  Objectives: To identify and quantify risk factors that contribute to clusters
of COVID-19 in the workplace.
  Methods: We identified clusters of COVID-19 cases in the workplace and
investigated the characteristics of the individuals, the workplaces, the areas
they work, and the methods of commute to work, through data linkages based on
Middle Layer Super Output Areas (MSOAs) in England between 20/06/2021 and
20/02/2022. We estimated associations between potential risk factors and
workplace clusters, adjusting for plausible confounders identified using a
Directed Acyclic Graph (DAG).
  Results: For most industries, increased physical proximity in the workplace
was associated with increased risk of COVID-19 clusters, while increased
vaccination was associated with reduced risk. Commuter demographic risk factors
varied across industry, but for the majority of industries, a higher proportion
of black/african/caribbean ethnicities, and living in deprived areas, was
associated with increased cluster risk. A higher proportion of commuters in the
60-64 age group was associated with reduced cluster risk. There were
significant associations between gender, work commute methods, and staff
contract type with cluster risk, but these were highly variable across
industries.
  Conclusions: This study has used novel national data linkages to identify
potential risk factors of workplace COVID-19 clusters, including possible
protective effects of vaccination and increased physical distance at work. The
same methodological approach can be applied to wider occupational and
environmental health research.
