Data and code for "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa"
McCreesh, N
(2026).
Data and code for "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa".
[Dataset].
London School of Hygiene & Tropical Medicine, London, United Kingdom.
10.17037/DATA.00005244.
(2026).
Data and code for "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa".
[Dataset].
London School of Hygiene & Tropical Medicine, London, United Kingdom.
10.17037/DATA.00005244.
Data and code to replicate the analyses in the paper "Influence of setting and diagnostic algorithm on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa". Dataset variables cover participant demographics, CD4TB score, TB diagnosis and symptoms, Xpert Ultra result, past instances of TB, HIV/ART status, and cavitation on chest X-ray. R code is used to generate table 1 and figure 1-2.
Additional Information
Researchers interested in the dataset are invited to complete the application form, outlining the research for which it will be used. Data will be provided subject to a light touch agreement that it should be stored securely.
Keywords
Tuberculosis; South Africa; HIV| Item Type | Dataset |
|---|---|
| Resource Type |
Resource Type Resource Description Dataset Quantitative |
| Capture method | Interview |
| Collection Period |
From To 2018 2024 |
| Date | 26 May 2026 |
| Language(s) of written materials | English |
| Creator(s) |
McCreesh, N
|
| Associated roles | Govender, I (Project Manager); Sithole, M (Data Manager); Wong, EB (Co-Investigator); Buthelezi, I (Other); Hanekom, WA (Principal Investigator); Ording-Jespersen, G (Data Manager); Siedner, MJ (Co-Investigator); Grant, AD (Principal Investigator) and Khan, PY (Co-Investigator) |
| LSHTM Faculty/Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
| Research Centre | TB Centre |
| Research Group | TB Modelling Group |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom; African Health Research Institute, Durban, South Africa |
| Funders |
Project Funder Grant Number Funder URI AHCoS R01A1147321 https://doi.org/10.13039/100000060 Vukuzazi UNSPECIFIED https://doi.org/10.13039/100016962 |
| Date Deposited | 26 May 2026 16:00 |
| Last Modified | 26 May 2026 16:00 |
| Publisher | London School of Hygiene & Tropical Medicine |
Data / Code
Dataset.csv
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subject - Data
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lock - Restricted to Request access for all
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copyright - Available under Data Sharing Agreement
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info - Anonymous dataset containing information on disease severity among people diagnosed with symptomatic and asymptomatic tuberculosis in South Africa
description - text/plain
- folder_info
- 56B
figure1.R
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subject - Data
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- Available under Creative Commons: Attribution 4.0
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info - R code for figure 1
description - text/plain
- folder_info
- 22kB
figure2.R
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subject - Data
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- Available under Creative Commons: Attribution 4.0
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info - R code for figure 2
description - text/plain
- folder_info
- 16kB
Documentation
Dataset_codebook.html
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subject - Documentation
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- Available under Creative Commons: Attribution 4.0
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info - Dataset codebook
html - text/html
- folder_info
- 7kB
Clinic_study_consent_forms.pdf
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subject - Documentation
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- Available under Creative Commons: Attribution 4.0
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info - Clinic study consent forms
picture_as_pdf - application/pdf
- folder_info
- 459kB
Clinic_study_guardian_consent_form.pdf
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subject - Documentation
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- Available under Creative Commons: Attribution 4.0
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info - Clinic study guardian consent form
picture_as_pdf - application/pdf
- folder_info
- 247kB
Community_study_consent_form.pdf
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subject - Documentation
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- Available under Creative Commons: Attribution 4.0
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info - Community study consent form
picture_as_pdf - application/pdf
- folder_info
- 270kB
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