دانلود مقاله افزایش تاب آوری ساخت و ساز در برابر بیماری عفونی
نکات برجسته
چکیده
چکیده گرافیکی
کلید واژه ها
1. مقدمه
2. مرور مطالعات پیشین
3. چارچوب چند عاملی تصادفی برای بیماری های عفونی در ساخت و ساز
4. مطالعه موردی ساخت و ساز: گسترش COVID-19 در یک پروژه ساختمان مسکونی
5. نتیجه گیری و کارهای آتی
منابع
Highlights
Abstract
Graphical abstract
Keywords
1. Introduction
2. Literature review
3. The stochastic multi-agent framework for infectious diseases in construction
4. Construction case-study: spread of COVID-19 in a residential building project
5. Conclusions and future works
Declaration of Competing Interest
References
چکیده
برای بازیابی اثرات نامطلوب COVID-19 بر ساخت‌وساز و جلوگیری از خسارات بیشتر به صنعت در همه‌گیری‌های آینده، تاب‌آوری صنعت ساختمان باید در برابر بیماری‌های عفونی افزایش یابد. در حال حاضر، شکافی برای چارچوب‌های مدل‌سازی برای شبیه‌سازی گسترش بیماری‌های عفونی در پروژه‌های ساختمانی در سطح خرد و آزمایش اثربخشی مداخلات برای تصمیم‌گیری مبتنی بر داده وجود دارد. در اینجا، این شکاف با توسعه یک چارچوب شبیه‌سازی با استفاده از مدل‌سازی مبتنی بر عامل تصادفی، که محققان و متخصصان ساخت‌وساز را قادر می‌سازد تا گسترش بیماری‌های عفونی را در پروژه‌های ساختمانی شبیه‌سازی و محدود کنند، پرداخته می‌شود. این امر به ویژه مهم است، زیرا نتایج یک مطالعه موردی پروژه ساختمان نشان می‌دهد که در مقایسه با جمعیت عمومی، بیماری‌های عفونی ممکن است سریع‌تر در بین کارگران ساختمانی گسترش یابد و تلفات به طور قابل توجهی بیشتر باشد. چارچوب پیشنهادی انگیزه تحقیقات آینده در مدل‌سازی سطح میکرو بیماری‌های عفونی و تلاش برای مداخله در گسترش بیماری‌ها در پروژه‌های ساختمانی است.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modelling frameworks to simulate the spread of infectious diseases in construction projects at micro-level and to test interventions’ effectiveness for data-informed decision-making. Here, this gap is addressed by developing a simulation framework using stochastic agent-based modelling, which enables construction researchers and practitioners to simulate and limit the spread of infectious diseases in construction projects. This is specifically important, since the results of a building project case-study reveals that, in comparison to the general population, infectious diseases may spread faster among construction workers and fatalities can be significantly higher. The proposed framework motivates future research on micro-level modelling of infectious diseases and efforts for intervening the spread of diseases in construction projects.
Introduction
The outbreak of COVID-19 forced several governments around the world to impose various restrictions, such as mobility restrictions, socioeconomic restrictions, and physical distancing regulations, in order to limit the spread of the disease [1]. Despite the positive impacts of these restrictions on the spread of COVID-19, they have caused immense losses to several industries, including manufacturing, hospitality, and construction. Specifically, construction industry has been severely affected by the imposing of social distancing measures, since the execution of construction projects highly relies on the physical interactions between project team members (e.g., labours, equipment operator, engineers). Moreover, despite the stringent restrictions imposed [5] and their consequent losses, previous research confirm that the construction industry have experienced the highest rate of COVID-19 infections among several other industries, including healthcare, manufacturing, and transportation, with five times of the chance of hospitalization as compared to the average of other industries . This might be caused due to the unique characteristics of construction projects, in which project team members commonly work in crews — rather than individually — and tasks are often executed in contained spaces. It should be noted that the temporary or permanent absence of the skilled workforce (i.e., absence or fatality) caused by COVID-19 infections has an additional adverse impact on the performance of construction projects
Conclusions
The outbreak of COVID-19 and its following restrictions imposed by local health authorities have caused several losses to the construction industry. Construction industry needs a comprehensive playbook for an effective and timely recovery from these adverse impacts. The development of such playbook requires an accurate predictive model to analyze the impacts caused by the pandemic and assess several potential interventions for limiting the spread of the disease in construction projects. In this paper, a stochastic simulation framework is introduced for this purpose, which is developed by combining agent-based modelling (ABM) and Monte Carlo simulation (MCS) techniques. This proposed ABM-MCS framework is a generic solution for modelling the resilience of construction projects against the spread of infectious diseases. This generic framework has the capacity to model the spread of different diseases in different types of construction projects with different projects’ site and crews’ settings.