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The open-source outbreak : H1N1, the olympics and new directions for public health Gardy, Jennifer 2009-11-03

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the open-source outbreak: H1N1, the olympics and new directions for public health dr. jennifer gardy bc centre for disease control genome research laboratory outline •  pandemic H1N1: the first open- source outbreak •  H1N1/Olympics research project •  descriptive epidemiology •  predictive epidemiology genomics enables: present: descriptive epidemiology of a bacterial/viral pathogen  future: predictive epidemiology via genome surveillance part 1 •  pandemic H1N1: the first open- source outbreak •  H1N1/Olympics research project •  descriptive epidemiology •  predictive epidemiology rewind to march 2009 pandemic!open source outbreak sharing germs, sharing genomes pandemic! april 25: 1st genome april 26: international wiki 13 people, 8 institutes, 4 countries http://tree.bio.ed.ac.uk/groups/influenza april 26: origins of the virus calculated april 30: origins data published 5 days from sequence  to open-access paper pandemic! april 25: 1st genome may 6: 69 virus’ RNA virus entered human population late 08/early 09 may 5: first major paper submitted may 11: first major paper published pandemic! april 25: 1st genome may 6: 69 virus’ RNA june 11: 250+ papers SARS, 2003 day 0 virus isolation H1N1, 2009 day 19  one viral genome day 19  100+ viral genomes where/when it arose multiple papers vaccine seed strain day 0 virus isolation how? technological advances shift in scientists’ attitudes genomes = easy, cheap, fast human genome project (1990) 10 years to draft 3 more to complete $3 billion 100s of people spring 2009 four weeks $48,000 worth of reagents three-person team stephen quake, stanford bioengineering data = easy, cheap, fast from flickr user amy and casey  the file-sharing generation Mann et al, Comm. of the ACM 52(3):135. (2009) collaboration pandemic H1N1: the first open-source outbreak part 2 •  pandemic H1N1: the first open- source outbreak •  H1N1/Olympics research project •  descriptive epidemiology •  predictive epidemiology BCCDC & pH1N1: lab testing •  april/may: surge in lab test volume BCCDC & pH1N1: research & activities •  “one-stop pandemic shop” •  sero-epi survey •  vaccine uptake campaign •  mathematical modelling •  informatics infrastructure •  genomics sequence 400-500 H1N1 genomes, observe viral evolution in real-time. “influenza virus is sloppy, capricious and promiscuous” – world health organization intersubtypic reassortment intrasubtypic reassortment point mutation H1N1 genomics project overview 1. targeted sequencing: public health outcomes • SNP-type and sequence key regions • monitor changes • adjust public health interventions as needed • identify interesting virus e.g. 4 samples with point mutations in M gene rendered typing assay probe ineffective = new probe. 2. whole-genome sequencing: evolution • monitor viral evolution in real-time • determine effect of Olympics on viral evolution 3. metagenomics: co-infections • capitalize on available samples • explore patterns of co- infection BCCDC’s H1N1 genomics project •  all sequence will be made publicly available •  collaborating with social scientists, FNIH, GSC, international group of phylodynamics researchers using orwik, GoogleWave part 3 •  pandemic H1N1: the first open- source outbreak •  H1N1/Olympics research project •  descriptive epidemiology •  predictive epidemiology what is descriptive epidemiology of a pathogen? where did it come from, how is it spreading, what makes it pathogenic? story 1: where did it come from? SARS •  first novel EID of 21st century •  Nov. 2002 – atypical pneumonia, China •  March 2003 – international spread •  July 2003 – containment (~800 deaths) •  suspected animal origin •  sequenced by BCCDC & others but… high nucleic acid identity, not found in wild civets •  SARS CoV and others found in bats •  older, evolutionarily stable •  endemic since mid-1980s story 2: how is it spreading? influenza •  IGSP: 4000 influenza genomes across time, space, species, type  source-sink model of emergence doi:10.1038/nature06945 co-circulating lineages w/ reassortment doi:10.1371/journal.ppat.1000133 antiviral resistance is dynamic story 3: what makes it pathogenic? Dengue •  50-100 million infections per year •  four serotypes, each with multiple genotypes, geographic distribution •  large-scale sequencing effort underway (target= 3500 genomes) •  genomic correlates of severity bccdc story 1: outbreak evolution TB •  36 complete M. tuberculosis genomes from VI outbreak to compare molecular evolution vs. field epidemiology data bccdc story 1: unusual isolate S. pneumo •  genome from serotype 5 DTES outbreak contains an unusual genomic island (sugar usage?) descriptive epidemiology: the future •  can answer questions around origins, evolution, pathogenicity, but not clinically- relevant questions •  effect of co-infections? links between evolution of co-infecting pathogens? role of immunity? viral quasispecies within an individual? epistatic interactions? genomes of most common pathogens? virus discovery?  •  genome data must be collected along with extensive host, co-infection data descriptive epidemiology part 4 •  pandemic H1N1: the first open- source outbreak •  H1N1/Olympics research project •  descriptive epidemiology •  predictive epidemiology stopping the next outbreak before it starts months of undiscovered circulation in people sometimes cover-ups, infrastructure problems most often poor surveillance, novel pathogens population sampling to pick up threats before the lab or clinic predictive epidemiology: genome surveillance •  genomics technology exists, global sentinel system is the roadblock •  needs infrastructure, standards, reporting •  local/national sentinel systems effective, start by incorporating genomics into these •  must ultimately consider diverse species, geography, demographics over time to be effective 10.1038/nature05775 wildlife other animals antimicrobial resistance vector-borne 0.1038/nature06536 from flickr user stuck in customs 

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