Purpose: The primary purposes of this work were to (1) develop a quantitative predictive risk assessment model that simulates norovirus disease dynamics, and (2) provide a comparative risk-cost framework to evaluate the efficacy and cost-effectiveness of potential intervention strategies.
Methods: We developed an agent-based model, NorOPTIMAL, that simulates norovirus transmission dynamics and disease in a LTCF. NorOPTIMAL represents interactions among agents (e.g., health care workers), and between agents and the microenvironment (e.g., surfaces, foods). Model parameters were derived through an exhaustive literature review, research conducted by the NoroCORE food safety initiative, and expert judgment. To demonstrate the utility of NorOPTIMAL to inform development of a risk-based food safety plan, a hypothetical case study was created that compared different intervention strategies for reducing foodborne contamination and spread of norovirus.
Results: The notional results from the case study suggest that a multi-option intervention strategy is most cost-effective in reducing disease burden including, for example, adoption of best sanitation practices for areas impacted by a vomiting event, rapid response training to limit residents’ exposure to aerosolized virus particles, and increasing compliance with personal hygiene requirements in the kitchen area.
Significance: This work provides: (1) a mathematical framework for simulating transmission dynamics of norovirus; (2) a teaching tool to learn risk assessment basics in a hands-on simulation environment; and (3) a practical approach to compare proposed intervention strategies and inform the development of an effective food safety plan.