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The benefits, both in terms of productivity and public health, areinvestigated for different levels of engagement with the test, trace andisolate procedures in the context of a pandemic in which there is little or noherd immunity. Simple mathematical modelling is used in the context of asingle, relatively closed workplace such as a factory or back-office where, innormal operation, each worker has lengthy interactions with a fixed set ofcolleagues. A discrete-time SEIR model on a fixed interaction graph issimulated with parameters that are motivated by the recent COVID-19 pandemic inthe UK during a post-peak phase, including a small risk of viral infection fromoutside the working environment. Two kinds of worker are assumed, transparentswho regularly test, share their results with colleagues and isolate as soon asa contact tests positive for the disease, and opaques who do none of these.Moreover, the simulations are constructed as a ``playable model" in which thetransparency level, disease parameters and mean interaction degree can bevaried by the user. The model is analysed in the continuum limit. Allsimulations point to the double benefit of transparency in maximisingproductivity and minimising overall infection rates. Based on these findings,public policy implications are discussed on how to incentivise this mutuallybeneficial behaviour in different kinds of workplace, and simplerecommendations are made.

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