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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

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (73rd percentile)

Mentioned by

twitter
5 tweeters

Citations

dimensions_citation
27 Dimensions

Readers on

mendeley
82 Mendeley
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.

Twitter Demographics

The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 82 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 79 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 24%
Researcher 15 18%
Student > Ph. D. Student 12 15%
Student > Bachelor 10 12%
Student > Postgraduate 10 12%
Other 15 18%
Readers by discipline Count As %
Medicine and Dentistry 27 33%
Agricultural and Biological Sciences 9 11%
Social Sciences 6 7%
Unspecified 6 7%
Computer Science 5 6%
Other 29 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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
#3,424,035
of 12,373,180 outputs
Outputs from BMC Infectious Diseases
#1,142
of 4,592 outputs
Outputs of similar age
#73,661
of 273,080 outputs
Outputs of similar age from BMC Infectious Diseases
#162
of 637 outputs
Altmetric has tracked 12,373,180 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 4,592 research outputs from this source. They receive a mean Attention Score of 4.8. This one has gotten more attention than average, scoring higher than 74% 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 273,080 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 72% of its contemporaries.
We're also able to compare this research output to 637 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 73% of its contemporaries.