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Yamayoshi S, Kawaoka Y. Current and future influenza vaccines. Nat Med 2019; 25:212-220. [PMID: 30692696 DOI: 10.1038/s41591-018-0340-z] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Accepted: 12/19/2018] [Indexed: 11/09/2022]
Abstract
Although antiviral drugs and vaccines have reduced the economic and healthcare burdens of influenza, influenza epidemics continue to take a toll. Over the past decade, research on influenza viruses has revealed a potential path to improvement. The clues have come from accumulated discoveries from basic and clinical studies. Now, virus surveillance allows researchers to monitor influenza virus epidemic trends and to accumulate virus sequences in public databases, which leads to better selection of candidate viruses for vaccines and early detection of drug-resistant viruses. Here we provide an overview of current vaccine options and describe efforts directed toward the development of next-generation vaccines. Finally, we propose a plan for the development of an optimal influenza vaccine.
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Affiliation(s)
- Seiya Yamayoshi
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Yoshihiro Kawaoka
- Division of Virology, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, Tokyo, Japan. .,Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo, Japan. .,Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin Madison, Madison, WI, USA.
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Abburu S. GIS Based Health Information Management through LETL, Multi Criteria Query, Analysis, Visualization. INTERNATIONAL JOURNAL OF E-HEALTH AND MEDICAL COMMUNICATIONS 2019. [DOI: 10.4018/ijehmc.2019010103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
For effective decision making in public health information management(HIM) system, health information availability, accessibility, prompt exchange, GIS linkage, spatiotemporal analysis of diseases is crucial. Lack of cost-effective technical support and information gaps are the main obstacles in HIM. This article defines a generic conceptual process framework for effective HIM that provides cost-effective, portable, easy to use solution. The solution incorporates GIS, Mobile technology, information management concepts, ICD-10 codes, WHO and mHealth standards. The current research is implemented as an android application that facilitates: 1) Patient disease data collection, geospatial mapping of disease data and accumulate a centralized server 2) LETL that supports bulk disease data upload 3) Addresses syntactic and semantic heterogeneity in health data 4) A strong multi-criteria query engine, visualization and spatiotemporal analysis of diseases are designed with a global perspective to be used across the globe.
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Orlek A, Phan H, Sheppard AE, Doumith M, Ellington M, Peto T, Crook D, Walker AS, Woodford N, Anjum MF, Stoesser N. Ordering the mob: Insights into replicon and MOB typing schemes from analysis of a curated dataset of publicly available plasmids. Plasmid 2017; 91:42-52. [PMID: 28286183 PMCID: PMC5466382 DOI: 10.1016/j.plasmid.2017.03.002] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Accepted: 03/08/2017] [Indexed: 01/17/2023]
Abstract
Plasmid typing can provide insights into the epidemiology and transmission of plasmid-mediated antibiotic resistance. The principal plasmid typing schemes are replicon typing and MOB typing, which utilize variation in replication loci and relaxase proteins respectively. Previous studies investigating the proportion of plasmids assigned a type by these schemes (‘typeability’) have yielded conflicting results; moreover, thousands of plasmid sequences have been added to NCBI in recent years, without consistent annotation to indicate which sequences represent complete plasmids. Here, a curated dataset of complete Enterobacteriaceae plasmids from NCBI was compiled, and used to assess the typeability and concordance of in silico replicon and MOB typing schemes. Concordance was assessed at hierarchical replicon type resolutions, from replicon family-level to plasmid multilocus sequence type (pMLST)-level, where available. We found that 85% and 65% of the curated plasmids could be replicon and MOB typed, respectively. Overall, plasmid size and the number of resistance genes were significant independent predictors of replicon and MOB typing success. We found some degree of non-concordance between replicon families and MOB types, which was only partly resolved when partitioning plasmids into finer-resolution groups (replicon and pMLST types). In some cases, non-concordance was attributed to ambiguous boundaries between MOBP and MOBQ types; in other cases, backbone mosaicism was considered a more plausible explanation. β-lactamase resistance genes tended not to show fidelity to a particular plasmid type, though some previously reported associations were supported. Overall, replicon and MOB typing schemes are likely to continue playing an important role in plasmid analysis, but their performance is constrained by the diverse and dynamic nature of plasmid genomes. 92% of clinically-relevant plasmids could be replicon typed, compared with reports of 100% typeability in 2014. Replicon and MOB typing were partly concordant; partitioning plasmids into finer-resolution groups increased concordance. Overlap between MOBP and MOBQ relaxase families complicates assignment of MOBP and MOBQ types. Generally, resistance genes showed low fidelity towards particular plasmid backbones. PacBio sequencing has driven increased availability of complete plasmid sequences, but retrieved datasets require curation.
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Affiliation(s)
- Alex Orlek
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK.
| | - Hang Phan
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Anna E Sheppard
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Michel Doumith
- Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - Matthew Ellington
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK; Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - Tim Peto
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Derrick Crook
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - A Sarah Walker
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK; NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK
| | - Neil Woodford
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK; Antimicrobial Resistance and Healthcare Associated Infections (AMRHAI) Reference Unit, National Infection Service, Public Health England, London, UK
| | - Muna F Anjum
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, University of Oxford, Oxford, UK; Department of Bacteriology, Animal and Plant Health Agency, Addlestone, UK
| | - Nicole Stoesser
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Oxford, UK
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Hampson A, Barr I, Cox N, Donis RO, Siddhivinayak H, Jernigan D, Katz J, McCauley J, Motta F, Odagiri T, Tam JS, Waddell A, Webby R, Ziegler T, Zhang W. Improving the selection and development of influenza vaccine viruses - Report of a WHO informal consultation on improving influenza vaccine virus selection, Hong Kong SAR, China, 18-20 November 2015. Vaccine 2017; 35:1104-1109. [PMID: 28131392 PMCID: PMC5357705 DOI: 10.1016/j.vaccine.2017.01.018] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Accepted: 01/10/2017] [Indexed: 11/25/2022]
Abstract
Since 2010 the WHO has held a series of informal consultations to explore ways of improving the currently highly complex and time-pressured influenza vaccine virus selection and development process. In November 2015 experts from around the world met to review the current status of efforts in this field. Discussion topics included strengthening influenza surveillance activities to increase the availability of candidate vaccine viruses and improve the extent, timeliness and quality of surveillance data. Consideration was also given to the development and potential application of newer laboratory assays to better characterize candidate vaccine viruses, the potential importance of antibodies directed against influenza virus neuraminidase, and the role of vaccine effectiveness studies. Advances in next generation sequencing and whole genome sequencing of influenza viruses were also discussed, along with associated developments in synthetic genomics technologies, evolutionary analysis and predictive mathematical modelling. Discussions were also held on the late emergence of an antigenic variant influenza A(H3N2) virus in mid-2014 that could not be incorporated in time into the 2014–15 northern hemisphere vaccine. There was broad recognition that given the current highly constrained influenza vaccine development and production timeline it would remain impossible to incorporate any variant virus which emerged significantly long after the relevant WHO biannual influenza vaccine composition meetings. Discussions were also held on the development of pandemic and broadly protective vaccines, and on associated regulatory and manufacturing requirements and constraints. With increasing awareness of the health and economic burdens caused by seasonal influenza, the ever-present threat posed by zoonotic influenza viruses, and the significant impact of the 2014–15 northern hemisphere seasonal influenza vaccine mismatch, this consultation provided a very timely opportunity to share developments and exchange views. In all areas, a renewed and strengthened emphasis was placed on developing concrete and measurable actions and identifying the key stakeholders responsible for their implementation.
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Affiliation(s)
| | - Ian Barr
- Victorian Infectious Diseases Reference Laboratory (VIDRL), Melbourne, Australia.
| | - Nancy Cox
- Centers for Disease Control and Prevention (CDC), Atlanta, USA.
| | - Ruben O Donis
- Biomedical Advanced Research and Development Authority (BARDA), ASPR, US Department of Health and Human Services, Washington DC, USA.
| | - Hirve Siddhivinayak
- Global Influenza Programme, World Health Organization (WHO), Geneva, Switzerland.
| | - Daniel Jernigan
- Centers for Disease Control and Prevention (CDC), Atlanta, USA.
| | - Jacqueline Katz
- Centers for Disease Control and Prevention (CDC), Atlanta, USA.
| | | | | | - Takato Odagiri
- National Institute of Infectious Diseases, Tokyo, Japan.
| | - John S Tam
- The Hong Kong Polytechnic University, Hong Kong Special Administrative Region.
| | | | | | - Thedi Ziegler
- Global Influenza Programme, World Health Organization (WHO), Geneva, Switzerland.
| | - Wenqing Zhang
- Global Influenza Programme, World Health Organization (WHO), Geneva, Switzerland.
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