RESUMO
OBJECTIVES: To identify risk factors that contribute to outbreaks of COVID-19 in the workplace and quantify their effect on outbreak risk. METHODS: We identified outbreaks of COVID-19 cases in the workplace and investigated the characteristics of the individuals, the workplaces, the areas they work and the mode of commute to work, through data linkages based on Middle Layer Super Output Areas in England between 20 June 2021 and 20 February 2022. We estimated population-level associations between potential risk factors and workplace outbreaks, adjusting for plausible confounders identified using a directed acyclic graph. RESULTS: For most industries, increased physical proximity in the workplace was associated with increased risk of COVID-19 outbreaks, while increased vaccination was associated with reduced risk. Employee 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 outbreak risk. A higher proportion of employees in the 60-64 age group was associated with reduced outbreak risk. There were significant associations between gender, work commute modes and staff contract type with outbreak 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 outbreaks, 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.
Assuntos
COVID-19 , Saúde Ocupacional , Humanos , COVID-19/epidemiologia , Local de Trabalho , Indústrias , Surtos de DoençasRESUMO
Reacting to a pandemic influenza outbreak will require the mass distribution of vaccine, when available, which will require county health departments to set up and operate one or more mass vaccination clinics, also known as points of dispensing (PODs). Carefully planning these PODs before an event occurs is a difficult but important job. First, this article describes a tool--the Clinic Planning Model Generator computer program--designed to help public health agencies evaluate and make adjustments to their POD plans. The Clinic Planning Model Generator was built on data from a smallpox exercise and other biological agent POD exercises. Second, this article demonstrates the application of the Clinic Planning Model Generator through an example pandemic influenza scenario. This work is the result of an ongoing collaboration between Montgomery County, Maryland's Advanced Practice Center for Public Health Emergency Preparedness and Response, and the Institute for Systems Research at the University of Maryland.