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Assessing Commitment and Reporting Fidelity to a Text Message-Based Participatory Surveillance in Rural Western Uganda

Overview of attention for article published in PLOS ONE, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
6 X users

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
67 Mendeley
Title
Assessing Commitment and Reporting Fidelity to a Text Message-Based Participatory Surveillance in Rural Western Uganda
Published in
PLOS ONE, June 2016
DOI 10.1371/journal.pone.0155971
Pubmed ID
Authors

James Lester, Sarah Paige, Colin A. Chapman, Mhairi Gibson, James Holland Jones, William M. Switzer, Nelson Ting, Tony L. Goldberg, Simon D. W. Frost

Abstract

Syndromic surveillance, the collection of symptom data from individuals prior to or in the absence of diagnosis, is used throughout the developed world to provide rapid indications of outbreaks and unusual patterns of disease. However, the low cost of syndromic surveillance also makes it highly attractive for the developing world. We present a case study of electronic participatory syndromic surveillance, using participant-mobile phones in a rural region of Western Uganda, which has a high infectious disease burden, and frequent local and regional outbreaks. Our platform uses text messages to encode a suite of symptoms, their associated durations, and household disease burden, and we explore the ability of participants to correctly encode their symptoms, with an average of 75.2% of symptom reports correctly formatted between the second and 11th reporting timeslots. Concomitantly we identify divisions between participants able to rapidly adjust to this unusually participatory style of data collection, and those few for whom the study proved more challenging. We then perform analyses of the resulting syndromic time series, examining the clustering of symptoms by time and household to identify patterns such as a tendency towards the within-household sharing of respiratory illness.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 1%
Unknown 66 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 19%
Student > Master 13 19%
Student > Ph. D. Student 7 10%
Student > Bachelor 4 6%
Student > Postgraduate 3 4%
Other 11 16%
Unknown 16 24%
Readers by discipline Count As %
Medicine and Dentistry 11 16%
Nursing and Health Professions 8 12%
Agricultural and Biological Sciences 6 9%
Computer Science 6 9%
Social Sciences 6 9%
Other 13 19%
Unknown 17 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 18 June 2016.
All research outputs
#1,667,000
of 22,876,619 outputs
Outputs from PLOS ONE
#21,505
of 195,157 outputs
Outputs of similar age
#32,342
of 343,019 outputs
Outputs of similar age from PLOS ONE
#490
of 4,674 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 195,157 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has done well, scoring higher than 88% 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 343,019 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 4,674 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.