Unrecognized introductions of SARS-CoV-2 into the US state of Georgia shaped the early epidemic.

In early 2020, as diagnostic and surveillance responses for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ramped up, attention focused primarily on returning international travelers. Here, we build on existing studies characterizing early patterns of SARS-CoV-2 spread within the USA by analyzing detailed clinical, molecular, and viral genomic data from the state of Georgia through March 2020. We find evidence for multiple early introductions into Georgia, despite relatively sparse sampling. Most sampled sequences likely stemmed from a single or small number of introductions from Asia three weeks prior to the state's first detected infection. Our analysis of sequences from domestic travelers demonstrates widespread circulation of closely related viruses in multiple US states by the end of March 2020. Our findings indicate that the exclusive focus on identifying SARS-CoV-2 in returning international travelers early in the pandemic may have led to a failure to recognize locally circulating infections for several weeks and point toward a critical need for implementing rapid, broadly targeted surveillance efforts for future pandemics.

Single-Amplicon Multiplex Real-Time Reverse Transcription-PCR with Tiled Probes To Detect SARS-CoV-2 spike Mutations Associated with Variants of Concern.

To provide an accessible and inexpensive method to surveil for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations, we developed a multiplex real-time reverse transcription-PCR (rRT-PCR) assay, the Spike single-nucleotide polymorphism (SNP) assay, to detect specific mutations in the spike receptor binding domain. A single primer pair was designed to amplify a 348-bp region of spike, and probes were initially designed to detect K417, E484K, and N501Y. The assay was evaluated using characterized variant sample pools and residual nasopharyngeal samples. Variant calls were confirmed by SARS-CoV-2 genome sequencing in a subset of samples. Subsequently, a fourth probe was designed to detect L452R. The lower limit of 95% detection was 2.46 to 2.48 log10 genome equivalents (GE)/ml for the three initial targets (∼1 to 2 GE/reaction). Among 253 residual nasopharyngeal swabs with detectable SARS-CoV-2 RNA, the Spike SNP assay was positive in 238 (94.1%) samples. All 220 samples with threshold cycle (CT) values of <30 for the SARS-CoV-2 N2 target were detected, whereas 18/33 samples with N2 CT values of ≥30 were detected. Spike SNP results were confirmed by sequencing in 50/50 samples (100%). Addition of the 452R probe did not affect performance for the original targets. The Spike SNP assay accurately identifies SARS-CoV-2 mutations in the receptor binding domain, and it can be quickly modified to detect new mutations that emerge.

Metagenomic Sequencing To Detect Respiratory Viruses in Persons under Investigation for COVID-19.

Broad testing for respiratory viruses among persons under investigation (PUIs) for SARS-CoV-2 has been performed inconsistently, limiting our understanding of alternative viral infections and coinfections in these patients. RNA metagenomic next-generation sequencing (mNGS) offers an agnostic tool for the detection of both SARS-CoV-2 and other RNA respiratory viruses in PUIs. Here, we used RNA mNGS to assess the frequencies of alternative viral infections in SARS-CoV-2 RT-PCR-negative PUIs (n = 30) and viral coinfections in SARS-CoV-2 RT-PCR-positive PUIs (n = 45). mNGS identified all viruses detected by routine clinical testing (influenza A [n = 3], human metapneumovirus [n = 2], and human coronavirus OC43 [n = 2], and human coronavirus HKU1 [n = 1]). mNGS also identified both coinfections (1, 2.2%) and alternative viral infections (4, 13.3%) that were not detected by routine clinical workup (respiratory syncytial virus [n = 3], human metapneumovirus [n = 1], and human coronavirus NL63 [n = 1]). Among SARS-CoV-2 RT-PCR-positive PUIs, lower cycle threshold (CT ) values correlated with greater SARS-CoV-2 read recovery by mNGS (R2, 0.65; P < 0.001). Our results suggest that current broad-spectrum molecular testing algorithms identify most respiratory viral infections among SARS-CoV-2 PUIs, when available and implemented consistently.