Fig. 1. Example of a swab grouping with transposition-based replication. Photo credit: National Research University Higher School of Economics
Researchers Mario Guarracino from the HSE Laboratory of Algorithms and Technologies for Network Analysis in Nizhny Novgorod and Julius Žilinskas and Algirdas Lančinskas from Vilnius University have proposed a new test method for COVID-19. With this group method, results can be obtained 13 times faster for each sample compared to individual tests. The research paper was published in the journal Scientific Reports.
The COVID-19 pandemic has already affected millions of people from over 200 countries. The rapid spread of the virus has shown how quickly such infections can spread in today’s globalized world. At the beginning of the pandemic, when little was known about the virus and vaccines had not yet been developed, the only way to slow its spread was by restricting the mobility of the population. Almost everyone around the world went through various locks and phases of isolation. If large groups of people can be tested quickly, the restrictions can be less stringent and at the same time more effective, believe the authors of the paper “Pooled Testing with Replication as a Mass Testing Strategy for the COVID-19 Pandemics”.
Current COVID-19 test solutions are based on extracting RNA from patients using oropharyngeal and nasopharyngeal swabs and then testing with real-time PCR for the presence of specific RNA filaments that identify the virus. The speed of this approach is limited by the availability of reactants, trained technicians, and laboratories.
One way to speed up the testing process is to perform group tests, in which the swabs from several patients are pooled and tested. The swabs from groups that give a positive result are then tested individually to identify specific COVID-19 positive patients. This approach helps reduce the number of tests (depending on the spread of the disease) by twice or more for each swab compared to individual tests.
Fig. 2. Example of swab grouping using the OptReplica method. Photo credit: National Research University Higher School of Economics
For example, suppose 96 samples should be tested and pools of up to 12 samples are possible. 96 tests are required for individual tests. In the case of pool tests, 8 pools with 12 samples are taken and tests are carried out. If the result of a pool is positive, an additional 12 individual tests are required. If two or three groups give a positive result, 24 or 36 additional tests are required which, along with the first eight tests, means a reduction in the number of tests from two to five times that of individual tests.
The researchers believe that the number of tests can be reduced by optimizing the group size, taking into account the total number of swabs and the projected number of people infected. As the number of infected people increases, the possibility of saving swabs decreases, but with an incidence of 100 positive samples per 1,000 it is still around 40% and with an incidence of 200 per 1,000 it is still around 18%.
There are ways to optimize group tests, e.g. B. Selecting the optimal group size based on the total number of swabs and the projected extent of disease spread. Another is the binary split method, where a positive group is split in half and retested until individual positive smears are detected. However, the second method is very time consuming, which makes it less attractive during a pandemic.
In order to optimize the group tests, a transposition-based replication is also used: After grouping the swabs, the researchers form additional control groups from the same swabs and test them together with the main groups. This helps further reduce the number of tests, and when disease levels are low it also helps identify positive swabs in one step, which speeds up the tests significantly.
Fig. 3. Reducing the number of tests using transposition-based replication (dotted line) and OptReplica (solid line) with optimal group size, depending on the incidence of disease, testing a sample of 96 swabs (blue) and 384 swabs (red). Photo credit: National Research University Higher School of Economics
However, this method does not allow experimentation with group sizes to determine the optimal group size under certain conditions. Researchers from HSE University and Vilnius University suggested OptReplica technology, which uses a more sophisticated algorithm to group swabs into key and control groups and help reduce the number of control groups. In addition, the algorithm helps calculate the optimal group size for the current number of swabs and the predicted extent of disease spread.
The authors conducted experimental studies on samples of 96 and 384 swabs, performed 100 randomized tests for each sample size, and compared the effectiveness of transposition-based replication and the OptReplica method for different disease incidence levels. The studies have shown that OptReplica is more effective than transposition-based replication when the optimal group size is selected. In low-incidence cases, using OptReplica can provide a 13-fold average reduction in tests compared to single tests with no time lag.
“Our simulations actually show that using this optimization replication strategy is always beneficial and that even if the spread of the disease is high (10% or 20% of positive results in the population) we can still compete with the individual testing strategy,” he explained to Mario Guarracino, Chief Research Fellow of the Laboratory for Algorithms and Technologies for Network Analysis.
The authors of the new technology propose to use it for asymptomatic populations with a seemingly low incidence of coronavirus cases, to detect the infected people at maximum speed and with a minimum number of tests, and to apply the quarantine measures in a timely manner to prevent the spread of the Illness. In regions with disease cases above 50 cases per 1,000 tests, the authors suggest using other methods of group replication or tests without replication.
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Julius Žilinskas et al., Pooled Testing with Replication as a Mass Testing Strategy for the COVID-19 Pandemics, Scientific Reports (2021). DOI: 10.1038 / s41598-021-83104-4
Provided by the National Research University Higher School of Economics
Quote: The group test method developed for COVID-19 (2021, March 24) was accessed on March 24, 2021 from https://medicalxpress.com/news/2021-03-group-method-covid-.html
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