{"id":11,"date":"2016-03-07T10:06:29","date_gmt":"2016-03-07T18:06:29","guid":{"rendered":"https:\/\/blogs.ubc.ca\/gardylab\/?p=11"},"modified":"2016-03-07T10:07:28","modified_gmt":"2016-03-07T18:07:28","slug":"monday-morning-status-update-attempting-to-clear-out","status":"publish","type":"post","link":"https:\/\/blogs.ubc.ca\/gardylab\/2016\/03\/07\/monday-morning-status-update-attempting-to-clear-out\/","title":{"rendered":"Ten Simple Rules &#8211; genomic epidemiology edition"},"content":{"rendered":"<p>Monday morning status update: attempting to clear out most of the inbox backlog before leaving this afternoon for <a href=\"https:\/\/www.escmid.org\/research_projects\/escmid_conferences\/immem_xi\/\" target=\"_blank\">IMMEM XI<\/a> in sunny Portugal. And I suppose I should write my IMMEM keynote talk at some point before Wednesday afternoon too. My assigned topic is integrating genomic data with epidemiological data for outbreak investigation, and I&#8217;m thinking of doing a PLoS Comp Bio &#8220;Ten Simple Rules&#8221; sort of thing, with anecdotes from our work and other key studies in the genomic epidemiology space.<\/p>\n<p>What have I got so far? Here are a few; feel free to comment with more (if I use them in the talk, you&#8217;ll get a shout-out on the slide):<\/p>\n<p><strong>Clinical bits to remember:<\/strong><\/p>\n<ol>\n<li><strong>Know your pathogen<\/strong>. Different bugs have different quirks that will affect an outbreak reconstruction, like latency, asymptomatic carriage, varying levels of infectiousness.<\/li>\n<li><strong>Think SIIR<\/strong> &#8211; Susceptible, Infected, Infectious, Removed. Each patient will move through these stages in different ways. For each individual, try to plot their potential trajectory. For some bugs with well-defined stages, like measles, this is easy. For others, mehhhhh, not so much.<\/li>\n<li><strong>Not all hosts are created equal<\/strong>. Within-host genetic diversity already bit us in the @$$ (see <a href=\"https:\/\/blogs.ubc.ca\/gardylab\/2016\/03\/04\/behind-the-preprint-declaring-a-tuberculosis-outbreak-over-with-genomic-epidemiology\/\" target=\"_blank\">this post<\/a> for a bit of background on that), and both recent and older work has shown that in diseases like TB, the within-host mutation rate fluctuates rather wildly. Stringent thresholds for person-to-person transmission might miss events involving a mutational-hotspot host.<\/li>\n<\/ol>\n<p><strong>Epidemiological bits to remember:<\/strong><\/p>\n<ol>\n<li><strong>People, places, food\/water, and things all need to be considered<\/strong>. In any given outbreak,\u00a0at least two of these things are probably in play, if not more. Your reconstruction diagram shouldn&#8217;t be just a bunch of people connected by arrows &#8211; there&#8217;s always more to the story.<\/li>\n<li><strong>When the genomic data says &#8220;maybe&#8221; and the field epis say &#8220;definitely&#8221;, believe the epis<\/strong>. Genomics is great for ruling out transmission events, but in complex outbreaks, the ruling-in part is harder. I&#8217;d trust a public health nurse over a model any day, especially for outbreaks like TB.<\/li>\n<li><strong>The line list is only half the story<\/strong>. Talk to the epis and nurses who collected the data about each case, especially if you&#8217;re trying to link two cases and the line list isn&#8217;t giving you much to work with. There&#8217;s always way more to the story than what ends up in the Excel spreadsheet.<\/li>\n<li>Following on from #3, <strong>learn to <del>love<\/del> tolerate Excel<\/strong>. Epidemiologists love a good spreadsheet. Tools like <a href=\"http:\/\/microreact.org\" target=\"_blank\">Microreact<\/a>\u00a0(David Aanensen) and <a href=\"http:\/\/nextflu.org\/h3n2\/3y\/\" target=\"_blank\">NextFlu<\/a>\u00a0(Trevor Bedford) are helping move them into the next generation, but for now, expect to be sent about a million Excel sheets.<\/li>\n<li><strong>Spread the ontology gospel<\/strong>. Groups like IRIDA (van Domselaar\/Brinkman\/Hsiao) are working towards developing a shared vocabulary for genomic epidemiology &#8211; try repackaging what you dig up out of those Excel files into these standardized vocabularies.<\/li>\n<\/ol>\n<p><strong>Big picture bits to remember:<\/strong><\/p>\n<ol>\n<li><strong>Genomics and phylogenetics is a strange and foreign landscape for most epidemiologists, but they&#8217;re enthusiastic to learn<\/strong>. We need to make our work accessible and open, and provide more opportunities to train our colleagues in understanding and interpreting genomic data.<\/li>\n<li><strong>Public health agencies change slowly<\/strong>. Don&#8217;t expect to march in with a new ontology and a new platform for collecting and displaying data and revamp the whole system overnight. Public health changes in response to evidence &#8211; when you can show that something works better, cheaper, and faster, then you can start making changes. Moving genomics to routine clinical use takes years of relationship-building.<\/li>\n<\/ol>\n<p>So, uh, that&#8217;s ten. But my &#8220;Ten Simple Rules&#8221; can totally turn into 12, 15, 18, 36, 47, etc simple rules, so feel free to chime in with new ones below, or comments\/feedback\/examples on the ones above. I should probably add the caveat that for each of those, your experience may vary depending on your pathogen and the team you&#8217;re working with.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Monday morning status update: attempting to clear out most of the inbox backlog before leaving this afternoon for IMMEM XI in sunny Portugal. And I suppose I should write my IMMEM keynote talk at some point before Wednesday afternoon too. My assigned topic is integrating genomic data with epidemiological data for outbreak investigation, and I&#8217;m [&hellip;]<\/p>\n","protected":false},"author":2416,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-11","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/posts\/11","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/users\/2416"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/comments?post=11"}],"version-history":[{"count":2,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/posts\/11\/revisions"}],"predecessor-version":[{"id":13,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/posts\/11\/revisions\/13"}],"wp:attachment":[{"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/media?parent=11"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/categories?post=11"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blogs.ubc.ca\/gardylab\/wp-json\/wp\/v2\/tags?post=11"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}