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Development of a program for automated recording of the results of polymerase chain reaction studies in real time in the conditions of a massive intake of biological material during the COVID-19 pandemic

Authors :
Alexey K. Noskov
Angelina Yu. Furina
Alexey S. Vodopyanov
Anton A. Lopatin
Yury N. Khomyakov
R. V. Pisanov
Source :
Epidemiology and Infectious Diseases. 25:102-108
Publication Year :
2020
Publisher :
ECO-Vector LLC, 2020.

Abstract

With regard to the rapid spread of the latest coronavirus infection (COVID-19) in the Russian Federation in 2020, 70 workplaces were organized in Antiplague Center of Rospotrebnadzor and were seconded by specialists from the Rospotrebnadzor research antiplague institutes. However, the round-the-clock three-shift mode of operation significantly complicates the organization and documentation of the studies and increases the risk of errors. Subsequently in Antiplague Center of Rospotrebnadzor, we have conducted the work to automate the most problematic stages of conducting polymerase chain reaction (PCR) studies for the latest coronavirus infection and to develop an algorithm for real-time monitoring of the results. The development of our own software solutions was carried out in Python 3.8.2. The initial data for automation were.xlsx files automatically generated by the thermocycler software and typical tabular templates filled in at the sample analysis and RNA extraction stages. The software we developed consolidated the data into a single file register to detect potential errors simultaneously (e.g., the presence of duplicates, differences in the lists of samples at different stages, etc.). Using the Python scripting language provides cross-platform functionality (the ability to work in any operating system) and allows you to easily and quickly modify the system when changing any parameters or input file structure. Thus, 7 days were spent on the development and commissioning of this software complex, which is particularly important when working in an emergency and high alert mode. Therefore, using the approach we developed made it possible to more quickly detect technical errors, discordant results, and samples requiring re-examination, which in turn reduced the time for issuing results.

Details

ISSN :
24113026 and 15609529
Volume :
25
Database :
OpenAIRE
Journal :
Epidemiology and Infectious Diseases
Accession number :
edsair.doi...........b422411fdb14d56043215f55a28ed378
Full Text :
https://doi.org/10.17816/eid46555