Improving Google Flu Trends Estimates for the United States through Transformation
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{"title"=>"Improving Google Flu trends estimates for the United States through transformation", "type"=>"journal", "authors"=>[{"first_name"=>"Leah J.", "last_name"=>"Martin", "scopus_author_id"=>"57191183495"}, {"first_name"=>"Biying", "last_name"=>"Xu", "scopus_author_id"=>"56611048700"}, {"first_name"=>"Yutaka", "last_name"=>"Yasui", "scopus_author_id"=>"7102135927"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "scopus"=>"2-s2.0-84928750394", "sgr"=>"84928750394", "pui"=>"605455196", "isbn"=>"1932-6203", "pmid"=>"25897857", "doi"=>"10.1371/journal.pone.0109209"}, "id"=>"33abcec1-8b9a-30a6-aa66-ea253cb4de7e", "abstract"=>"Google Flu Trends (GFT) uses Internet search queries in an effort to provide early warning of increases in influenza-like illness (ILI). In the United States, GFT estimates the percentage of physician visits related to ILI (%ILINet) reported by the Centers for Disease Control and Prevention (CDC). However, during the 2012-13 influenza season, GFT overestimated %ILINet by an appreciable amount and estimated the peak in incidence three weeks late. Using data from 2010-14, we investigated the relationship between GFT estimates (%GFT) and %ILINet. Based on the relationship between the relative change in %GFT and the relative change in %ILINet, we transformed %GFT estimates to better correspond with %ILINet values. In 2010-13, our transformed %GFT estimates were within ±10% of %ILINet values for 17 of the 29 weeks that %ILINet was above the seasonal baseline value determined by the CDC; in contrast, the original %GFT estimates were within ±10% of %ILINet values for only two of these 29 weeks. Relative to the %ILINet peak in 2012-13, the peak in our transformed %GFT estimates was 2% lower and one week later, whereas the peak in the original %GFT estimates was 74% higher and three weeks later. The same transformation improved %GFT estimates using the recalibrated 2013 GFT model in early 2013-14. Our transformed %GFT estimates can be calculated approximately one week before %ILINet values are reported by the CDC and the transformation equation was stable over the time period investigated (2010-13). We anticipate our results will facilitate future use of GFT.", "link"=>"http://www.mendeley.com/research/improving-google-flu-trends-estimates-united-states-through-transformation", "reader_count"=>23, "reader_count_by_academic_status"=>{"Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Master"=>5, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_user_role"=>{"Researcher"=>7, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>8, "Student > Master"=>5, "Lecturer"=>1, "Lecturer > Senior Lecturer"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Engineering"=>2, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>4, "Agricultural and Biological Sciences"=>4, "Veterinary Science and Veterinary Medicine"=>1, "Psychology"=>2, "Social Sciences"=>3, "Computer Science"=>4}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Social Sciences"=>{"Social Sciences"=>3}, "Psychology"=>{"Psychology"=>2}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>4}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>1}}, "reader_count_by_country"=>{"Ireland"=>1, "Portugal"=>1}, "group_count"=>2}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1859680"], "description"=>"<p>The final CDC value (f%ILINet; blue) is compared to the GFT estimate (%GFT; red) and the transformed GFT estimate using <i>c</i> = 0.65 (transformed %GFT; turquoise). The GFT model was recalibrated during the 2013–14 season: dashed lines show the period in which GFT estimates were retrospectively re-estimated using the 2013 GFT model.</p>", "links"=>[], "tags"=>["ili", "recalibrated 2013 GFT model", "ilinet", "Google Flu Trends Estimates", "Internet search queries", "United States", "Transformation Google Flu Trends", "cdc", "29 weeks"], "article_id"=>1283584, "categories"=>["Biological Sciences"], "users"=>["Leah J. Martin", "Biying Xu", "Yutaka Yasui"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0109209.g001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Weekly_percentage_of_sentinel_physician_visits_related_to_influenza_like_illness_ILI_reported_by_the_Centers_for_Disease_Control_and_Prevention_CDC_and_estimated_using_Google_Flu_Trends_GFT_United_States_October_2010_8211_March_2014_/1283584", "title"=>"Weekly percentage of sentinel physician visits related to influenza-like illness (ILI) reported by the Centers for Disease Control and Prevention (CDC) and estimated using Google Flu Trends (GFT), United States, October 2010–March 2014.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-12-31 03:29:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1859681"], "description"=>"<p>*Week 39 of 2010 and week 30 of 2013 were used to calculate transformed %GFT estimates for each of these time periods, respectively.</p><p>**During the 2010–13 seasons, 29 weeks were above baseline.</p>†<p>During the 2013–14 season, 14 weeks were above baseline.</p><p>Comparing estimates of the weekly percentage of physician visits related to influenza-like illness (ILI) based on Google Flu Trends (GFT) to values reported by the Centers for Disease Control and Prevention (CDC), United States, October 2010–March 2014.</p>", "links"=>[], "tags"=>["ili", "recalibrated 2013 GFT model", "ilinet", "Google Flu Trends Estimates", "Internet search queries", "United States", "Transformation Google Flu Trends", "cdc", "29 weeks"], "article_id"=>1283585, "categories"=>["Biological Sciences"], "users"=>["Leah J. Martin", "Biying Xu", "Yutaka Yasui"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0109209.t001"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparing_estimates_of_the_weekly_percentage_of_physician_visits_related_to_influenza_like_illness_ILI_based_on_Google_Flu_Trends_GFT_to_values_reported_by_the_Centers_for_Disease_Control_and_Prevention_CDC_United_States_October_2010_8211_March_2014_/1283585", "title"=>"Comparing estimates of the weekly percentage of physician visits related to influenza-like illness (ILI) based on Google Flu Trends (GFT) to values reported by the Centers for Disease Control and Prevention (CDC), United States, October 2010–March 2014.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-12-31 03:29:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/1859704", "https://ndownloader.figshare.com/files/1859705", "https://ndownloader.figshare.com/files/1859706", "https://ndownloader.figshare.com/files/1859707", "https://ndownloader.figshare.com/files/1859708", "https://ndownloader.figshare.com/files/1859709", "https://ndownloader.figshare.com/files/1859711", "https://ndownloader.figshare.com/files/1859712", "https://ndownloader.figshare.com/files/1859714", "https://ndownloader.figshare.com/files/1859716", "https://ndownloader.figshare.com/files/1859717", "https://ndownloader.figshare.com/files/1859718", "https://ndownloader.figshare.com/files/1859719", "https://ndownloader.figshare.com/files/1859720"], "description"=>"<div><p>Google Flu Trends (GFT) uses Internet search queries in an effort to provide early warning of increases in influenza-like illness (ILI). In the United States, GFT estimates the percentage of physician visits related to ILI (%ILINet) reported by the Centers for Disease Control and Prevention (CDC). However, during the 2012–13 influenza season, GFT overestimated %ILINet by an appreciable amount and estimated the peak in incidence three weeks late. Using data from 2010–14, we investigated the relationship between GFT estimates (%GFT) and %ILINet. Based on the relationship between the relative change in %GFT and the relative change in %ILINet, we transformed %GFT estimates to better correspond with %ILINet values. In 2010–13, our transformed %GFT estimates were within ±10% of %ILINet values for 17 of the 29 weeks that %ILINet was above the seasonal baseline value determined by the CDC; in contrast, the original %GFT estimates were within ±10% of %ILINet values for only two of these 29 weeks. Relative to the %ILINet peak in 2012–13, the peak in our transformed %GFT estimates was 2% lower and one week later, whereas the peak in the original %GFT estimates was 74% higher and three weeks later. The same transformation improved %GFT estimates using the recalibrated 2013 GFT model in early 2013–14. Our transformed %GFT estimates can be calculated approximately one week before %ILINet values are reported by the CDC and the transformation equation was stable over the time period investigated (2010–13). We anticipate our results will facilitate future use of GFT.</p></div>", "links"=>[], "tags"=>["ili", "recalibrated 2013 GFT model", "ilinet", "Google Flu Trends Estimates", "Internet search queries", "United States", "Transformation Google Flu Trends", "cdc", "29 weeks"], "article_id"=>1283606, "categories"=>["Biological Sciences"], "users"=>["Leah J. Martin", "Biying Xu", "Yutaka Yasui"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0109209.s001", "https://dx.doi.org/10.1371/journal.pone.0109209.s002", "https://dx.doi.org/10.1371/journal.pone.0109209.s003", "https://dx.doi.org/10.1371/journal.pone.0109209.s004", "https://dx.doi.org/10.1371/journal.pone.0109209.s005", "https://dx.doi.org/10.1371/journal.pone.0109209.s006", "https://dx.doi.org/10.1371/journal.pone.0109209.s007", "https://dx.doi.org/10.1371/journal.pone.0109209.s008", "https://dx.doi.org/10.1371/journal.pone.0109209.s009", "https://dx.doi.org/10.1371/journal.pone.0109209.s010", "https://dx.doi.org/10.1371/journal.pone.0109209.s011", "https://dx.doi.org/10.1371/journal.pone.0109209.s012", "https://dx.doi.org/10.1371/journal.pone.0109209.s013", "https://dx.doi.org/10.1371/journal.pone.0109209.s014"], "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Improving_Google_Flu_Trends_Estimates_for_the_United_States_through_Transformation_/1283606", "title"=>"Improving Google Flu Trends Estimates for the United States through Transformation", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2014-12-31 03:29:53"}

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