dc.contributor.author |
Nelson, Kristin N.
|
|
dc.contributor.author |
Jenness, Samuel M.
|
|
dc.contributor.author |
Mathema, Barun
|
|
dc.contributor.author |
Lopman, Benjamin A.
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|
dc.contributor.author |
Auld, Sara C.
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|
dc.contributor.author |
Shah, N. Sarita
|
|
dc.contributor.author |
Brust, James C.M.
|
|
dc.contributor.author |
Ismail, Nazir Ahmed
|
|
dc.contributor.author |
Omar, Shaheed Vally
|
|
dc.contributor.author |
Brown, Tyler S.
|
|
dc.contributor.author |
Allana, Salim
|
|
dc.contributor.author |
Campbell, Angie
|
|
dc.contributor.author |
Moodley, Pravi
|
|
dc.contributor.author |
Mlisana, Koleka
|
|
dc.contributor.author |
Gandhi, Neel R.
|
|
dc.date.accessioned |
2021-05-13T06:20:20Z |
|
dc.date.available |
2021-05-13T06:20:20Z |
|
dc.date.issued |
2020-06 |
|
dc.description.abstract |
BACKGROUND: Tuberculosis (TB) is the leading infectious cause of death globally, and drug-resistant TB strains pose a serious threat to controlling the global TB epidemic. The clinical features, locations, and social factors driving transmission in settings with high incidences of drug-resistant TB are poorly understood.
METHODS : We measured a network of genomic links using Mycobacterium tuberculosis whole-genome sequences. RESULTS : Patients with 2–3 months of cough or who spent time in urban locations were more likely to be linked in the network, while patients with sputum smear–positive disease were less likely to be linked than those with smear-negative disease. Associations persisted using different thresholds to define genomic links and irrespective of assumptions about the direction of transmission.
CONCLUSIONS : Identifying factors that lead to many transmissions, including contact with urban areas, can suggest settings instrumental in transmission and indicate optimal locations and groups to target with interventions. |
en_ZA |
dc.description.department |
Medical Microbiology |
en_ZA |
dc.description.librarian |
hj2021 |
en_ZA |
dc.description.uri |
http://cid.oxfordjournals.org |
en_ZA |
dc.identifier.citation |
Nelson, K.N., Jenness, S.M., Mathema, B. et al. 2020, 'Social mixing and clinical features linked with transmission in a network of extensively drug-resistant Tuberculosis cases in KwaZulu-Natal, South Africa', Clinical Infectious Diseases, vol. 70, no. 11, pp. 2396-2402, https://doi.org/10.1093/cid/ciz636. |
en_ZA |
dc.identifier.issn |
1058-4838 (print) |
|
dc.identifier.issn |
1537-6591 (online) |
|
dc.identifier.other |
10.1093/cid/ciz636 |
|
dc.identifier.uri |
http://hdl.handle.net/2263/79866 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Oxford University Press |
en_ZA |
dc.rights |
© The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. . This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Clinical Infectious Diseases following peer review. The definitive publisher-authenticated version is : 'Social mixing and clinical features linked with transmission in a network of extensively drug-resistant Tuberculosis cases in KwaZulu-Natal, South Africa', Clinical Infectious Diseases, vol. 70, no. 11, pp. 2396-2402, 2020, doi : 10.1093/cid/ciz636, is available online at : http://cid.oxfordjournals.org. |
en_ZA |
dc.subject |
Drug-resistant tuberculosis |
en_ZA |
dc.subject |
Tuberculosis (TB) |
en_ZA |
dc.subject |
Tuberculosis transmission |
en_ZA |
dc.subject |
Whole genome sequencing (WGS) |
en_ZA |
dc.subject |
Transmission networks |
en_ZA |
dc.subject |
Network models |
en_ZA |
dc.title |
Social mixing and clinical features linked with transmission in a network of extensively drug-resistant tuberculosis cases in KwaZulu-Natal, South Africa |
en_ZA |
dc.type |
Postprint Article |
en_ZA |