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The benefits of peer transparency in safe workplace operation post pandemic lockdown

机译:在大流行锁定后对同伴透明度的好处

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摘要

The benefits of different levels of engagement with test, trace and isolate procedures are investigated for a pandemic in which there is little population immunity, in terms of productivity and public health. Simple mathematical modelling is used in the context of a single, relatively closed workplace such as a factory or back-office where, in normal operation, each worker has lengthy interactions with a fixed set of colleagues. A discrete-time SEIR model on a fixed interaction graph is simulated with parameters that are motivated by the recent COVID-19 pandemic in the UK during a post-peak phase, including a small risk of viral infection from outside the working environment. Two kinds of worker are assumed, transparents who regularly test, share their results with colleagues and isolate as soon as a contact tests positive for the disease, and opaques who do none of these. Moreover, the simulations are constructed as a ‘playable model’ in which the transparency level, disease parameters and mean interaction degree can be varied by the user. The model is also analysed in the continuum limit. All simulations point to the double benefit of transparency in both maximizing productivity and minimizing overall infection rates. Based on these findings, public policy implications are discussed for how to incentivise this mutually beneficial behaviour in different kinds of workplace, and simple recommendations are made.
机译:在生产力和公共卫生方面,研究了对测试,痕量和分离程序不同与试验,痕量和分离程序的益处。简单的数学建模在单个相对封闭的工作场所的上下文中使用,例如工厂或后台,在正常操作中,每个工作人员都有冗长的交互与固定的同事。固定相互作用图上的离散时间SEIR模型模拟了在峰值阶段在英国最近的Covid-19大流行病的参数,包括来自工作环境外部病毒感染的少量风险。假设两种工人,经常测试的透明度,并尽快与同事分享他们的结果,并将其孤立,并将其阳性的接触测试,并且不做这些的opaques。此外,模拟被构造为“可玩型”,其中用户可以改变透明度水平,疾病参数和平均相互作用程度。还在连续局部限制中分析模型。所有模拟都指向最大化生产率和最小化整体感染率的透明度的双重效益。基于这些调查结果,讨论了如何在不同类型的工作场所激励这种互利行为的公共政策影响,并制定简单的建议。

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