Evaluation of sample pooling for the detection of SARS-CoV-2 in a resource-limited setting, Dominican Republic.

Enferm Infecc Microbiol Clin (Engl Ed)

Instituto de Medicina Tropical & Salud Global, Universidad Iberoamericana (UNIBE), Santo Domingo, Dominican Republic. Electronic address:

Published: July 2021

AI Article Synopsis

  • COVID-19 poses a global health risk, and RT-PCR testing is the standard method for diagnosis, but sample pooling can help optimize resources by reducing workloads and reagent shortages in labs, especially in resource-limited settings.
  • The study evaluated SARS-CoV-2 detection by pooling samples, creating 210 pools from 245 samples, each containing a positive case to test the efficiency of this method.
  • Findings suggest that pooling up to three samples for SARS-CoV-2 testing is effective without compromising the sensitivity of RT-PCR, while larger pools may lead to a higher chance of false negatives.

Article Abstract

Introduction: COVID-19 is a worldwide public health threat. Diagnosis by RT-PCR has been employed as the standard method to confirm viral infection. Sample pooling testing can optimize the resources by reducing the workload and reagents shortage, and be useful in laboratories and countries with limited resources. This study aims to evaluate SARS-CoV-2 detection by sample pooling testing in comparison with individual sample testing.

Materials And Methods: We created 210 pools out of 245 samples, varying from 4 to 10 samples per pool, each containing a positive sample. We conducted detection of SARS-CoV-2-specific RdRp/E target sites.

Results: Pooling of three samples for SARS-CoV-2 detection might be an efficient strategy to perform without losing RT-PCR sensitivity.

Conclusions: Considering the positivity rate in Dominican Republic and that larger sample pools have higher probabilities of obtaining false negative results, the optimal sample size to perform a pooling strategy shall be three samples.

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Source
http://dx.doi.org/10.1016/j.eimc.2021.07.004DOI Listing

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