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

2019 ◽  
Author(s):  
Kristin N. Nelson ◽  
Neel R. Gandhi ◽  
Barun Mathema ◽  
Benjamin A. Lopman ◽  
James C.M. Brust ◽  
...  
Keyword(s):  
South Africa ◽  
Missing At Random ◽  
Biased Sampling ◽  
Drug Resistant ◽  
Sequencing Data ◽  
Bias Analysis ◽  
Drug Resistant Tuberculosis ◽  
Resistant Tuberculosis ◽  
Extensively Drug Resistant ◽  
Incident Cases

ABSTRACTThe transmission patterns of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases in 2017. Modeling TB transmission networks can provide insight into the nature and drivers of transmission, but incomplete and non-random sampling of TB cases can pose challenges to making inferences from epidemiologic and molecular data. We conducted a quantitative bias analysis to assess the effect of missing cases on a transmission network inferred from Mtb sequencing data on extensively drug-resistant (XDR) TB cases in South Africa. We tested scenarios in which cases were missing at random, differentially by clinical characteristics, or differentially by transmission (i.e., cases with many links were under or over-sampled). Under the assumption cases were missing at random, cases in the complete, modeled network would have had a mean of 20 or more transmission links, which is far higher than expected, in order to reproduce the observed, partial network. Instead, we found that the most likely scenario involved undersampling of high-transmitting cases, and further models provided evidence for superspreading behavior. This is, to our knowledge, the first study to define and assess the support for different mechanisms of missingness in a study of TB transmission. Our findings should caution interpretation of results of future studies of TB transmission in high-incidence settings, given the potential for biased sampling, and should motivate further research aimed at identifying the specific host, pathogen, or environmental factors contributing to superspreading.

scholarly journals Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa

2020 ◽  
Vol 189 (7) ◽  
pp. 735-745
Author(s):  
Kristin N Nelson ◽  
Neel R Gandhi ◽  
Barun Mathema ◽  
Benjamin A Lopman ◽  
James C M Brust ◽  
...  
Keyword(s):  
South Africa ◽  
Missing At Random ◽  
Drug Resistant ◽  
Sequencing Data ◽  
Drug Resistant Tuberculosis ◽  
Resistant Tuberculosis ◽  
Extensively Drug Resistant ◽  
Kwazulu Natal ◽  
Incident Cases ◽  
Incomplete Sampling

Abstract Patterns 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.

scholarly journals Genome Analysis of Multi- and Extensively-Drug-Resistant Tuberculosis from KwaZulu-Natal, South Africa

PLoS ONE ◽  
2009 ◽  
Vol 4 (11) ◽  
pp. e7778 ◽  
Author(s):  
Thomas R. Ioerger ◽  
Sunwoo Koo ◽  
Eun-Gyu No ◽  
Xiaohua Chen ◽  
Michelle H. Larsen ◽  
...  
Keyword(s):  
South Africa ◽  
Genome Analysis ◽  
Drug Resistant ◽  
Drug Resistant Tuberculosis ◽  
Resistant Tuberculosis ◽  
Extensively Drug Resistant ◽  
Kwazulu Natal

Long-term outcomes of patients with extensively drug-resistant tuberculosis in South Africa: a cohort study

The Lancet ◽  
2014 ◽  
Vol 383 (9924) ◽  
pp. 1230-1239 ◽  
Author(s):  
Elize Pietersen ◽  
Elisa Ignatius ◽  
Elizabeth M Streicher ◽  
Barbara Mastrapa ◽  
Xavier Padanilam ◽  
...  
Keyword(s):  
South Africa ◽  
Cohort Study ◽  
Drug Resistant ◽  
Long Term Outcomes ◽  
Drug Resistant Tuberculosis ◽  
Resistant Tuberculosis ◽  
Extensively Drug Resistant

scholarly journals Cost-effectiveness of bedaquiline, pretomanid and linezolid for treatment of extensively drug-resistant tuberculosis in South Africa, Georgia and the Philippines

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e051521
Author(s):  
Gabriela Beatriz Gomez ◽  
Mariana Siapka ◽  
Francesca Conradie ◽  
Norbert Ndjeka ◽  
Anna Marie Celina Garfin ◽  
...  
Keyword(s):  
South Africa ◽  
Cost Effectiveness ◽  
Standard Of Care ◽  
The Philippines ◽  
List Price ◽  
Drug Resistant ◽  
Drug Resistant Tuberculosis ◽  
Resistant Tuberculosis ◽  
Extensively Drug Resistant ◽  
Mdr Tb

ObjectivesPatients with highly resistant tuberculosis have few treatment options. Bedaquiline, pretomanid and linezolid regimen (BPaL) is a new regimen shown to have favourable outcomes after six months. We present an economic evaluation of introducing BPaL against the extensively drug-resistant tuberculosis (XDR-TB) standard of care in three epidemiological settings.DesignCost-effectiveness analysis using Markov cohort model.SettingSouth Africa, Georgia and the Philippines.ParticipantsXDR-TB and multidrug-resistant tuberculosis (MDR-TB) failure and treatment intolerant patients.InterventionsBPaL regimen.Primary and secondary outcome measures(1) Incremental cost per disability-adjusted life years averted by using BPaL against standard of care at the Global Drug Facility list price. (2) The potential maximum price at which the BPaL regimen could become cost neutral.ResultsBPaL for XDR-TB is likely to be cost saving in all study settings when pretomanid is priced at the Global Drug Facility list price. The magnitude of these savings depends on the prevalence of XDR-TB in the country and can amount, over 5 years, to approximately US$ 3 million in South Africa, US$ 200 000 and US$ 60 000 in Georgia and the Philippines, respectively. In South Africa, related future costs of antiretroviral treatment (ART) due to survival of more patients following treatment with BPaL reduced the magnitude of expected savings to approximately US$ 1 million. Overall, when BPaL is introduced to a wider population, including MDR-TB treatment failure and treatment intolerant, we observe increased savings and clinical benefits. The potential threshold price at which the probability of the introduction of BPaL becoming cost neutral begins to increase is higher in Georgia and the Philippines (US$ 3650 and US$ 3800, respectively) compared with South Africa (US$ 500) including ART costs.ConclusionsOur results estimate that BPaL can be a cost-saving addition to the local TB programmes in varied programmatic settings.

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