遵循更系统的移动模式,减少了感染者与其他人的互动频率,从而降低了病毒传播的可能性。

3.2 疫情防控政策管理模拟

为了更深入了解施工现场疫情传播的机制,本研究还调查了几种常用的预防和控制措施的效果,包括工人佩戴口罩比例、分组平衡策略和入场检查策略。

佩戴口罩被认为是对抗传染病的直接有效手段。模拟实验评估了口罩对病毒的防护效果。结果表明,全体工人佩戴口罩可以将平均总感染人数减少约一半。然而,当未能实现全员佩戴口罩时,不同口罩佩戴比例对疫情防控效果影响不大。这表明,高比例的口罩佩戴合规性对于有效预防和控制工作场所的传染病传播至关重要。

分组平衡策略是一种将较大群体细分为较小组或子组以减少互动和降低交叉感染风险的疫情控制措施。在施工现场实施该策略时,可以根据工种和任务将团队划分为不同的子组,确保这些子组独立运作,减少工作时间表和工作区域的重叠。模拟结果显示,分组平衡策略显著减缓了疫情传播。前线工人(如木工)和非前线工人(如办公室人员)的初始感染源对模拟结果的影响也有所不同,这表明初始感染源的工种对疫情传播有影响。

入场检查被认为是疫情管理的有效方法,涉及筛查和调控潜在高风险外来人员的进入。模拟结果显示,实施入场检查措施后,施工现场工人的感染率显著下降。

综合分析不同管理策略的效果,通过蒙特卡罗模拟进行对照实验,结果表明严格执行所有三项措施可显著减少因疫情导致的施工延误。具体来说,与未采取任何措施的情景相比,延误时间也大幅减少。

本研究通过模拟实验和分析,提供了疫情防控策略在施工现场的有效性洞见,为项目经理制定针对性的疫情管理措施提供了依据。



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