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A reduction of the number of assays and turnaround time by optimizing polymerase chain reaction (PCR) pooled testing for SARS-CoV-2.

Christos PerivolaropoulosVasiliki Vlacha
Published in: Journal of medical virology (2021)
Early detection of the severe acute respiratory syndrome coronavirus 2 infection can decrease the spread of the disease and provide therapeutic options promptly in affected individuals. However, the diagnosis by reverse-transcription polymerase chain reaction is costly and time-consuming. Several methods of group testing have been developed to overcome this problem. The proposed strategy offers optimization of group testing according to the available resources by decreasing not only the number of the assays but also the turnaround time. The initial classification of the samples would be done according to the intention of testing defined as diagnostic or screening/surveillance, achieving the best possible homogeneity. The proposed stratification of pooling is based on branching (divisions) and depth (levels of re-pooling) of the original group in association with the estimated probability of a positive sample. The dilutional effect of the grouped samples has also been considered. The margins of minimum and maximum conservation of assays of pooled specimens are calculated and the optimum strategy can be selected in association with the probability of positive samples in the original group. This algorithm intends to be a useful tool for group testing offering a choice of strategies according to the requirements.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • high throughput
  • machine learning
  • deep learning
  • randomized controlled trial
  • coronavirus disease
  • single cell