Introduction: Pooled testing is a cost-effective approach to increasing testing capacity during pandemics. This study analysed the effectiveness of pooling of samples and RNA extracts for the detection of SARS-CoV-2 by real time RT-PCR.Methods: Twenty SARS-CoV-2 positive samples with Ct value of 25–35 and 60 known negative samples based on initial PCR results were used for this study. The samples were used to prepare 2-, 4- and 8-fold pooled samples prior to extraction. The RNA extracts of a further 10 PCR positive samples were pooled to prepare 2-, 4- and 8-fold RNA extract pools. The Ct values of neat samples and pooled samples were compared using the paired t-test with a 95% confidence interval. The same was done for the neat RNA extracts and the extract pools.Results: The detection capacity was considerably lower when the pool size was increased from 2- to 8-fold in sample pooling, whereas pools of RNA extracts showed 100% detection from 2- to 8-fold dilution. The increase in Ct value of 2-, 4- and 8-fold sample dilutions were 1.69 ± 0.78, 3.84 ± 1.47 and 8.98 ± 2.25, respectively (P < 0.0001). However, there was a small rise in the Ct value of 2-, 4- and 8-fold extract pools (1.01 ± 0.38, 2.18 ± 0.82 and 3.05 ± 0.77, respectively).Conclusions: Large scale screening of asymptomatic individuals for SARS-CoV-2 can be maximised with optimal use of resources by 2- or 4-fold pooling of samples or 4- or 8-fold pooling of RNA extracts without significantly compromising the detection capacity.

A comprehensive analysis of the molecular epidemiology of SARS-CoV-2 in the Kandy District of Sri Lanka from November 2020 to March 2022 was conducted to address the limited genomic surveillance data available across the country. The study investigated the circulating SARS-CoV-2 lineages, their temporal dynamics, and the associated mutational profiles in the study area. A total of 280 SARS-CoV-2-positive samples were selected, and 252 complete genomes were successfully sequenced using Oxford Nanopore Technology. Lineage classification was performed using the EPI2ME tool, while phylogenetic relationships were inferred through maximum likelihood and time-scaled phylogenetic trees using IQ-TREE2 and BEAST, respectively. Amino acid substitutions were analyzed to understand lineage-specific mutation patterns. Fifteen SARS-CoV-2 lineages were identified, and of those B.1.411 (36%) was the most prevalent, followed by Q.8 (21%), AY.28 (9.5%), and the Delta and Omicron variants. The lineage distribution showed a temporal shift from B.1.411 to Alpha, Delta, and finally the Omicron, mirroring the global trends. Time to the most recent common ancestor analyses provided estimates for the introduction of major variants, while mutation analysis revealed the widespread occurrence of D614G in the spike protein and lineage-specific mutations across structural, non-structural, and accessory proteins.Detection of the Epsilon variant (absent in other national-level studies) in November 2020, highlighted the regional heterogeneity viral spread. This study emphasizes the importance of localized genomic surveillance to capture the true diversity and evolution of SARS-CoV-2, to facilitate containment strategies in resource-limited settings.