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Small contribution of gold mines to the ongoing tuberculosis epidemic in South Africa: a modeling-based study

Overview of attention for article published in BMC Medicine, April 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)

Mentioned by

news
2 news outlets
twitter
7 tweeters

Citations

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5 Dimensions

Readers on

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64 Mendeley
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Title
Small contribution of gold mines to the ongoing tuberculosis epidemic in South Africa: a modeling-based study
Published in
BMC Medicine, April 2018
DOI 10.1186/s12916-018-1037-3
Pubmed ID
Authors

Stewart T. Chang, Violet N. Chihota, Katherine L. Fielding, Alison D. Grant, Rein M. Houben, Richard G. White, Gavin J. Churchyard, Philip A. Eckhoff, Bradley G. Wagner

Abstract

Gold mines represent a potential hotspot for Mycobacterium tuberculosis (Mtb) transmission and may be exacerbating the tuberculosis (TB) epidemic in South Africa. However, the presence of multiple factors complicates estimation of the mining contribution to the TB burden in South Africa. We developed two models of TB in South Africa, a static risk model and an individual-based model that accounts for longer-term trends. Both models account for four populations - mine workers, peri-mining residents, labor-sending residents, and other residents of South Africa - including the size and prevalence of latent TB infection, active TB, and HIV of each population and mixing between populations. We calibrated to mine- and country-level data and used the static model to estimate force of infection (FOI) and new infections attributable to local residents in each community compared to other residents. Using the individual-based model, we simulated a counterfactual scenario to estimate the fraction of overall TB incidence in South Africa attributable to recent transmission in mines. We estimated that the majority of FOI in each community is attributable to local residents: 93.9% (95% confidence interval 92.4-95.1%), 91.5% (91.4-91.5%), and 94.7% (94.7-94.7%) in gold mining, peri-mining, and labor-sending communities, respectively. Assuming a higher rate of Mtb transmission in mines, 4.1% (2.6-5.8%), 5.0% (4.5-5.5%), and 9.0% (8.8-9.1%) of new infections in South Africa are attributable to gold mine workers, peri-mining residents, and labor-sending residents, respectively. Therefore, mine workers with TB disease, who constitute ~ 2.5% of the prevalent TB cases in South Africa, contribute 1.62 (1.04-2.30) times as many new infections as TB cases in South Africa on average. By modeling TB on a longer time scale, we estimate 63.0% (58.5-67.7%) of incident TB disease in gold mining communities to be attributable to recent transmission, of which 92.5% (92.1-92.9%) is attributable to local transmission. Gold mine workers are estimated to contribute a disproportionately large number of Mtb infections in South Africa on a per-capita basis. However, mine workers contribute only a small fraction of overall Mtb infections in South Africa. Our results suggest that curtailing transmission in mines may have limited impact at the country level, despite potentially significant impact at the mining level.

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 20%
Student > Bachelor 10 16%
Student > Ph. D. Student 9 14%
Student > Master 8 13%
Student > Doctoral Student 3 5%
Other 8 13%
Unknown 13 20%
Readers by discipline Count As %
Medicine and Dentistry 12 19%
Nursing and Health Professions 9 14%
Mathematics 6 9%
Agricultural and Biological Sciences 4 6%
Computer Science 3 5%
Other 14 22%
Unknown 16 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 24. 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 12 June 2020.
All research outputs
#1,042,962
of 17,944,974 outputs
Outputs from BMC Medicine
#809
of 2,753 outputs
Outputs of similar age
#28,916
of 289,504 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 17,944,974 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,753 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.3. This one has gotten more attention than average, scoring higher than 70% 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 289,504 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 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them