Developing safety policies to protect large groups of individuals working in indoor environments from disease spread is an important and challenging task. To address this issue, we investigate the scenario of workers becoming infected by a dangerous airborne pathogen in a near-real-life industrial environment. We present a simple analytical model based on observations made during the recent COVID-19 pandemic and business expectations concerning worker protection. The model can be adapted to address other epidemic or non-epidemic threats, including hazardous vapors from industrial processes. In the presented model, we consider both direct and indirect modes of infection. Direct infection occurs through direct contact with an infected individual, while indirect infection results from contact with a contaminated environment, including airborne pathogens in enclosed spaces or contaminated surfaces. Our analysis utilizes a simplified droplet/aerosol diffusion model, validated by droplet spread simulations. This model can be easily applied to new scenarios and has modest computational requirements compared to full simulations. Thus, it can be implemented within an automated protection ecosystem in an industrial setting, where rapid assessment of potential danger is required, and calculations must be performed almost in real-time. We validate general research findings on disease spread using a simple agent-based model. Based on our results, we outline a set of countermeasures for infection prevention, which could serve as the foundation for a prevention policy suited to industrial scenarios.

翻译：制定安全政策以保护在室内环境中工作的大规模人群免受疾病传播，是一项重要且具挑战性的任务。为解决这一问题，我们研究了工人在接近真实的工业环境中感染危险空气传播病原体的情景。我们基于近期COVID-19大流行期间的观察数据及企业对工人防护的预期，提出了一个简单的分析模型。该模型可适用于其他流行病或非流行病威胁，包括工业过程中产生的有害蒸汽。在所提出的模型中，我们同时考虑了直接与间接感染模式。直接感染通过直接接触感染者发生，而间接感染则源于接触受污染环境，包括密闭空间中的空气传播病原体或被污染的表面。我们的分析采用了一个简化的飞沫/气溶胶扩散模型，该模型已通过飞沫传播模拟验证。相比完整模拟，该模型易于应用于新场景，且计算需求较低。因此，它可被集成到工业环境中的自动化防护生态系统中，用于需要快速评估潜在危险并近乎实时执行计算的场景。我们使用一个简单的基于智能体的模型验证了关于疾病传播的总体研究发现。基于研究结果，我们提出了一套预防感染的对策措施，这些措施可作为适用于工业场景的预防政策基础。