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Tuberculosis case finding using population-based disease surveillance platforms in urban and rural Kenya

Overview of attention for article published in BMC Infectious Diseases, June 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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1 policy source
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2 X users

Citations

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11 Dimensions

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75 Mendeley
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Title
Tuberculosis case finding using population-based disease surveillance platforms in urban and rural Kenya
Published in
BMC Infectious Diseases, June 2018
DOI 10.1186/s12879-018-3172-z
Pubmed ID
Authors

Godfrey Bigogo, Kevin Cain, Diana Nyole, Geoffrey Masyongo, Joshua Auko Auko, Newton Wamola, Albert Okumu, Janet Agaya, Joel Montgomery, Martien Borgdorff, Deron Burton

Abstract

Tuberculosis (TB) case finding is an important component of TB control because it can reduce transmission of Mycobacterium tuberculosis (MTB) through prompt detection and treatment of infectious patients. Using population-based infectious disease surveillance (PBIDS) platforms with links to health facilities in Kenya we implemented intensified TB case finding in the community and at the health facilities, as an adjunct to routine passive case finding conducted by the national TB program. From 2011 to 2014, PBIDS participants ≥15 years were screened either at home or health facilities for possible TB symptoms which included cough, fever, night sweats or weight loss in the preceding 2 weeks. At home, participants with possible TB symptoms had expectorated sputum collected. At the clinic, HIV-infected participants with possible TB symptoms were invited to produce sputum. Those without HIV but with symptoms lasting 7 days including the visit day had chest radiographs performed, and had sputum collected if the radiographs were abnormal. Sputum samples were tested for the presence of MTB using the Xpert MTB/RIF assay. TB detection rates were calculated per 100,000 persons screened. Of 11,191 participants aged ≥15 years screened at home at both sites, 2695 (23.9%) reported possible TB symptoms, of whom 2258 (83.8%) produced sputum specimens. MTB was detected in 32 (1.4%) of the specimens resulting in a detection rate of 286/100,000 persons screened. At the health facilities, a total of 11,762 person were screened, 7500 (63.8%) had possible TB symptoms of whom 1282 (17.1%) produced sputum samples. MTB was detected in 69 (5.4%) of the samples, resulting in an overall detection rate of 587/100,000 persons screened. The TB detection rate was higher in persons with HIV compared to those without at both home (HIV-infected - 769/100,000, HIV-uninfected 141/100,000, rate ratio (RR) - 5.45, 95% CI 3.25-22.37), and health facilities (HIV-infected 3399/100,000, HIV-uninfected 294/100,000, RR 11.56, 95% CI 6.18-18.44). Facility-based intensified TB case finding detected more TB cases per the number of specimens tested and the number of persons screened, including those with HIV, than home-based TB screening and should be further evaluated to determine its potential programmatic impact.

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The data shown below were collected from the profiles of 2 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 75 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 20%
Student > Ph. D. Student 9 12%
Researcher 8 11%
Student > Bachelor 5 7%
Lecturer 3 4%
Other 8 11%
Unknown 27 36%
Readers by discipline Count As %
Medicine and Dentistry 15 20%
Nursing and Health Professions 12 16%
Mathematics 5 7%
Immunology and Microbiology 3 4%
Social Sciences 3 4%
Other 7 9%
Unknown 30 40%
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 01 June 2019.
All research outputs
#6,893,001
of 23,088,369 outputs
Outputs from BMC Infectious Diseases
#2,176
of 7,748 outputs
Outputs of similar age
#118,650
of 329,367 outputs
Outputs of similar age from BMC Infectious Diseases
#42
of 135 outputs
Altmetric has tracked 23,088,369 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 7,748 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 71% 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 329,367 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 63% of its contemporaries.
We're also able to compare this research output to 135 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 68% of its contemporaries.