Comparative transmissibility of SARS-CoV-2 variants Delta and Alpha in New England, USA

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant quickly rose to dominance in mid-2021, displacing other variants, including Alpha. Studies using data from the United Kingdom and India estimated that Delta was 40-80% more transmissible than Alpha, allowing Delta to become the globally dominant variant. However, it was unclear if the ostensible difference in relative transmissibility was due mostly to innate properties of Deltas infectiousness or differences in the study populations. To investigate, we formed a partnership with SARS-CoV-2 genomic surveillance programs from all six New England US states. By comparing logistic growth rates, we found that Delta emerged 37-163% faster than Alpha in early 2021 (37% Massachusetts, 75% New Hampshire, 95% Maine, 98% Rhode Island, 151% Connecticut, and 163% Vermont). We next computed variant-specific effective reproductive numbers and estimated that Delta was 58-120% more transmissible than Alpha across New England (58% New Hampshire, 68% Massachusetts, 76% Connecticut, 85% Rhode Island, 98% Maine, and 120% Vermont). Finally, using RT-PCR data, we estimated that Delta infections generate on average [~]6 times more viral RNA copies per mL than Alpha infections. Overall, our evidence indicates that Deltas enhanced transmissibility could be attributed to its innate ability to increase infectiousness, but its epidemiological dynamics may vary depending on the underlying immunity and behavior of distinct populations.

Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 lineages

Emerging SARS-CoV-2 variants have shaped the second year of the COVID-19 pandemic and the public health discourse around effective control measures. Evaluating the public health threat posed by a new variant is essential for appropriately adapting response efforts when community transmission is detected. However, this assessment requires that a true comparison can be made between the new variant and its predecessors because factors other than the virus genotype may influence spread and transmission. In this study, we develop a framework that integrates genomic surveillance data to estimate the relative effective reproduction number (Rt) of co-circulating lineages. We use Connecticut, a state in the northeastern United States in which the SARS-CoV-2 variants B.1.1.7 and B.1.526 co-circulated in early 2021, as a case study for implementing this framework. We find that the Rt of B.1.1.7 was 6-10% larger than that of B.1.526 in Connecticut in the midst of a COVID-19 vaccination campaign. To assess the generalizability of this framework, we apply it to genomic surveillance data from New York City and observe the same trend. Finally, we use discrete phylogeography to demonstrate that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of B.1.1.7 were larger than those resulting from B.1.526 introductions. Our framework, which uses open-source methods requiring minimal computational resources, may be used to monitor near real-time variant dynamics in a myriad of settings.

A two-pronged approach for rapid and high-throughput SARS-CoV-2 nucleic acid testing

Improved molecular screening and diagnostic tools are needed to substantially increase SARS-CoV-2 testing capacity and throughput while reducing the time to receive test results. Here we developed multiplex reverse transcriptase polymerase chain reaction (m-RT-PCR) for detection of SARS-CoV-2 using rapid DNA electrophoresis and alternatively using multiplex viral sequencing (mVseq). For RNA specimens extracted from nasopharyngeal (NP) swabs in viral transport media (VTM), our assays achieved a sensitivity for SARS-CoV-2 detection corresponding to cycle threshold (Ct) of 37.2 based on testing of these specimens using quantitative reverse transcription PCR (RT-qPCR). For NP swab-VTM specimens without prior RNA extraction, sensitivity was reduced to Ct of 31.6, which was due to lower concentration of SARS-CoV-2 genome copies in VTM compared to RNA-extracted samples. Assay turnaround time was 60 minutes using rapid gel electrophoresis, 90 minutes using Agilent Bioanalyzer, and 24-48 hours using Illumina sequencing, the latter of which required a second PCR to produce a sequence-ready library using m-RT-PCR products as the template. Our assays can be employed for high-throughput sequencing-based detection of SARS-CoV-2 directly from a clinical specimen without RNA isolation, while ease-of-use and low cost of the electrophoresis-based readout enables screening, particularly in resource-constrained settings.

Neuroinvasive potential of SARS-CoV-2 revealed in a human brain organoid model

Although COVID-19 is considered to be primarily a respiratory disease, SARS-CoV-2 affects multiple organ systems including the central nervous system (CNS). Yet, there is no consensus whether the virus can infect the brain, or what the consequences of CNS infection are. Here, we used three independent approaches to probe the capacity of SARS-CoV-2 to infect the brain. First, using human brain organoids, we observed clear evidence of infection with accompanying metabolic changes in the infected and neighboring neurons. However, no evidence for the type I interferon responses was detected. We demonstrate that neuronal infection can be prevented either by blocking ACE2 with antibodies or by administering cerebrospinal fluid from a COVID-19 patient. Second, using mice overexpressing human ACE2, we demonstrate in vivo that SARS-CoV-2 neuroinvasion, but not respiratory infection, is associated with mortality. Finally, in brain autopsy from patients who died of COVID-19, we detect SARS-CoV-2 in the cortical neurons, and note pathologic features associated with infection with minimal immune cell infiltrates. These results provide evidence for the neuroinvasive capacity of SARS-CoV2, and an unexpected consequence of direct infection of neurons by SARS-CoV-2.