Modeling missing cases and transmission links in networks of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa

dc.contributor.authorNelson, Kristin N.
dc.contributor.authorGandhi, Neel R.
dc.contributor.authorMathema, Barun
dc.contributor.authorLopman, Benjamin A.
dc.contributor.authorBrust, James C.M.
dc.contributor.authorAuld, Sara C.
dc.contributor.authorIsmail, Nazir Ahmed
dc.contributor.authorOmar, Shaheed Vally
dc.contributor.authorBrown, Tyler S.
dc.contributor.authorAllana, Salim
dc.contributor.authorCampbell, Angie
dc.contributor.authorMoodley, Pravi
dc.contributor.authorMlisana, Koleka
dc.contributor.authorShah, N. Sarita
dc.contributor.authorJenness, Samuel M.
dc.date.accessioned2021-08-03T08:09:24Z
dc.date.available2021-08-03T08:09:24Z
dc.date.issued2020-07
dc.descriptionThis work was presented at the Seventh International Conference on Infectious Disease Dynamics (Epidemics7), Charleston, South Carolina, December 3–6, 2019.en_ZA
dc.description.abstractPatterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011–2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.en_ZA
dc.description.departmentMedical Microbiologyen_ZA
dc.description.librarianhj2021en_ZA
dc.description.sponsorshipThe National Institute of Allergy and Infectious Diseases, US National Institutes of Health, the National Institute of Allergy and Infectious Diseases, the Emory Center for AIDS Research, the Einstein Center for AIDS Research and the Einstein/Montefiore Institute for Clinical and Translational Research.en_ZA
dc.description.urihttps://academic.oup.com/ajeen_ZA
dc.identifier.citationNelson, K.N., Gandhi, N.R., Mathema, B. et al. 2020, 'Modeling missing cases and transmission links in networks of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa', American Journal of Epidemiology, vol. 189, no. 7, pp. 735-745.en_ZA
dc.identifier.issn0002-9262 (print)
dc.identifier.issn1476-6256 (online)
dc.identifier.other10.1093/aje/kwaa028
dc.identifier.urihttp://hdl.handle.net/2263/81099
dc.language.isoenen_ZA
dc.publisherOxford University Pressen_ZA
dc.rights© The Author(s) 2020. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. This is a pre-copy-editing, author-produced PDF of an article accepted for publication in American Journal of Epidemiology following peer review. The definitive publisher-authenticated version is : 'Modeling missing cases and transmission links in networks of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa', American Journal of Epidemiology, vol. 189, no. 7, pp. 735-745, 2020. doi : 10.1093/aje/kwaa028, is available online at : https://academic.oup.com/aje.en_ZA
dc.subjectTuberculosis (TB)en_ZA
dc.subjectBias analysisen_ZA
dc.subjectDrug-resistant tuberculosisen_ZA
dc.subjectMissing dataen_ZA
dc.subjectNetwork modelingen_ZA
dc.subjectTuberculosis transmissionen_ZA
dc.subjectWhole genome sequencing (WGS)en_ZA
dc.subjectMycobacterium tuberculosis (MTB)en_ZA
dc.subjectSouth Africa (SA)en_ZA
dc.subjectExtensively drug-resistant (XDR)en_ZA
dc.titleModeling missing cases and transmission links in networks of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africaen_ZA
dc.typePostprint Articleen_ZA

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