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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.

SummaryThe emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight the primary ports of entry for B.1.1.7 in the US and locations of possible underreporting of B.1.1.7 cases. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Drug-resistant influenza is a significant threat to global public health. Until new antiviral agents with novel mechanisms of action become available, there is a pressing need for alternative treatment strategies with available influenza antivirals. Our aims were to evaluate the antiviral activity of two neuraminidase inhibitors (oseltamivir and zanamivir) as combination therapy against H1N1 influenza A viruses, as these agents bind to the neuraminidase active site differently: oseltamivir requires a conformational change for binding whereas zanamivir does not. We performed pharmacodynamic studies in the hollow fiber infection model (HFIM) system with oseltamivir (75 mg Q12h, t1/2: 8 h) and zanamivir (600 mg Q12h, t1/2: 2.5 h), given as mono- or combination therapy, against viruses with varying susceptibilities to oseltamivir and zanamivir. Each antiviral suppressed the replication of influenza strains which were resistant to the other neuraminidase inhibitor, showing each drug does not engender cross-resistance to the other compound. Oseltamivir/zanamivir combination therapy was as effective at suppressing oseltamivir- and zanamivir-resistant influenza viruses and the combination regimen inhibited viral replication at a level that was similar to the most effective monotherapy arm. However, combination therapy offered a clear benefit by preventing the emergence and spread of drug-resistant viruses. These findings demonstrate that combination therapy with two agents that target the same viral protein through distinctly different binding interactions is a feasible strategy to combat resistance emergence. This is a novel finding that may be applicable to other viral and non-viral diseases for which different classes of agents do not exist.

Whole-genome sequencing (WGS) is a newer alternative for tuberculosis (TB) diagnostics and is capable of providing rapid drug resistance profiles while performing species identification and capturing the data necessary for genotyping. Our laboratory developed and validated a comprehensive and sensitive WGS assay to characterize Mycobacterium tuberculosis and other M. tuberculosis complex (MTBC) strains, composed of a novel DNA extraction, optimized library preparation, paired-end WGS, and an in-house-developed bioinformatics pipeline. This new assay was assessed using 608 MTBC isolates, with 146 isolates during the validation portion of this study and 462 samples received prospectively. In February 2016, this assay was implemented to test all clinical cases of MTBC in New York State, including isolates and early positive Bactec mycobacterial growth indicator tube (MGIT) 960 cultures from primary specimens. Since the inception of the assay, we have assessed the accuracy of identification of MTBC strains to the species level, concordance with culture-based drug susceptibility testing (DST), and turnaround time. Species identification by WGS was determined to be 99% accurate. Concordance between drug resistance profiles generated by WGS and culture-based DST methods was 96% for eight drugs, with an average resistance-predictive value of 93% and susceptible-predictive value of 96%. This single comprehensive WGS assay has replaced seven molecular assays and has resulted in resistance profiles being reported to physicians an average of 9 days sooner than with culture-based DST for first-line drugs and 32 days sooner for second-line drugs.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2500 COVID-19 cases associated with this variant have been detected in the US since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response., The SARS-CoV-2 variant B.1.1.7 was introduced to the United States in early December 2020 and soon became established within many communities. The primary points of entry into the US are identified as NY, CA, and FL, and exponential growth in these states resulted in spread to neighboring states.

Background The Wadsworth Center, New York State Department of Health (NYSDOH), conducts routine diagnosis and surveillance of influenza viruses. Whole genome sequencing (WGS) with next generation sequencing (NGS) was initiated to provide more rapid, detailed, thorough, and accurate analysis. Objectives To optimize and implement a method for routine WGS of influenza A viruses. To use WGS to monitor influenza A viruses for reassortment, mutations associated with antiviral resistance and antigenicity changes, as well as those potentially affecting virulence and tropism. Study design Multiple extraction and amplification methods were investigated and optimized for the production of template to be used for NGS. Additionally, software options were considered for data analysis. Initial WGS influenza projects have included the comparison of mixed population sequence data obtained with NGS, Sanger dideoxy sequencing, and pyrosequencing, the comparison of sequences obtained from paired primary/cultured samples, the analysis of sequence changes over several influenza seasons, and phylogenetic analysis. Results Procedures were optimized for extraction and amplification such that WGS could be successfully performed on both cultured isolates and primary specimens. Data is presented on 15 A/H1pdm09 and 44 A/H3N2 samples. Analysis of influenza A viruses identified and confirmed variant and mixed populations affecting antigenicity and antiviral susceptibility in both primary specimens and cultured isolates. Conclusions An influenza A whole genome PCR method has been optimized for the reliable production of template for NGS. The WGS method has been successfully implemented for enhanced comprehensive surveillance and the generation of detailed clinical data on drug resistance and virulence. Data obtained with this method will also aid in future vaccine selection.

Ocular infections caused by human adenovirus (HAdV) are highly contagious. The most severe are usually caused by members of species HAdV-D (types HAdV8, 19, 37, 53, 54, and 56) and can manifest as epidemic keratoconjunctivitis (EKC), often resulting in prolonged impairment of vision. During the early months of 2012, EKC outbreaks occurred in neonatal intensive care units (NICUs) in 3 hospitals in New York State (New York and Suffolk Counties). A total of 32 neonates were affected. For 14 of them, HAdV8 was laboratory-confirmed as the causative agent. Nine healthcare workers were also affected with 3 laboratory-confirmed, HAdV-positive EKC. A fourth EKC outbreak was documented among patients attending a private ophthalmology practice in Ulster County involving a total of 35 cases. Epidemiological linkage between the neonatal intensive care unit outbreaks was demonstrated by molecular typing of virus isolates with restriction enzyme analysis and next generation whole genome sequencing. The strain isolated from the ophthalmology clinic was easily distinguishable from the others by restriction enzyme analysis.