1. Detecting influenza epidemics using search engine query data
Jeremy Ginsberg, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski & Larry Brilliant
Nature volume 457, pages1012–1014(2009)Cite this article
Query fractions for the top 100 search queries, sorted by mean Z-transformed correlation with CDC-provided ILI percentages across the nine regions of the United States. (XLS 5264 kb)
2. The Parable of Google Flu: Traps in Big Data Analysis
David Lazer1,2,*, Ryan Kennedy1,3,4, Gary King3, Alessandro Vespignani5,6,3
See all authors and affiliations
Science 14 Mar 2014:
Vol. 343, Issue 6176, pp. 1203-1205
DOI: 10.1126/science.1248506
Lazer, David; Kennedy, Ryan; King, Gary; Vespignani, Alessandro, 2014, "Replication data for: The Parable of Google Flu: Traps in Big Data Analysis", https://doi.org/10.7910/DVN/24823, Harvard Dataverse, V2, UNF:5:BJh9WzZQNEeSEpV3EWs+xg== [fileUNF]
3. Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches
Fred S. Lu, Mohammad W. Hattab, Cesar Leonardo Clemente, Matthew Biggerstaff & Mauricio Santillana
1. Detecting influenza epidemics using search engine query data
Jeremy Ginsberg, Matthew H. Mohebbi, Rajan S. Patel, Lynnette Brammer, Mark S. Smolinski & Larry Brilliant Nature volume 457, pages1012–1014(2009)Cite this article
14k Accesses 2136 Citations
https://www.nature.com/articles/nature07634#Ack1
Data
https://static-content.springer.com/esm/art%3A10.1038%2Fnature07634/MediaObjects/41586_2009_BFnature07634_MOESM271_ESM.xls
Supplementary Information 2
Query fractions for the top 100 search queries, sorted by mean Z-transformed correlation with CDC-provided ILI percentages across the nine regions of the United States. (XLS 5264 kb)
2. The Parable of Google Flu: Traps in Big Data Analysis
David Lazer1,2,*, Ryan Kennedy1,3,4, Gary King3, Alessandro Vespignani5,6,3 See all authors and affiliations
Science 14 Mar 2014: Vol. 343, Issue 6176, pp. 1203-1205 DOI: 10.1126/science.1248506
data & code
https://science.sciencemag.org/content/sci/suppl/2014/03/12/343.6176.1203.DC1/1248506.Lazer.SM.revision1.pdf
dataverse_files_parable.zip
Lazer, David; Kennedy, Ryan; King, Gary; Vespignani, Alessandro, 2014, "Replication data for: The Parable of Google Flu: Traps in Big Data Analysis", https://doi.org/10.7910/DVN/24823, Harvard Dataverse, V2, UNF:5:BJh9WzZQNEeSEpV3EWs+xg== [fileUNF]
3. Improved state-level influenza nowcasting in the United States leveraging Internet-based data and network approaches
Fred S. Lu, Mohammad W. Hattab, Cesar Leonardo Clemente, Matthew Biggerstaff & Mauricio Santillana
Nature Communications volume 10, Article number: 147 (2019)
https://www.nature.com/articles/s41467-018-08082-0#data-availability
Code availability
The code supporting the results of this study is available from: https://github.com/fl16180/argonet.
Data availability
The data used in this study are available from Harvard dataverse: [https://doi.org/10.7910/DVN/L5NT70]34 Up-to-date CDC %ILI data can be obtained from CDC’s FluView Interactive application: [https://www.cdc.gov/flu/weekly/fluviewinteractive.htm].