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An agent-based model to simulate workplace transmission of SARS-CoV-2

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Understanding how workplace transmission of SARS -CoV-2 is influenced by workplace environmental factors, human behaviour and control strategies is critical. We aimed to develop an agent-based mathematical model to simulate how SARS -CoV-2 outbreaks propagate within workplaces to investigate the efficacy of potential control and mitigation strategies. A stochastic SIR model has been developed utilising enterprise-level contact networks. Initial development used a published pre-pandemic workplace contact network of French office workers. Individual workers transition between states in 24-hour steps where the risk of individual infection is dependent upon contact duration and distance, the infectivity of daily contacts, and on environmental and control factors. Disease characteristics such as the incubation period and daily infectiousness were based on published estimates. Individual infection probabilities were based on the Wells-Riley infection model with viral generation parameters selected to give SARs (Secondary Attack Rates) consistent with those observed in workplace outbreaks seen via UK Test and Trace. The relative efficacy of different controls (workplace social distancing, face coverings, room ventilation, rapid antigen testing and case isolation) was investigated by running the model over different combinations of relevant variations in model parameters and changes to the contact network. Preliminary results suggest that the effectiveness of control measures depends upon patterns of short and medium proximity contacts and the relative contribution to transmission from droplet and finer aerosols. Workplace Covid security is likely to be best achieved through a package of control and mitigation measures.

This talk is part of the Worms and Bugs series.

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