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Respiratory syncytial virus tracking using internet search engine data

Overview of attention for article published in BMC Public Health, April 2018
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  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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7 X users

Citations

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20 Dimensions

Readers on

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44 Mendeley
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Title
Respiratory syncytial virus tracking using internet search engine data
Published in
BMC Public Health, April 2018
DOI 10.1186/s12889-018-5367-z
Pubmed ID
Authors

Eyal Oren, Justin Frere, Eran Yom-Tov, Elad Yom-Tov

Abstract

Respiratory Syncytial Virus (RSV) is the leading cause of hospitalization in children less than 1 year of age in the United States. Internet search engine queries may provide high resolution temporal and spatial data to estimate and predict disease activity. After filtering an initial list of 613 symptoms using high-resolution Bing search logs, we used Google Trends data between 2004 and 2016 for a smaller list of 50 terms to build predictive models of RSV incidence for five states where long-term surveillance data was available. We then used domain adaptation to model RSV incidence for the 45 remaining US states. Surveillance data sources (hospitalization and laboratory reports) were highly correlated, as were laboratory reports with search engine data. The four terms which were most often statistically significantly correlated as time series with the surveillance data in the five state models were RSV, flu, pneumonia, and bronchiolitis. Using our models, we tracked the spread of RSV by observing the time of peak use of the search term in different states. In general, the RSV peak moved from south-east (Florida) to the north-west US. Our study represents the first time that RSV has been tracked using Internet data results and highlights successful use of search filters and domain adaptation techniques, using data at multiple resolutions. Our approach may assist in identifying spread of both local and more widespread RSV transmission and may be applicable to other seasonal conditions where comprehensive epidemiological data is difficult to collect or obtain.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 18%
Student > Ph. D. Student 7 16%
Student > Master 6 14%
Student > Bachelor 3 7%
Other 3 7%
Other 9 20%
Unknown 8 18%
Readers by discipline Count As %
Medicine and Dentistry 15 34%
Computer Science 4 9%
Nursing and Health Professions 3 7%
Business, Management and Accounting 2 5%
Engineering 2 5%
Other 8 18%
Unknown 10 23%
Attention Score in Context

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 06 March 2019.
All research outputs
#7,235,526
of 23,035,022 outputs
Outputs from BMC Public Health
#7,591
of 15,002 outputs
Outputs of similar age
#126,174
of 329,113 outputs
Outputs of similar age from BMC Public Health
#216
of 312 outputs
Altmetric has tracked 23,035,022 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 15,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 329,113 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 61% of its contemporaries.
We're also able to compare this research output to 312 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.