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Nat Microbiol. 2019 Jan;4(1):10-19. doi: 10.1038/s41564-018-0296-2. Epub 2018 Dec 13.

Tracking virus outbreaks in the twenty-first century.

Author information

1
Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA.
2
Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
3
Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA. jason.ladner@nau.edu.
4
Department of Microbiology and Immunology, Rega Institute, KU Leuven - University of Leuven, Leuven, Belgium.
5
Department of Zoology, University of Oxford, Oxford, UK.
6
Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK. a.rambaut@ed.ac.uk.
7
Fogarty International Center, National Institutes of Health, Bethesda, MD, USA. a.rambaut@ed.ac.uk.
8
Marie Bashir Institute for Infectious Diseases and Biosecurity, School of Life and Environmental Sciences and Sydney Medical School, Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia. edward.holmes@sydney.edu.au.
9
Scripps Research Translational Institute, La Jolla, CA, USA.

Abstract

Emerging viruses have the potential to impose substantial mortality, morbidity and economic burdens on human populations. Tracking the spread of infectious diseases to assist in their control has traditionally relied on the analysis of case data gathered as the outbreak proceeds. Here, we describe how many of the key questions in infectious disease epidemiology, from the initial detection and characterization of outbreak viruses, to transmission chain tracking and outbreak mapping, can now be much more accurately addressed using recent advances in virus sequencing and phylogenetics. We highlight the utility of this approach with the hypothetical outbreak of an unknown pathogen, 'Disease X', suggested by the World Health Organization to be a potential cause of a future major epidemic. We also outline the requirements and challenges, including the need for flexible platforms that generate sequence data in real-time, and for these data to be shared as widely and openly as possible.

PMID:
30546099
DOI:
10.1038/s41564-018-0296-2

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