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	<title>EHSLibrary &#187; public health monitoring</title>
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		<title>Predicting disease outbreaks using&#8230;Twitter?</title>
		<link>http://library.med.utah.edu/blog/eccles/2012/05/22/predicting-disease-outbreaks-using-twitter/</link>
		<comments>http://library.med.utah.edu/blog/eccles/2012/05/22/predicting-disease-outbreaks-using-twitter/#comments</comments>
		<pubDate>Tue, 22 May 2012 14:43:42 +0000</pubDate>
		<dc:creator>Todd Vandenbark</dc:creator>
				<category><![CDATA[public health]]></category>
		<category><![CDATA[social media]]></category>
		<category><![CDATA[public health monitoring]]></category>
		<category><![CDATA[Twitter]]></category>

		<guid isPermaLink="false">http://library.med.utah.edu/blog/eccles/?p=1985</guid>
		<description><![CDATA[While raising ethical concerns, monitoring Twitter and other social media may anticipate disease outbreaks faster than traditional data-gathering methods.]]></description>
				<content:encoded><![CDATA[<p><a href="http://library.med.utah.edu/blog/eccles/?s=Twitter"><img class="alignleft size-full wp-image-1987" style="border: 0pt none; float: left; padding:0.5em;" title="Twitter logo" src="http://library.med.utah.edu/blog/eccles/files/2012/05/twitter_sq120.png" alt="Search for posts containing the word &quot;Twitter&quot;" /></a>In a <a title="Link to citation in PubMed" href="http://www.ncbi.nlm.nih.gov/pubmed/22597352">recent British Medical Journal article</a>, UK journalists Gozde Zorlu and&#160;Connie St Louis examine how public health experts are beginning to exploit the power of social media, both proactively and retrospectively. Traditional methods of collecting information on potential disease outbreaks &#8212; collecting lab test results and diagnostic information from doctors &#8212; are more thorough and&#160; accurate, but slower. Time is of the essence when identifying and preparing a response to disease outbreaks.</p>
<p>Popular social media sites have millions of registered users (Facebook, over 800 million; Twitter, over 500 million; WordPress, over 15 million), many of whom log in daily to share intimate details of their lives, including symptoms, illnesses and struggles with chronic diseases. This is a treasure trove of informal data available for research and monitoring of public health issues. While tapping this resource raises many ethical issues, particularly individual identification, initial research has demonstrated that it may help with disease surveillance.</p>
<p>St Louis and Zorlu offer the following examples:</p>
<ul>
<li>Recent analysis of three million tweets from May &#8211; December 2009 showed that &#8220;the 2009 H1N1 flu outbreak could have been identified on Twitter one week before it emerged in official records from general practitioner reports&#8221;</li>
<li>Physicians, unable to reach patients with chronic conditions after the tsunami in Japan in March 2011, turned to Twitter and the mobile Internet to direct patients to sources for their medications.</li>
<li>Digital surveillance platforms such as <a title="Link to site" href="http://born.nii.ac.jp/">BioCaster</a> and <a title="Link to site" href="http://www.healthmap.org/">HealthMap</a> regularly search and extract information from news, social media and other sites looking for hints and clues of new public health threats.</li>
</ul>
<p>While these examples are compelling, and collaborations between HealthMap and public health agencies are underway to track influenza and other public health challenges, Twitter cannot replace traditional methods of tracking and verifying diseases. How many times have you or someone you know attributed symptoms to one illness, only to find it was a different illness? Monitoring must be coupled with verification, else we risk spreading rumor and panic.</p>
<p>Do you use Twitter or other social media to talk about your health concerns and conditions? How do you feel about having this information monitored for the good of many? Tell us!</p>
<p><strong>References</strong>:</p>
<p>St Louis, C., &amp; Zorlu, G. (2012). Can Twitter predict disease outbreaks? <em>BMJ, 344</em>, e2353. doi: 10.1136/bmj.e2353</p>
<p>Szomszor, M., Kostkova, P., &amp; De Quincey, E. (2012). <em>Swineflu: Twitter predicts swine flu oubreak in 2009</em>.</p>
<p>Tamura, Y., &amp; Fukuda, K. (2011). Earthquake in Japan. <em>Lancet, 377</em>(9778), 1652. doi: 10.1016/s0140-6736(11)60672-7</p>
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