Validation of sample pooling strategy in diagnosis of SARS-CoV-2 in Uganda.

Abstract

Millions of people have been impacted by the current SARS-CoV-2 virus pandemic, also known as COVID-19. The World Health Organization (WHO) has suggested extensive testing to distinguish SARS-CoV-2 from other respiratory illnesses so that proper care and management can be provided. In situations like this, effective testing methodologies are required, and pooled testing of samples for the SARS-CoV-2 virus has given a solution for mass COVID-19 screening. When resources are limited, a pooled testing technique can be quite effective, but it has its own set of limitations. When studying highly contagious diseases like COVID-19, these benefits and restrictions must be carefully considered. The rationale is: when specimens from different people are mixed together (pooled) and tested, the test will be negative when everyone is healthy and positive when at least one person is infected. Although, when applying this technique, limit-of-detection, sensitivity, specificity of the assay, and the prevalence of disease in the population are key principles to put in consideration. The aim of the study is to determine the performance of the sample pooling strategy in the detection of SARS-CoV-2 in Uganda. This is a cross-sectional lab-based study. Archived SARS-COV-2 positive clinical samples at different cycle threshold (Ct) values were used in evaluating the pooled testing of nasopharyngeal swabs for SARS-COV-2 by comparing the sensitivity of individual sample testing with 5-and 10-pool sample testing. Median cycle threshold (Ct) values were compared, and the intra-assay repeatability of pooled testing was assessed by measuring variability using coefficient of variation. The sensitivity becomes considerably lower when the samples are pooled. There is an increased false negative reports with larger sample pool size and when the sample viral load is Low. High variability was reported in the repeatability, notably among weak positive samples and when more number of samples are pooled together. COVID−19 being highly infectious and spreading so fast makes the need for testing to remain high, we must precisely evaluate the testing strategy considering the cost and risk of missing even a single positive.