MATHEMATICAL MODELING APPROACHES FOR MANAGING INFECTIOUS DISEASE EXPOSURE IN THE WORKPLACE

Although workers in a variety of industries are at increased risk for exposure to infectious agents, traditional occupational exposure assessment and risk management methods focus primarily on chemical hazards. Much less has been done to estimate exposures to infectious agents in the workplace. Given the cost and difficulty in interpreting sampling data, a prudent way to assess worker exposures is through mathematical modeling. We developed a suite of models that will estimate occupational exposures to infectious agents, allowing occupational health and safety professionals to implement risk management, prevention, and control strategies at the appropriate level. To develop and demonstrate the use of these models, we focused on concentrated animal feeding operations (CAFOs) as a source of Staphylococcus aureus (S. aureus) exposure to workers. First, we developed a model for worker exposure by incorporating well-established inhalation models of exposure with fomite transmission and particle dynamics models. The occupational exposure model accounts for all significant determinants of worker exposure, which allows us to identify effective interventions and quantify the potential reduction in exposure. Next, we developed a model of changes in worker nasal carriage status of S. aureus and used it to make predictions on nasal carriage status over time. In this model, we consider the impact of mask use on predicted nasal carriage status of the population of workers in the long run. Finally, we used models to make predictions about PPE needs during the COVID-19 Pandemic. We determined the expected impact of changes in community transmission levels on facility level PPE needs. This suite of models can be used to evaluate the effectiveness of proposed control measures, including adjusting ventilation parameters, implementing additional biosecurity measures, and increasing the use of N-95 respirators and other personal protective equipment. We hypothesize risk management strategies designed to address pathogens in the workplace will significantly reduce exposure to workers, household members, and communities