Enterovirus D68 outbreak detection through a syndromic disease epidemiology network

Meyers, Lindsay; Bard, Jennifer Dien; Galvin, Ben; Nawrocki, Jeff; Niesters, Hubert G. M.; Stellrecht, Kathleen A.; George, Kirsten St.; Daly, Judy A.; Blaschke, Anne J.; Robinson, Christine C.; Wang, Huanyu; Cook, Camille V; Hassan, Ferdaus; Dominguez, Sam R; Pretty, Kristin; Naccache, Samia N.; Olin, Katherine; Althouse, Benjamin M.; Jones, Jay; Ginocchio, Christine C.; Poritz, Mark A.; Leber, Amy; Selvarangan, Rangaraj

doi:10.1016/j.jcv.2020.104262

Cited by 17 publications

(21 citation statements)

References 39 publications

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“…Dynamic tracking of the evolution of the COVID-19 pandemic has been enabled by genomic viral surveillance resources such as Global Initiative on Sharing All Influenza Data (GISAID), the JHU Dashboard, and Nextstrain (https://nextstrain.org/ncov) (Gardy et al, 2015, Meyers et al, 2020, Hadfield et al, 2018. Nevertheless, the fraction of cases that have undergone full-length viral genome sequencing are still low (<0.5% of documented cases), underscoring the need for additional profiling, particularly in global infection epicenters such as NYC.…”

Section: Introductionmentioning

confidence: 99%

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

Butler

Mozsary

Meydan

et al. 2020

Preprint

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The pandemic from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) led to hundreds of thousands of deaths, including >15,000 in New York City (NYC). This pandemic highlighted a pressing clinical and public health need for rapid, scalable diagnostics that can detect SARS-CoV-2 infection, interrogate strain evolution, and map host response in patients. To address these challenges, we designed a fast (30 minute) colorimetric test to identify SARS-CoV-2 infection and simultaneously developed a large-scale shotgun metatranscriptomic profiling platform for nasopharyngeal swabs. Both technologies were used to profile 338 clinical specimens tested for SARS-CoV-2 and 86 NYC subway samples, creating a broad molecular picture of the COVID-19 epidemic in NYC. Our results nominate a novel, NYC-enriched SARS-CoV-2 subclade, reveal specific host responses in ACE pathways, and find medication risks associated with SARS-CoV-2 infection and ACE inhibitors. Our findings have immediate applications to SARS-CoV-2 diagnostics, public health monitoring, and therapeutic development.

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Section: Introductionmentioning

confidence: 99%

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

Butler

Mozsary

Meydan

et al. 2020

Preprint

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“…The biggest numbers of AFM cases are reported from California (89 out of 606 total cases), where the observed peak month matches the observed peak month at the national level [17], and Texas (63 out of 606 cases). PER-predicted EV-D68 reports from the BioFire ® Trend are concentrated in Northeast and Midwest regions (6534 out of 10395 total cases), particularly in New York (2478 out of 10395 total cases), but are sparse in California and Texas (446 out of 10395 total cases).…”

Section: Supplementary Textmentioning

confidence: 86%

“…BioFire Trend provides near real-time surveillance based on deidentified clinical test results using the BioFire ® System ( 16 ). EV-D68 cases are then predicted using a Pathogen Extended Resolution (PER) algorithm (see ( 16 ) for details, and Materials and Methods S1.1 for a summary) from the samples that tested positive for rhinovirus/enterovirus (RV/EV) from the BioFire ® FilmArray ® Respiratory (RP) Panel results ( 17 ). We analyze PER-predicted EV-D68 cases across 24 states, consisting of 55 sites, in the US between January 2014 and September 2019.…”

mentioning

confidence: 99%

Epidemiological dynamics of enterovirus D68 in the US: implications for acute flaccid myelitis

Park

Farrar

Messacar

et al. 2020

Preprint

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The lack of active surveillance for enterovirus D68 (EV-D68) in the US has hampered the ability to assess the relationship with predominantly biennial epidemics of acute flaccid myelitis (AFM), a rare but serious neurological condition. Using novel surveillance data from the BioFire® Syndromic Trends (Trend) epidemiology network, we characterize the epidemiological dynamics of EV-D68 and demonstrate strong spatiotemporal association with AFM. Although the recent dominant biennial cycles of EV-D68 dynamics may not be stable, we show that a major EV-D68 epidemic, and hence an AFM outbreak, would still be possible in 2020 under normal epidemiological conditions. Significant social distancing due to the ongoing COVID-19 pandemic could reduce the size of an EV-D68 epidemic in 2020, illustrating the potential broader epidemiological impact of the pandemic.

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“…The coronavirus disease 2019 (COVID-19), an infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the first global pandemic of the 21 st century. Several genomic epidemiology tools have been developed to track the public and population health impact of SARS-CoV-2 community spread worldwide [1-5]. More than 137 million cases and close to 3 million deaths have been reported since the beginning of the pandemic in January 2020 (https://coronavirus.jhu.edu).…”

Section: Introductionmentioning

confidence: 99%

Precision Health Diagnostic and Surveillance Network uses S Gene Target Failure (SGTF) combined with sequencing technologies to identify emerging SARS-CoV-2 variants

Guerrero-Preston¹,

Amill

Caraballo³

et al. 2021

Preprint

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Several genomic epidemiology tools have been developed to track the public and population health impact of SARS-CoV-2 community spread worldwide. A SARS-CoV-2 Variant of Concern (VOC) B.1.1.7, known as 501Y.V1, which shows increased transmissibility, has rapidly become the dominant VOC in the United States (US). Our objective was to develop an evidenced-based genomic surveillance algorithm that combines RT-PCR and sequencing technologies to identify VOCs. Deidentified data were obtained from 508,969 patients tested for COVID-19 with the TaqPath COVID-19 RT-PCR Combo Kit (ThermoFisher) in four CLIA certified clinical laboratories in Puerto Rico (n=86,639) and in three CLIA certified clinical laboratories in the US (n=422,330). TaqPath data revealed a frequency of S Gene Target Failure (SGTF) >47% for the last week of March 2021, in both Puerto Rico and US laboratories. The monthly frequency of SGTF in Puerto Rico steadily increased exponentially from 4% in November 2020 to 47% in March 2021.The weekly SGTF rate in US samples was high (>8%) from late December to early January, and then also increased exponentially through April (48%). The exponential increase in SGFT prevalence in Puerto Rico is concurrent with a sharp increase in VOCs among all SARS-CoV-2 sequences from Puerto Rico uploaded to GISAID (n=461). B.1.1.7 frequency increased from <1% in the last week of January 2021 to 51.5% of viral sequences from Puerto Rico collected in the last week of March 2021. The exponential increase in SGTF and B.1.1.7 prevalence in Puerto Rico and US requires an urgent response. According to the proposed evidence-based algorithm, approximately 50% of all positive samples should be managed as potential B.1.1.7 carriers with VOC quarantine and contact tracing protocols while their lineage is confirmed by WGS in surveillance laboratories. Patients infected with VOCs should be effectively triaged for isolation, contact tracing and follow-up treatment purposes.

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Enterovirus D68 outbreak detection through a syndromic disease epidemiology network

Cited by 17 publications

References 39 publications

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

Shotgun Transcriptome and Isothermal Profiling of SARS-CoV-2 Infection Reveals Unique Host Responses, Viral Diversification, and Drug Interactions

Epidemiological dynamics of enterovirus D68 in the US: implications for acute flaccid myelitis

Precision Health Diagnostic and Surveillance Network uses S Gene Target Failure (SGTF) combined with sequencing technologies to identify emerging SARS-CoV-2 variants

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