Awad, SF; Dargham, SR; Omori, R; Pearson, F; Critchley, JA; Abu-Raddad, LJ
(2019)
Analytical Exploration of Potential Pathways by which Diabetes Mellitus Impacts Tuberculosis Epidemiology.
Sci Rep, 9 (1).
p. 8494.
ISSN 2045-2322
https://doi.org/10.1038/s41598-019-44916-7
SGUL Authors: Critchley, Julia
Abstract
We aimed to develop a conceptual framework of diabetes mellitus (DM) effects on tuberculosis (TB) natural history and treatment outcomes, and to assess the impact of these effects on TB-transmission dynamics. The model was calibrated using TB data for India. A conceptual framework was developed based on a literature review, and then translated into a mathematical model to assess the impact of the DM-on-TB effects. The impact was analyzed using TB-disease incidence hazard ratio (HR) and population attributable fraction (PAF) measures. Evidence was identified for 10 plausible DM-on-TB effects. Assuming a flat change of 300% (meaning an effect size of 3.0) for each DM-on-TB effect, the HR ranged between 1.0 (Effect 9-Recovery) and 2.7 (Effect 2-Fast progression); most effects did not have an impact on the HR. Meanwhile, TB-disease incidence attributed directly and indirectly to each effect ranged between -4.6% (Effect 7-TB mortality) and 34.5% (Effect 2-Fast progression). The second largest impact was for Effect 6-Disease infectiousness at 29.9%. In conclusion, DM can affect TB-transmission dynamics in multiple ways, most of which are poorly characterized and difficult to assess in epidemiologic studies. The indirect (e.g. onward transmission) impacts of some DM-on-TB effects are comparable in scale to the direct impacts. While the impact of several effects on the HR was limited, the impact on the PAF was substantial suggesting that DM could be impacting TB epidemiology to a larger extent than previously thought.
Item Type: |
Article
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Additional Information: |
Open Access
This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
© The Author(s) 2019 |
SGUL Research Institute / Research Centre: |
Academic Structure > Population Health Research Institute (INPH) |
Journal or Publication Title: |
Sci Rep |
ISSN: |
2045-2322 |
Language: |
eng |
Dates: |
Date | Event |
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11 June 2019 | Published | 28 May 2019 | Accepted |
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Publisher License: |
Creative Commons: Attribution 4.0 |
Projects: |
Project ID | Funder | Funder ID |
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7-627-3-167 | Qatar National Research Fund (QNRF) | UNSPECIFIED |
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PubMed ID: |
31186499 |
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Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/110934 |
Publisher's version: |
https://doi.org/10.1038/s41598-019-44916-7 |
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