Keywords: simulation modeling, anyLogic, workload planning, laboratory production, COVID-19 pandemic
UDC 004.94
DOI: 10.26102/2310-6018/2026.55.4.003
The sharp increase in the burden on healthcare systems during the COVID-19 pandemic has shown the inefficiency of traditional methods of calculating labor productivity based on mathematical formulas. They do not take into account the dynamics of work processes, problems in the planning of labor resources, equipment and areas. This leads to inefficient load distribution, especially when, using the example of clinical laboratories, it became necessary to process thousands of samples for PCR testing every day. The aim of the research is to develop and analyze a method for workload planning using simulation modeling in AnyLogic, which allows visualizing and optimizing laboratory processes. The tasks include an analysis of existing approaches, a description of the methodology, application using the example of a PCR laboratory, and an assessment of the benefits in a pandemic. The proposed approach includes timekeeping of technological processes, data collection in tabular form, and creation of a digital laboratory model to identify bottlenecks, equipment and personnel downtime. Using the example of a PCR laboratory, the possibility of optimizing resources, calculating maximum productivity, and justifying purchases is demonstrated. The method makes it possible to increase the efficiency of laboratory production in situations of unpredictable demand, minimizing the risks of disruptions and financial losses.
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Keywords: simulation modeling, anyLogic, workload planning, laboratory production, COVID-19 pandemic
For citation: Donsckaia A.R., Lomakin A.S., Zubkov A.V., Orlov D.V., Nazarov N.O., Kovaleva E.S. Simulation model for managing laboratory staff workload during a pandemic using the AnyLogic platform. Modeling, Optimization and Information Technology. 2026;14(4). URL: https://moitvivt.ru/ru/journal/article?id=2203 DOI: 10.26102/2310-6018/2026.55.4.003 (In Russ).
© Donsckaia A.R., Lomakin A.S., Zubkov A.V., Orlov D.V., Nazarov N.O., Kovaleva E.S. Статья опубликована на условиях лицензии Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NS 4.0)Received 16.02.2026
Revised 25.03.2026
Accepted 03.04.2026