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      Towards a genomics-informed, real-time, global pathogen surveillance system

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          Key Points

          • Despite the recommendations of many expert groups, public health surveillance systems have not yet improved to the point where emerging infectious threats can be better anticipated. The Ebola and Zika epidemics are the latest to demonstrate that pathogens often spread undetected for some time before being diagnosed in a population.

          • Next-generation sequencing, particularly the use of portable genomic sequencers, offers an intriguing solution to the diagnosis and surveillance problems — it enables rapid in situ diagnostics through amplicon-based or metagenomics approaches and creates a stream of genomic data that can reveal critical epidemiological aspects of an outbreak or epidemic's dynamics.

          • Genomic epidemiology for rapid outbreak response has demonstrated some early successes in Ebola and Zika, but there are a number of challenges to overcome — some technical and some cultural. Data sharing is one of these, but other ethical and legal issues must be considered.

          • The power of a genomic epidemiology approach could be extended by incorporating concepts from digital disease detection and One Health. By coupling sequencing to an enhanced surveillance and response platform, we could take a more anticipatory approach to outbreak prevention and control.

          Supplementary information

          The online version of this article (doi:10.1038/nrg.2017.88) contains supplementary material, which is available to authorized users.

          Abstract

          Next-generation sequencing has the potential to support public health surveillance systems to improve the early detection of emerging infectious diseases. This Review delineates the role of genomics in rapid outbreak response and the challenges that need to be tackled for genomics-informed pathogen surveillance to become a global reality.

          Supplementary information

          The online version of this article (doi:10.1038/nrg.2017.88) contains supplementary material, which is available to authorized users.

          Abstract

          The recent Ebola and Zika epidemics demonstrate the need for the continuous surveillance, rapid diagnosis and real-time tracking of emerging infectious diseases. Fast, affordable sequencing of pathogen genomes — now a staple of the public health microbiology laboratory in well-resourced settings — can affect each of these areas. Coupling genomic diagnostics and epidemiology to innovative digital disease detection platforms raises the possibility of an open, global, digital pathogen surveillance system. When informed by a One Health approach, in which human, animal and environmental health are considered together, such a genomics-based system has profound potential to improve public health in settings lacking robust laboratory capacity.

          Supplementary information

          The online version of this article (doi:10.1038/nrg.2017.88) contains supplementary material, which is available to authorized users.

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          Most cited references77

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          Performance comparison of benchtop high-throughput sequencing platforms.

          Three benchtop high-throughput sequencing instruments are now available. The 454 GS Junior (Roche), MiSeq (Illumina) and Ion Torrent PGM (Life Technologies) are laser-printer sized and offer modest set-up and running costs. Each instrument can generate data required for a draft bacterial genome sequence in days, making them attractive for identifying and characterizing pathogens in the clinical setting. We compared the performance of these instruments by sequencing an isolate of Escherichia coli O104:H4, which caused an outbreak of food poisoning in Germany in 2011. The MiSeq had the highest throughput per run (1.6 Gb/run, 60 Mb/h) and lowest error rates. The 454 GS Junior generated the longest reads (up to 600 bases) and most contiguous assemblies but had the lowest throughput (70 Mb/run, 9 Mb/h). Run in 100-bp mode, the Ion Torrent PGM had the highest throughput (80–100 Mb/h). Unlike the MiSeq, the Ion Torrent PGM and 454 GS Junior both produced homopolymer-associated indel errors (1.5 and 0.38 errors per 100 bases, respectively).
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            Digital disease detection--harnessing the Web for public health surveillance.

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              Google trends: a web-based tool for real-time surveillance of disease outbreaks.

              Google Flu Trends can detect regional outbreaks of influenza 7-10 days before conventional Centers for Disease Control and Prevention surveillance systems. We describe the Google Trends tool, explain how the data are processed, present examples, and discuss its strengths and limitations. Google Trends shows great promise as a timely, robust, and sensitive surveillance system. It is best used for surveillance of epidemics and diseases with high prevalences and is currently better suited to track disease activity in developed countries, because to be most effective, it requires large populations of Web search users. Spikes in search volume are currently hard to interpret but have the benefit of increasing vigilance. Google should work with public health care practitioners to develop specialized tools, using Google Flu Trends as a blueprint, to track infectious diseases. Suitable Web search query proxies for diseases need to be established for specialized tools or syndromic surveillance. This unique and innovative technology takes us one step closer to true real-time outbreak surveillance.
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                Author and article information

                Contributors
                jennifer.gardy@bccdc.ca
                Journal
                Nat Rev Genet
                Nat. Rev. Genet
                Nature Reviews. Genetics
                Nature Publishing Group UK (London )
                1471-0056
                1471-0064
                13 November 2017
                2018
                : 19
                : 1
                : 9-20
                Affiliations
                [1 ]GRID grid.418246.d, ISNI 0000 0001 0352 641X, British Columbia Centre for Disease Control, ; Vancouver, V5Z 4R4 British Columbia Canada
                [2 ]GRID grid.17091.3e, ISNI 0000 0001 2288 9830, School of Population and Public Health, University of British Columbia, ; Vancouver, V6T 1Z3 British Columbia Canada
                [3 ]GRID grid.6572.6, ISNI 0000 0004 1936 7486, Institute of Microbiology and Infection, University of Birmingham, ; Birmingham, B15 2TT UK
                Article
                BFnrg201788
                10.1038/nrg.2017.88
                7097748
                29129921
                07a5f9c9-6db8-4d98-81cd-17d89c9a0afe
                © Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. 2017

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

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                © Springer Nature Limited 2018

                genomics,pathogens,public health,metagenomics,next-generation sequencing,clinical microbiology,bacterial genomics,infectious-disease epidemiology,viral epidemiology

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