Tracking SARS-CoV-2 variants through pandemic waves using RT-PCR testing in low-resource settings

Abstract

COVID-19 resulted in extensive morbidity and mortality worldwide. SARS-CoV-2 evolved rapidly, with increasing transmission due to Variants of Concern (VOC). Identifying VOC became important but genome submissions from low-middle income countries (LMIC) remained low leading to gaps in genomic epidemiology. We demonstrate the use of a specific mutation RT-PCR based approach to identify VOC in SARS-CoV-2 positive samples through the pandemic in Pakistan. We selected 2150 SARS-CoV-2 PCR positive respiratory specimens tested between April 2021 and February 2022, at the Aga Khan University Hospital Clinical Laboratories, Karachi, Pakistan. Commercially available RT-PCR assays were used as required for mutations in Spike protein (N501Y, A570D, E484K, K417N, L452R, P681R and deletion69_70) to identify Alpha, Beta, Gamma, Delta, and Omicron variants respectively. Three pandemic waves associated with Alpha, Delta and Omicron occurred during the study period. Of the samples screened, VOC were identified in 81.7% of cases comprising mainly; Delta (37.2%), Alpha (29.8%) and Omicron (17.1%) variants. During 2021, Alpha variants were predominant in April and May; Beta and Gamma variants emerged in May and peaked in June; the Delta variant peaked in July and remained predominant until November. Omicron (BA.1) emerged in December 2021 and remained predominant until February 2022. The CT values of Alpha, Beta, Gamma and Delta were all significantly higher than that of Omicron variants (p<0.0001). We observed VOC through the pandemic waves using spike mutation specific RT-PCR assays. We show the spike mutation specific RT-PCR assay is a rapid, low-cost and adaptable for the identification of VOC as an adjunct approach to NGS to effectively inform the public health response. Further, by associating the VOC with CT values of its diagnostic PCR we gain information regarding the viral load of samples and therefore the level of transmission and disease severity in the population.

Fig 1. SARS-CoV-2 PCR positive tests reported by the Aga Khan University Hospital Clinical Laboratories, Karachi between April 2021 and February 2022.

A, The graph depicts the number of SARS-CoV-2 PCR positive respiratory samples reported daily by the AKUH Clinical Laboratories, Karachi, Pakistan. The trend of daily positive cases is depicted with a red dotted trend line.

Fig 2. SARS-CoV-2 variants in Karachi.

Data presented is of 2150 positive SARS-CoV-2 samples tested AKUH for Alpha, Beta, Gamma, Delta, Kappa and Omicron variants. The proportion of each VOC identified is shown by the pie chart for Alpha (n = 90), Beta (n = 168), Gamma (n = 46), Delta (n = 800), Kappa (n = 39) and Omicron (n = 367) variants. Samples which were none of these VOC are classified as Undetermined (n = 640).

Fig 3. The number of each VOC across the study period is shown.

The line graph depicts the number of each VOC; Alpha, Beta, Gamma, Delta, Kappa and Omicron together with undetermined samples which were identified across the study period.

Fig 4. The frequency of VOCs across the study period.

The graph depicts the frequency of each VOC; Alpha, Beta, Gamma, Delta, Kappa and Omicron together with undetermined samples which were identified across the study period.

Fig 5. Higher viral loads of Alpha, Beta and Delta as compared with Omicron variants.

The data represent the CT values of SARS-CoV-2 positive samples selected for VOC testing using specific mutation RT-PCR testing. CT values denote the results of the primary diagnostic SARS-CoV-2 PCR result on the cobas 6800 SARS-CoV-2 Roche assay (orf1ab gene target). Results for Alpha, Beta, Gamma, Delta, Kappa and Omicron variants are represented by a box and whiskers plots with IQR (10–90) and median shown by a horizontal line. Kruskal-Wallis analysis was run to determine significant differences between each VOC (p<0.05). ‘*’, denotes p<0.05 in comparison with CT of Omicron variant using the Mann-Whitney U test.