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Using internet search queries for infectious disease surveillance: screening diseases for suitability

Overview of attention for article published in BMC Infectious Diseases, December 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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133 Mendeley
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Title
Using internet search queries for infectious disease surveillance: screening diseases for suitability
Published in
BMC Infectious Diseases, December 2014
DOI 10.1186/s12879-014-0690-1
Pubmed ID
Authors

Gabriel J Milinovich, Simon M R Avril, Archie C A Clements, John S Brownstein, Shilu Tong, Wenbiao Hu

Abstract

BackgroundInternet-based surveillance systems provide a novel approach to monitoring infectious diseases. Surveillance systems built on internet data are economically, logistically and epidemiologically appealing and have shown significant promise. The potential for these systems has increased with increased internet availability and shifts in health-related information seeking behaviour. This approach to monitoring infectious diseases has, however, only been applied to single or small groups of select diseases. This study aims to systematically investigate the potential for developing surveillance and early warning systems using internet search data, for a wide range of infectious diseases.MethodsOfficial notifications for 64 infectious diseases in Australia were downloaded and correlated with frequencies for 164 internet search terms for the period 2009¿13 using Spearman¿s rank correlations. Time series cross correlations were performed to assess the potential for search terms to be used in construction of early warning systems.ResultsNotifications for 17 infectious diseases (26.6%) were found to be significantly correlated with a selected search term. The use of internet metrics as a means of surveillance has not previously been described for 12 (70.6%) of these diseases. The majority of diseases identified were vaccine-preventable, vector-borne or sexually transmissible; cross correlations, however, indicated that vector-borne and vaccine preventable diseases are best suited for development of early warning systems.ConclusionsThe findings of this study suggest that internet-based surveillance systems have broader applicability to monitoring infectious diseases than has previously been recognised. Furthermore, internet-based surveillance systems have a potential role in forecasting emerging infectious disease events, especially for vaccine-preventable and vector-borne diseases.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 133 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 2%
United States 1 <1%
Unknown 130 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 25 19%
Researcher 20 15%
Student > Ph. D. Student 15 11%
Student > Bachelor 14 11%
Student > Postgraduate 13 10%
Other 28 21%
Unknown 18 14%
Readers by discipline Count As %
Medicine and Dentistry 38 29%
Agricultural and Biological Sciences 12 9%
Computer Science 11 8%
Social Sciences 6 5%
Psychology 4 3%
Other 38 29%
Unknown 24 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2015.
All research outputs
#13,069,608
of 22,775,504 outputs
Outputs from BMC Infectious Diseases
#3,111
of 7,670 outputs
Outputs of similar age
#166,619
of 352,205 outputs
Outputs of similar age from BMC Infectious Diseases
#68
of 187 outputs
Altmetric has tracked 22,775,504 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,670 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,205 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 187 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.