Combining genomic and epidemiological data to compare the transmissibility of SARS-CoV-2 variants Alpha and Iota.

SARS-CoV-2 variants shaped the second year of the COVID-19 pandemic and the discourse around effective control measures. Evaluating the threat posed by a new variant is essential for adapting response efforts when community transmission is detected. In this study, we compare the dynamics of two variants, Alpha and Iota, by integrating genomic surveillance data to estimate the effective reproduction number (Rt) of the variants. We use Connecticut, United States, in which Alpha and Iota co-circulated in 2021. We find that the Rt of these variants were up to 50% larger than that of other variants. We then use phylogeography to show that while both variants were introduced into Connecticut at comparable frequencies, clades that resulted from introductions of Alpha were larger than those resulting from Iota introductions. By monitoring the dynamics of individual variants throughout our study period, we demonstrate the importance of routine surveillance in the response to COVID-19

Detection and Genetic Characterization of Adenovirus Type 14 Strain in Students with Influenza-Like Illness, New York, USA, 2014–2015

During the 2014–15 influenza season, 13/168 respiratory samples from students with influenza-like illness (ILI) at a college in New York, USA, were positive for human adenovirus (HAdV); 4/13 samples were positive for HAdV-B14p1. During influenza season, HAdV should be included in the differential diagnostic panel used to determine the etiology of ILI

Influenza Antiviral Resistance Testing in New York and Wisconsin, 2006 to 2008: Methodology and Surveillance Data▿ †

The need for effective influenza antiviral susceptibility surveillance methods has increased due to the emergence of near-universal adamantane resistance in influenza A/H3N2 viruses during the 2005-2006 season and the appearance of oseltamivir resistance in the influenza A/H1N1 virus subtype during the 2007-2008 season. The two classes of influenza antivirals, the neuraminidase inhibitors (NAIs) and the adamantanes, are well characterized, as are many mutations that can confer resistance to these drugs. Adamantane resistance is imparted mainly by a S31N mutation in the matrix gene, while NAI resistance can result from a number of mutations in the neuraminidase gene. During the 2007-2008 season, a neuraminidase mutation (H274Y) conferring resistance to the NAI oseltamivir emerged worldwide in the A/H1N1 virus subtype. Surveillance methodology and data from New York (NY) and Wisconsin (WI) for the 2006-2007 and 2007-2008 influenza seasons are presented. We used an existing pyrosequencing method (R. A. Bright et al., Lancet 366:1175-1181, 2005) and a modified version of this method for detection of adamantane resistance mutations. For NAI resistance mutation detection, we used a mutation-specific pyrosequencing technique and developed a neuraminidase gene dideoxy sequencing method. Adamantane resistance in the A/H3N2 virus samples was 100% for 2007-2008, similar to the 99.8% resistance nationwide as reported by the CDC. Adamantane resistance was found in only 1.2% of NY and WI A/H1N1 virus samples, compared to that found in 10.8% of samples tested nationwide as reported by the CDC. Influenza A/H1N1 virus H274Y mutants were found in 11.1% of NY samples for 2007-2008, a level comparable to the 10.9% nationwide level reported by the CDC; in contrast, mutants were found in 17.4% of WI samples. These results indicate the need for regional influenza antiviral surveillance

Implementation of a high-throughput whole genome sequencing approach with the goal of maximizing efficiency and cost effectiveness to improve public health

ABSTRACTThis manuscript describes the development of a streamlined, cost-effective laboratory workflow to meet the demands of increased whole genome sequence (WGS) capacity while achieving mandated quality metrics. From 2020 to 2021, the Wadsworth Center Bacteriology Laboratory (WCBL) used a streamlined workflow to sequence 5,743 genomes that contributed sequence data to nine different projects. The combined use of the QIAcube HT, Illumina DNA Prep using quarter volume reactions, and the NextSeq allowed the WCBL to process all samples that required WGS while also achieving a median turn-around time of 7 days (range 4 to 10 days) and meeting minimum sequence quality requirements. Public Health Laboratories should consider implementing these methods to aid in meeting testing requirements within budgetary restrictions.IMPORTANCEPublic Health Laboratories that implement whole genome sequencing (WGS) technologies may struggle to find the balance between sample volume and cost effectiveness. We present a method that allows for sequencing of a variety of bacterial isolates in a cost-effective manner. This report provides specific strategies to implement high-volume WGS, including an innovative, low-cost solution utilizing a novel quarter volume sequencing library preparation. The methods described support the use of high-throughput DNA extraction and WGS within budgetary constraints, strengthening public health responses to outbreaks and disease surveillance

Rapid Whole-Genome Sequencing for Surveillance of Salmonella enterica Serovar Enteritidis

For Salmonella enterica serovar Enteritidis, 85% of isolates can be classified into 5 pulsed-field gel electrophoresis (PFGE) types. However, PFGE has limited discriminatory power for outbreak detection. Although whole-genome sequencing has been found to improve discrimination of outbreak clusters, whether this procedure can be used in real-time in a public health laboratory is not known. Therefore, we conducted a retrospective and prospective analysis. The retrospective study investigated isolates from 1 confirmed outbreak. Additional cases could be attributed to the outbreak strain on the basis of whole-genome data. The prospective study included 58 isolates obtained in 2012, including isolates from 1 epidemiologically defined outbreak. Whole-genome sequencing identified additional isolates that could be attributed to the outbreak, but which differed from the outbreak-associated PFGE type. Additional putative outbreak clusters were detected in the retrospective and prospective analyses. This study demonstrates the practicality of implementing this approach for outbreak surveillance in a state public health laboratory