{"id":21723,"date":"2018-02-12T12:07:58","date_gmt":"2018-02-12T12:07:58","guid":{"rendered":"http:\/\/punjabnews24.com\/?p=21723"},"modified":"2018-02-12T12:07:58","modified_gmt":"2018-02-12T12:07:58","slug":"smart-thermometer-could-predict-flu-spread-2","status":"publish","type":"post","link":"https:\/\/blastingskyhawk.com\/english\/smart-thermometer-could-predict-flu-spread-2\/","title":{"rendered":"&#8216;Smart thermometer&#8217; could predict flu spread"},"content":{"rendered":"<p>Washington<\/p>\n<p>A &#8220;smart thermometer&#8221; connected to a mobile phone app can track flu activity in real time and help predict how the infection will spread, scientists say.<\/p>\n<p>&#8220;We found the smart thermometer data are highly correlated with information obtained from traditional public health surveillance systems and can be used to<\/p>\n<p>improve forecasting of influenza-like illness activity, possibly giving warnings of changes in disease activity weeks in advance,&#8221; said Aaron Miller, a postdoctoral<\/p>\n<p>scholar at University of Iowa (UI) in the US.<\/p>\n<p>&#8220;Using simple forecasting models, we showed that thermometer data could be effectively used to predict influenza levels up to two to three weeks into the<\/p>\n<p>future,&#8221; said Miller.<\/p>\n<p>&#8220;Given that traditional surveillance systems provide data with a lag time of one to two weeks, this means that estimates of future flu activity may actually be<\/p>\n<p>improved up to four or five weeks earlier,&#8221; he said.<\/p>\n<p>Scientists analysed de-identified data from a commercially available thermometer and accompanying app, which recorded users&#8217; temperature measurement<\/p>\n<p>over a study period from 2015 to 2017.<\/p>\n<p>There were over 8 million temperature readings generated by almost 450,000 unique devices.<\/p>\n<p>The smart thermometers encrypt device identities to protect user privacy and also give users the option of providing anonymised information on age or sex.<\/p>\n<p>The team compared the data from the smart thermometers to influenza-like illness (ILI) activity data gathered by the US Centers for Disease Control and<\/p>\n<p>Prevention (CDC) from health care providers across the country.<\/p>\n<p>The study, published in the journal Clinical Infectious Diseases, found that the de-identified smart thermometer data was highly correlated with ILI activity at<\/p>\n<p>national and regional levels and for different age groups.<\/p>\n<p>Current forecasts rely on this CDC data, but even at its fastest, the information is almost two weeks behind real-time flu activity.<\/p>\n<p>The study showed that adding thermometer data, which captures clinically relevant symptoms (temperature) likely even before a person goes to the doctor, to<\/p>\n<p>simple forecasting models, improved predictions of flu activity.<\/p>\n<p>This approach accurately predicted influenza activity at least three weeks in advance.<\/p>\n<p>&#8220;Our findings suggest that data from smart thermometers are a new source of information for accurately tracking influenza in advance of standard approaches,&#8221;<\/p>\n<p>said Philip Polgreen, associate professor at UI.<\/p>\n<p>&#8220;More advanced information regarding influenza activity can help alert health care professionals that influenza is circulating, help coordinate response efforts,<\/p>\n<p>and help anticipate clinic and hospital staffing needs and increases in visits associated with high levels of influenza activity,&#8221; he said.<\/p>\n<!-- AddThis Advanced Settings generic via filter on the_content --><!-- AddThis Share Buttons generic via filter on the_content -->","protected":false},"excerpt":{"rendered":"<p>Washington A &#8220;smart thermometer&#8221; connected to a mobile phone app can track flu activity in real time and help predict how the infection will spread, scientists say. &#8220;We found the smart thermometer data are highly correlated with information obtained from traditional public health surveillance systems and can be used to improve forecasting of influenza-like illness [&hellip;]<!-- AddThis Advanced Settings generic via filter on get_the_excerpt --><!-- AddThis Share Buttons generic via filter on get_the_excerpt --><\/p>\n","protected":false},"author":1,"featured_media":21724,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[239],"tags":[],"class_list":["post-21723","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-health"],"_links":{"self":[{"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/posts\/21723","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/comments?post=21723"}],"version-history":[{"count":1,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/posts\/21723\/revisions"}],"predecessor-version":[{"id":21725,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/posts\/21723\/revisions\/21725"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/media\/21724"}],"wp:attachment":[{"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/media?parent=21723"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/categories?post=21723"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blastingskyhawk.com\/english\/wp-json\/wp\/v2\/tags?post=21723"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}