Estimating the contribution of subclinical tuberculosis disease to transmission: an individual patient data analysis from prevalence surveys

Emery, J.C. orcid.org/0000-0001-6644-7604, Dodd, P.J., Banu, S. et al. (18 more authors) (2023) Estimating the contribution of subclinical tuberculosis disease to transmission: an individual patient data analysis from prevalence surveys. eLife, 2023 (12). e82469. ISSN 2050-084X

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2023 Emery et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Keywords: Mtb transmission; asymptomatic transmission; asymptomatic tuberculosis; epidemiology; global health; household Mtb infection surveys; human; infectious disease; mathematical modelling; microbiology; subclinical transmission; Humans; Prevalence; Tuberculosis; Tuberculosis, Pulmonary; Mycobacterium tuberculosis; Asia
Dates:
  • Accepted: 4 August 2023
  • Published (online): 18 December 2023
  • Published: 18 December 2023
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health
Depositing User: Symplectic Sheffield
Date Deposited: 05 Jan 2024 12:24
Last Modified: 05 Jan 2024 12:24
Published Version: http://dx.doi.org/10.7554/elife.82469
Status: Published
Publisher: eLife Sciences Publications, Ltd
Refereed: Yes
Identification Number: https://doi.org/10.7554/elife.82469
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