Evidence map›Paper›PMID 37262051›Full record

ArticlePLOS global public health2023

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

Asghar Nasir, Uzma Bashir Aamir, Akbar Kanji, Ali Raza Bukhari, Zeeshan Ansar, Najia Karim Ghanchi, Kiran Iqbal Masood, Azra Samreen, Nazneen Islam, Samina Ghani and 4 more

Abstract read
In one paragraph

Article in PLOS global public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Asghar NasirDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Uzma Bashir AamirWorld Health Organization, Islamabad, Pakistan.
Akbar KanjiDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Ali Raza BukhariDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Zeeshan AnsarDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Najia Karim GhanchiDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Kiran Iqbal MasoodDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Azra SamreenDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Nazneen IslamDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
Samina GhaniDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.
M Asif SyedDepartment of Health, Government of Sindh, Karachi, Pakistan.
Mansoor WassanDepartment of Health, Government of Sindh, Karachi, Pakistan.
Syed Faisal MahmoodDepartment of Medicine, The Aga Khan University, Karachi, Pakistan.ORCID https://orcid.org/0000-0002-3390-7659
Zahra HasanDepartment of Pathology and Laboratory Medicine, Aga Khan University, Karachi, Pakistan.ORCID https://orcid.org/0000-0001-7580-372X

Funding

World Health Organization 001
6 · The paper itself

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.

Identifiers

PMID37262051
PMCPMC10234525

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.