Multiplex Fragment Analysis for Flexible Detection of All SARS-CoV-2 Variants of Concern.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to emerge, and effective tracking requires rapid return of results. Surveillance of variants is typically performed by whole genome sequencing (WGS), which can be financially prohibitive and requires specialized equipment and bioinformatic expertise. Genotyping approaches are rapid methods for monitoring SARS-CoV-2 variants but require continuous adaptation. Fragment analysis may represent an approach for improved SARS-CoV-2 variant detection. METHODS: A multiplex fragment analysis approach (CoVarScan) was validated using PCR targeting variants by size and fluorescent color. Eight SARS-CoV-2 mutational hot spots in variants of concern (VOCs) were targeted. Three primer pairs (recurrently deleted region [RDR] 1, RDR2, and RDR3-4) flank RDRs in the S-gene. Three allele-specific primers target recurrent spike receptor binding domain mutants. Lastly, 2 primer pairs target recurrent deletions or insertions in ORF1A and ORF8. Fragments were resolved and analyzed by capillary electrophoresis (ABI 3730XL), and mutational signatures were compared to WGS results. RESULTS: We validated CoVarScan using 3544 clinical respiratory specimens. The assay exhibited 96% sensitivity and 99% specificity compared to WGS. The limit of detection for the core targets (RDR1, RDR2, and ORF1A) was 5 copies/reaction. Variants were identified in 95% of samples with cycle threshold (CT) <30 and 75% of samples with a CT 34 to 35. Assay design was frozen April 2021, but all subsequent VOCs have been detected including Delta (n = 2820), Mu, (n = 6), Lambda (n = 6), and Omicron (n = 309). Genotyping results are available in as little as 4 h. CONCLUSIONS: Multiplex fragment analysis is adaptable and rapid and has similar accuracy to WGS to classify SARS-CoV-2 variants.

Harnessing the Electronic Health Record and Computerized Provider Order Entry Data for Resource Management During the COVID-19 Pandemic: Development of a Decision Tree.

BACKGROUND: The COVID-19 pandemic has resulted in shortages of diagnostic tests, personal protective equipment, hospital beds, and other critical resources. OBJECTIVE: We sought to improve the management of scarce resources by leveraging electronic health record (EHR) functionality, computerized provider order entry, clinical decision support (CDS), and data analytics. METHODS: Due to the complex eligibility criteria for COVID-19 tests and the EHR implementation-related challenges of ordering these tests, care providers have faced obstacles in selecting the appropriate test modality. As test choice is dependent upon specific patient criteria, we built a decision tree within the EHR to automate the test selection process by using a branching series of questions that linked clinical criteria to the appropriate SARS-CoV-2 test and triggered an EHR flag for patients who met our institutional persons under investigation criteria. RESULTS: The percentage of tests that had to be canceled and reordered due to errors in selecting the correct testing modality was 3.8% (23/608) before CDS implementation and 1% (262/26,643) after CDS implementation (P<.001). Patients for whom multiple tests were ordered during a 24-hour period accounted for 0.8% (5/608) and 0.3% (76/26,643) of pre- and post-CDS implementation orders, respectively (P=.03). Nasopharyngeal molecular assay results were positive in 3.4% (826/24,170) of patients who were classified as asymptomatic and 10.9% (1421/13,074) of symptomatic patients (P<.001). Positive tests were more frequent among asymptomatic patients with a history of exposure to COVID-19 (36/283, 12.7%) than among asymptomatic patients without such a history (790/23,887, 3.3%; P<.001). CONCLUSIONS: The leveraging of EHRs and our CDS algorithm resulted in a decreased incidence of order entry errors and the appropriate flagging of persons under investigation. These interventions optimized reagent and personal protective equipment usage. Data regarding symptoms and COVID-19 exposure status that were collected by using the decision tree correlated with the likelihood of positive test results, suggesting that clinicians appropriately used the questions in the decision tree algorithm.

Application, Verification, and Implementation of SARS-CoV-2 Serologic Assays with Emergency Use Authorization.

Interest continues to grow regarding the role of serologic assays for the detection of prior infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The U.S. Food and Drug Administration (FDA) has granted emergency use authorization (EUA) status to many SARS-CoV-2 serologic assays. In this document, expert recommendations from clinical microbiologist members of the American Society for Microbiology (ASM) concerning detailed verification strategies for SARS-CoV-2 serologic assays with FDA EUA are provided, as are insights into assay limitations and reporting considerations for laboratories. Assessments concerning single-antibody and multiantibody isotype detection assays, which may provide either differentiated or nondifferentiated (i.e., total antibody) antibody class results, are addressed. Additional considerations prior to assay implementation are also discussed, including biosafety, quality control, and proficiency testing strategies. As the landscape of SARS-CoV-2 serologic testing is rapidly changing, this document provides updated guidance for laboratorians on application of these assays.

Clinical Validation of a SARS-CoV-2 Real-Time Reverse Transcription PCR Assay Targeting the Nucleocapsid Gene.

BACKGROUND: Detection of SARS-CoV-2 viral RNA is important for the diagnosis and management of COVID-19. METHODS: We present a clinical validation of a reverse transcription PCR (RT-PCR) assay for the SARS-CoV-2 nucleocapsid (N1) gene. Off-board lysis on an automated nucleic acid extraction system was optimized with endemic coronaviruses (OC43 and NL63). Genomic RNA and SARS-CoV-2 RNA in a recombinant viral protein coat were used as control materials and compared for recovery from nucleic acid extraction. RESULTS: Nucleic acid extraction showed decreased recovery of endemic Coronavirus in vitro transcribed RNA (NL63) compared with attenuated virus (OC43). SARS-CoV-2 RNA had more reliable recovery from extraction through amplification than genomic RNA. Recovery of genomic RNA was improved by combining lysis buffer with clinical matrix before adding RNA. The RT-PCR assay demonstrated 100% in silico sensitivity and specificity. The accuracy across samples was 100% (75 of 75). Precision studies showed 100% intra-run, inter-run, and inter-technologist concordance. The limit of detection was 264 copies per milliliter (estimated 5 copies per reaction; 35.56 mean threshold cycle value). CONCLUSIONS: This SARS-CoV-2 assay demonstrates appropriate characteristics for use under an Emergency Use Authorization. Endemic coronavirus controls were useful in optimizing the extraction procedure. In the absence of live or attenuated virus, recombinant virus in a protein coat is an appropriate control specimen type for assay validation during a pandemic.