Within-laboratory SARS-CoV-2 real time PCR testing operations in Nepal: a simulation-based analysis

Background COVID-19 has challenged entire health systems, including laboratories. To address the increasing demand for tests to inform the epidemiology of the disease and for case management purposes, many countries made significant investments to rapidly expand laboratory capacity for detecting SARS-CoV-2. In this study, we used a simulated laboratory environment, based on a model of operating laboratories in Nepal, to identify opportunities for improvement.

Methods We developed a discrete event simulation (DES) model, based on data from and in collaboration with Nepali health authorities, to analyse laboratory operations in Nepal. We used a series of “what-if” scenarios under different levels of testing demand and staffing to investigate bottlenecks in the processing of COVID-19 samples in a simulated laboratory environment, assess the impact of potential reagent shortages and increased automation, and more generally, explore the key factors that drive the performance and resilience of the testing system.

Findings Suboptimal staff allocation and scheduling can limit the timely return of laboratory results; however, better staff allocation can mitigate bottlenecks and reduce the impact of reagent shortages. For example, when the demand is 720 samples per day and seven staff members are on duty, adding one additional staff member improves reporting time (reduction from 48 h to approximately 32 h). However, changes in scheduling can increase the average time to return the results to over 200 h. A one-day reagent shortage appears to have minimal impact, but a delay of five days significantly increases the reporting time, reaching nearly 150 h. Increasing automation or better process coordination for sample registration can also lead to better performance, reducing the average reporting time from over 60 h to just under 24 h.

Interpretation Our findings identify important bottlenecks and challenges, along with ways to address them, and thus provide important lessons for improving disease testing operations for this and future pandemics.

Uncontrolled Keywords

• COVID-19
• SARS-CoV-2
• PCR
• laboratory capacity assessment
• discrete event simulation (DES)
• sensitivity analysis