Last data update: Nov 04, 2024. (Total: 48056 publications since 2009)
Records 1-12 (of 12 Records) |
Query Trace: Neuhaus E[original query] |
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Monitoring and reporting the US COVID-19 vaccination effort
Scharf LG , Adeniyi K , Augustini E , Boyd D , Corvin L , Kalach RE , Fast H , Fath J , Harris L , Henderson D , Hicks-Thomson J , Jones-Jack N , Kellerman A , Khan AN , McGarvey SS , McGehee JE , EMiner C , Moore LB , Murthy BP , Myerburg S , Neuhaus E , Nguyen K , Parker M , Pierce-Richards S , Samchok D , Shaw LK , Spoto S , Srinivasan A , Stearle C , Thomas J , Winarsky M , Zell E . Vaccine 2023 Immunizations are an important tool to reduce the burden of vaccine preventable diseases and improve population health.(1) High-quality immunization data is essential to inform clinical and public health interventions and respond to outbreaks of vaccine-preventable diseases. To track COVID-19 vaccines and vaccinations, CDC established an integrated network that included vaccination provider systems, health information exchange systems, immunization information systems, pharmacy and dialysis systems, vaccine ordering systems, electronic health records, and tools to support mass vaccination clinics. All these systems reported data to CDC's COVID-19 response system (either directly or indirectly) where it was processed, analyzed, and disseminated. This unprecedented vaccine tracking effort provided essential information for public health officials that was used to monitor the COVID-19 response and guide decisions. This paper will describe systems, processes, and policies that enabled monitoring and reporting of COVID-19 vaccination efforts and share challenges and lessons learned for future public health emergency responses. |
Mitigating Pandemic Risk with Influenza A Virus Field Surveillance at a Swine-Human Interface (preprint)
Rambo-Martin BL , Keller MW , Wilson MM , Nolting JM , Anderson TK , Vincent AL , Bagal UR , Jang Y , Neuhaus EB , Davis CT , Bowman AS , Wentworth DE , Barnes JR . bioRxiv 2019 585588 Working overnight at a large swine exhibition, we identified an influenza A virus (IAV) outbreak in swine, nanopore-sequenced 13 IAV genomes from samples collected, and in real-time, determined that these viruses posed a novel risk to humans due to genetic mismatches between the viruses and current pre-pandemic candidate vaccine viruses (CVV). We developed and used a portable IAV sequencing and analysis platform called Mia (Mobile Influenza Analysis) to complete and characterize full-length consensus genomes approximately 18 hours after unpacking the mobile lab. Swine are important animal IAV reservoirs that have given rise to pandemic viruses via zoonotic transmission. Genomic analyses of IAV in swine are critical to understanding pandemic risk of viruses in this reservoir, and characterization of viruses circulating in exhibition swine enables rapid comparison to current seasonal influenza vaccines and CVVs. The Mia system rapidly identified three genetically distinct swine IAV lineages from three subtypes: A(H1N1), A(H3N2) and A(H1N2). Additional analysis of the HA protein sequences of the A(H1N2) viruses identified >30 amino acid differences between the HA1 portion of the hemagglutinin of these viruses and the most closely related pre-2009 CVV. All virus sequences were emailed to colleagues at CDC who initiated development of a synthetically derived CVV designed to provide an optimal antigenic match with the viruses detected in the exhibition. In subsequent months, this virus caused 13 infections in humans, and was the dominant variant virus in the US detected in 2018. Had this virus caused a severe outbreak or pandemic, our proactive surveillance efforts and CVV derivation would have provided an approximate 8 week time advantage for vaccine manufacturing. This is the first report of the use of field-derived nanopore sequencing data to initiate a real-time, actionable public health countermeasure. |
Direct RNA Sequencing of the Complete Influenza A Virus Genome (preprint)
Keller MW , Rambo-Martin BL , Wilson MM , Ridenour CA , Shepard SS , Stark TJ , Neuhaus EB , Dugan VG , Wentworth DE , Barnes JR . bioRxiv 2018 300384 For the first time, a complete genome of an RNA virus has been sequenced in its original form. Previously, RNA was sequenced by the chemical degradation of radiolabelled RNA, a difficult method that produced only short sequences. Instead, RNA has usually been sequenced indirectly by copying it into cDNA, which is often amplified to dsDNA by PCR and subsequently analyzed using a variety of DNA sequencing methods. We designed an adapter to short highly conserved termini of the influenza virus genome to target the (-) sense RNA into a protein nanopore on the Oxford Nanopore MinION sequencing platform. Utilizing this method and total RNA extracted from the allantoic fluid of infected chicken eggs, we demonstrate successful sequencing of the complete influenza virus genome with 100% nucleotide coverage, 99% consensus identity, and 99% of reads mapped to influenza. By utilizing the same methodology we can redesign the adapter in order to expand the targets to include viral mRNA and (+) sense cRNA, which are essential to the viral life cycle. This has the potential to identify and quantify splice variants and base modifications, which are not practically measurable with current methods. |
Author Correction: Direct RNA Sequencing of the Coding Complete Influenza A Virus Genome.
Keller MW , Rambo-Martin BL , Wilson MM , Ridenour CA , Shepard SS , Stark TJ , Neuhaus EB , Dugan VG , Wentworth DE , Barnes JR . Sci Rep 2018 8 (1) 15746 A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper. |
Influenza A virus field surveillance at a swine-human interface
Rambo-Martin BL , Keller MW , Wilson MM , Nolting JM , Anderson TK , Vincent AL , Bagal UR , Jang Y , Neuhaus EB , Davis CT , Bowman AS , Wentworth DE , Barnes JR . mSphere 2020 5 (1) While working overnight at a swine exhibition, we identified an influenza A virus (IAV) outbreak in swine, Nanopore sequenced 13 IAV genomes from samples we collected, and predicted in real time that these viruses posed a novel risk to humans due to genetic mismatches between the viruses and current prepandemic candidate vaccine viruses (CVVs). We developed and used a portable IAV sequencing and analysis platform called Mia (Mobile Influenza Analysis) to complete and characterize full-length consensus genomes approximately 18 h after unpacking the mobile lab. Exhibition swine are a known source for zoonotic transmission of IAV to humans and pose a potential pandemic risk. Genomic analyses of IAV in swine are critical to understanding this risk, the types of viruses circulating in swine, and whether current vaccines developed for use in humans would be predicted to provide immune protection. Nanopore sequencing technology has enabled genome sequencing in the field at the source of viral outbreaks or at the bedside or pen-side of infected humans and animals. The acquired data, however, have not yet demonstrated real-time, actionable public health responses. The Mia system rapidly identified three genetically distinct swine IAV lineages from three subtypes, A(H1N1), A(H3N2), and A(H1N2). Analysis of the hemagglutinin (HA) sequences of the A(H1N2) viruses identified >30 amino acid differences between the HA1 of these viruses and the most closely related CVV. As an exercise in pandemic preparedness, all sequences were emailed to CDC collaborators who initiated the development of a synthetically derived CVV.IMPORTANCE Swine are influenza virus reservoirs that have caused outbreaks and pandemics. Genomic characterization of these viruses enables pandemic risk assessment and vaccine comparisons, though this typically occurs after a novel swine virus jumps into humans. The greatest risk occurs where large groups of swine and humans comingle. At a large swine exhibition, we used Nanopore sequencing and on-site analytics to interpret 13 swine influenza virus genomes and identified an influenza virus cluster that was genetically highly varied to currently available vaccines. As part of the National Strategy for Pandemic Preparedness exercises, the sequences were emailed to colleagues at the CDC who initiated the development of a synthetically derived vaccine designed to match the viruses at the exhibition. Subsequently, this virus caused 14 infections in humans and was the dominant U.S. variant virus in 2018. |
Pathogen Genomics in Public Health.
Armstrong GL , MacCannell DR , Taylor J , Carleton HA , Neuhaus EB , Bradbury RS , Posey JE , Gwinn M . N Engl J Med 2019 381 (26) 2569-2580 Rapid advances in DNA sequencing technology ("next-generation sequencing") have inspired optimism about the potential of human genomics for "precision medicine." Meanwhile, pathogen genomics is already delivering "precision public health" through more effective investigations of outbreaks of foodborne illnesses, better-targeted tuberculosis control, and more timely and granular influenza surveillance to inform the selection of vaccine strains. In this article, we describe how public health agencies have been adopting pathogen genomics to improve their effectiveness in almost all domains of infectious disease. This momentum is likely to continue, given the ongoing development in sequencing and sequencing-related technologies. |
Potential utility of pharmacy data to measure antibiotic use in nursing homes
Kabbani S , Palms DL , Bartoces M , Marek J , Stone ND , Hicks LA , Jump RLP . Infect Control Hosp Epidemiol 2019 40 (7) 1-2 Antibiotics are among the most commonly prescribed medications in nursing homes,Reference Gurwitz, Field, Judge, Rochon, Harrold and Cadoret1 and they are frequently prescribed inappropriately.Reference Lim, Kong and Stuart2, Reference Nicolle, Bentley, Garibaldi, Neuhaus and Smith3 The Centers for Medicare and Medicaid Services requires that all nursing homes have an antibiotic stewardship program and a system for monitoring antibiotic use.4 Antibiotic use can be monitored using different measures to identify potential targets for practice improvement and to track the impact of antibiotic stewardship interventions.Reference Mylotte5 The 2 most commonly used antibiotic use measures in nursing homes are antibiotic days of therapy and antibiotic starts.Reference Mylotte5, 6 |
Direct RNA Sequencing of the Coding Complete Influenza A Virus Genome.
Keller MW , Rambo-Martin BL , Wilson MM , Ridenour CA , Shepard SS , Stark TJ , Neuhaus EB , Dugan VG , Wentworth DE , Barnes JR . Sci Rep 2018 8 (1) 14408 For the first time, a coding complete genome of an RNA virus has been sequenced in its original form. Previously, RNA was sequenced by the chemical degradation of radiolabeled RNA, a difficult method that produced only short sequences. Instead, RNA has usually been sequenced indirectly by copying it into cDNA, which is often amplified to dsDNA by PCR and subsequently analyzed using a variety of DNA sequencing methods. We designed an adapter to short highly conserved termini of the influenza A virus genome to target the (-) sense RNA into a protein nanopore on the Oxford Nanopore MinION sequencing platform. Utilizing this method with total RNA extracted from the allantoic fluid of influenza rA/Puerto Rico/8/1934 (H1N1) virus infected chicken eggs (EID50 6.8 x 10(9)), we demonstrate successful sequencing of the coding complete influenza A virus genome with 100% nucleotide coverage, 99% consensus identity, and 99% of reads mapped to influenza A virus. By utilizing the same methodology one can redesign the adapter in order to expand the targets to include viral mRNA and (+) sense cRNA, which are essential to the viral life cycle, or other pathogens. This approach also has the potential to identify and quantify splice variants and base modifications, which are not practically measurable with current methods. |
Viral deep sequencing needs an adaptive approach: IRMA, the iterative refinement meta-assembler.
Shepard SS , Meno S , Bahl J , Wilson MM , Barnes J , Neuhaus E . BMC Genomics 2016 17 (1) 708 BACKGROUND: Deep sequencing makes it possible to observe low-frequency viral variants and sub-populations with greater accuracy and sensitivity than ever before. Existing platforms can be used to multiplex a large number of samples; however, analysis of the resulting data is complex and involves separating barcoded samples and various read manipulation processes ending in final assembly. Many assembly tools were designed with larger genomes and higher fidelity polymerases in mind and do not perform well with reads derived from highly variable viral genomes. Reference-based assemblers may leave gaps in viral assemblies while de novo assemblers may struggle to assemble unique genomes. RESULTS: The IRMA (iterative refinement meta-assembler) pipeline solves the problem of viral variation by the iterative optimization of read gathering and assembly. As with all reference-based assembly, reads are included in assembly when they match consensus template sets; however, IRMA provides for on-the-fly reference editing, correction, and optional elongation without the need for additional reference selection. This increases both read depth and breadth. IRMA also focuses on quality control, error correction, indel reporting, variant calling and variant phasing. In fact, IRMA's ability to detect and phase minor variants is one of its most distinguishing features. We have built modules for influenza and ebolavirus. We demonstrate usage and provide calibration data from mixture experiments. Methods for variant calling, phasing, and error estimation/correction have been redesigned to meet the needs of viral genomic sequencing. CONCLUSION: IRMA provides a robust next-generation sequencing assembly solution that is adapted to the needs and characteristics of viral genomes. The software solves issues related to the genetic diversity of viruses while providing customized variant calling, phasing, and quality control. IRMA is freely available for non-commercial use on Linux and Mac OS X and has been parallelized for high-throughput computing. |
Improving pandemic influenza risk assessment.
Russell CA , Kasson PM , Donis RO , Riley S , Dunbar J , Rambaut A , Asher J , Burke S , Davis CT , Garten RJ , Gnanakaran S , Hay SI , Herfst S , Lewis NS , Lloyd-Smith JO , Macken CA , Maurer-Stroh S , Neuhaus E , Parrish CR , Pepin KM , Shepard SS , Smith DL , Suarez DL , Trock SC , Widdowson MA , George DB , Lipsitch M , Bloom JD . Elife 2014 3 e03883 Assessing the pandemic risk posed by specific non-human influenza A viruses is an important goal in public health research. As influenza virus genome sequencing becomes cheaper, faster, and more readily available, the ability to predict pandemic potential from sequence data could transform pandemic influenza risk assessment capabilities. However, the complexities of the relationships between virus genotype and phenotype make such predictions extremely difficult. The integration of experimental work, computational tool development, and analysis of evolutionary pathways, together with refinements to influenza surveillance, has the potential to transform our ability to assess the risks posed to humans by non-human influenza viruses and lead to improved pandemic preparedness and response. |
Analytical challenges for emerging public health surveillance
Rolka H , Walker DW , English R , Katzoff MJ , Scogin G , Neuhaus E . MMWR Suppl 2012 61 (3) 35-40 The root of effective disease control and prevention is an informed understanding of the epidemiology of a particular disease based on sound scientific interpretation of evidence. Such evidence must frequently be transformed from raw data into consumable information before it can be used for making decisions, determining policy, and conducting programs. However, the work of building such evidence in public health practice--doing the right thing at the right time--is essentially hidden from view. Surveillance involves acquiring, analyzing, and interpreting data and information from several sources across various systems. Achieving the goals and objectives of surveillance investments requires attention to analytic requirements of such systems. The process requires computer programming, statistical reasoning, subject matter expertise, often modeling, and effective communication skills. |
Tracking diabetes: New York City's A1C registry
Chamany S , Silver LD , Bassett MT , Driver CR , Berger DK , Neuhaus CE , Kumar N , Frieden TR . Milbank Q 2009 87 (3) 547-70 CONTEXT: In December 2005, in characterizing diabetes as an epidemic, the New York City Board of Health mandated the laboratory reporting of hemoglobin A1C laboratory test results. This mandate established the United States' first population-based registry to track the level of blood sugar control in people with diabetes. But mandatory A1C reporting has provoked debate regarding the role of public health agencies in the control of noncommunicable diseases and, more specifically, both privacy and the doctor-patient relationship. METHODS: This article reviews the rationale for adopting the rule requiring the reporting of A1C test results, experience with its implementation, and criticisms raised in the context of the history of public health practice. FINDINGS: For many decades, public health agencies have used identifiable information collected through mandatory laboratory reporting to monitor the population's health and develop programs for the control of communicable and noncommunicable diseases. The registry program sends quarterly patient rosters stratified by A1C level to more than one thousand medical providers, and it also sends letters, on the provider's letterhead whenever possible, to patients at risk of diabetes complications (A1C level >9 percent), advising medical follow-up. The activities of the registry program are similar to those of programs for other reportable conditions and constitute a joint effort between a governmental public health agency and medical providers to improve patients' health outcomes. CONCLUSIONS: Mandatory reporting has proven successful in helping combat other major epidemics. New York City's A1C Registry activities combine both traditional and novel public health approaches to reduce the burden of an epidemic chronic disease, diabetes. Despite criticism that mandatory reporting compromises individuals' right to privacy without clear benefit, the early feedback has been positive and suggests that the benefits will outweigh the potential harms. Further evaluation will provide additional information that other local health jurisdictions may use in designing their strategies to address chronic disease. |
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