SARS-CoV-2 genomic surveillance using self-collected saliva specimens during occupational testing programs

在职业检测项目中利用自采集唾液样本进行SARS-CoV-2基因组监测

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Abstract

Continually emerging SARS-CoV-2 variants pose challenges to clinical and public health interventions, necessitating sustainable approaches to real-time variant monitoring. This case study describes an innovative SARS-CoV-2 screening and surveillance program that demonstrates the utility of sequencing-based variant monitoring using self-collected saliva specimens. We conducted saliva-based SARS-CoV-2 screening in occupational settings in Omaha, Nebraska from December 2021 through November 2022. 8,372 saliva specimens collected from 1,480 participants were tested for SARS-CoV-2 RNA by extraction-free PCR, with 334 positive samples referred for whole-genome sequencing analysis. Program utilization, quality metrics, and sequencing outputs were compared across sites. Specimen quality was high across program settings, demonstrating the suitability of self-collected saliva specimens for PCR and genomic surveillance testing. Virus RNA sequencing successfully determined the variant strain in 83 and 67% of SARS-CoV-2-positive saliva samples collected in two program settings, demonstrating the successful integration of SARS-CoV-2 sequencing for variant determination into screening programs in occupational settings using self-collected saliva with an extraction-free qRT-PCR testing method. We further demonstrate that the sensitivity and efficiency of variant analysis is dependent on the PCR cycle threshold (Ct) cutoff of the diagnostic assay virus gene target. Use of an optimized Ct value cutoff for sequencing referral is recommended. Community-based saliva testing programs can be utilized to enhance variant monitoring, and could be considered in the risk identification of other respiratory infections. This approach offers the advantages of a non-invasive specimen collection, no need for supervised collection by a healthcare worker, supply chain resiliency, distributable access, and scalability.

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