Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

Area of Science:

• Public Health
• Operations Research
• Biotechnology

Background:

• COVID-19 testing capacity limitations and long wait times hindered effective case isolation.
• Operational challenges, including supply and staffing shortages, exacerbated testing bottlenecks.
• The need for rapid scale-up of testing was critical for pandemic mitigation.

Purpose of the Study:

• To utilize operational simulations for rapid scale-up of COVID-19 testing capacity.
• To identify process bottlenecks and evaluate interventions for expanding testing capabilities.
• To estimate resource requirements and the impact of demand variability on laboratory performance.

Main Methods:

• Developed discrete event simulation models for RT-PCR testing processes at a university testing center.
• Analyzed process steps to pinpoint bottlenecks and simulated 'what-if' scenarios for capacity expansion.
• Evaluated interventions, such as using virucidal collection medium, to streamline the testing workflow.

Main Results:

• Simulation models identified critical bottlenecks in the RT-PCR testing workflow.
• Implementing a virucidal collection medium eliminated a time-consuming 'deswabbing' step, nearly doubling testing capacity.
• Models estimated minimum equipment and personnel needed for various target capacities and assessed demand variability impacts.

Conclusions:

• Simulation modeling is an effective tool for optimizing SARS-CoV-2 RT-PCR testing operations.
• High-leverage process changes can significantly increase testing capacity at feasible costs.
• This approach aids preparedness planners in identifying solutions for efficient testing scale-up.