Dataset Information

Tuberculosis in Cape Town: An age-structured transmission model.

ABSTRACT: BACKGROUND:Tuberculosis (TB) is the leading cause of death in South Africa. The burden of disease varies by age, with peaks in TB notification rates in the HIV-negative population at ages 0-5, 20-24, and 45-49 years. There is little variation between age groups in the rates in the HIV-positive population. The drivers of this age pattern remain unknown. METHODS:We developed an age-structured simulation model of Mycobacterium tuberculosis (Mtb) transmission in Cape Town, South Africa. We considered five states of TB progression: susceptible, infected (latent TB), active TB, treated TB, and treatment default. Latently infected individuals could be re-infected; a previous Mtb infection slowed progression to active disease. We further considered three states of HIV progression: HIV negative, HIV positive, on antiretroviral therapy. To parameterize the model, we analysed treatment outcomes from the Cape Town electronic TB register, social mixing patterns from a Cape Town community and used literature estimates for other parameters. To investigate the main drivers behind the age patterns, we conducted sensitivity analyses on all parameters related to the age structure. RESULTS:The model replicated the age patterns in HIV-negative TB notification rates of Cape Town in 2009. Simulated TB notification rate in HIV-negative patients was 1000/100,000 person-years (pyrs) in children aged <5 years and decreased to 51/100,000 in children 5-15 years. The peak in early adulthood occurred at 25-29 years (463/100,000 pyrs). After a subsequent decline, simulated TB notification rates gradually increased from the age of 30 years. Sensitivity analyses showed that the dip after the early adult peak was due to the protective effect of latent TB and that retreatment TB was mainly responsible for the rise in TB notification rates from the age of 30 years. CONCLUSION:The protective effect of a first latent infection on subsequent infections and the faster progression in previously treated patients are the key determinants of the age-structure of TB notification rates in Cape Town.

SUBMITTER: Blaser N

PROVIDER: S-EPMC4791535 | biostudies-literature | 2016 Mar

REPOSITORIES: biostudies-literature

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Tuberculosis in Cape Town: An age-structured transmission model.

Blaser Nello N Zahnd Cindy C Hermans Sabine S Salazar-Vizcaya Luisa L Estill Janne J Morrow Carl C Egger Matthias M Keiser Olivia O Wood Robin R

Epidemics 20151020

<h4>Background</h4>Tuberculosis (TB) is the leading cause of death in South Africa. The burden of disease varies by age, with peaks in TB notification rates in the HIV-negative population at ages 0-5, 20-24, and 45-49 years. There is little variation between age groups in the rates in the HIV-positive population. The drivers of this age pattern remain unknown.<h4>Methods</h4>We developed an age-structured simulation model of Mycobacterium tuberculosis (Mtb) transmission in Cape Town, South Afric ...[more]

PMID: 26972514

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Project description:BackgroundExperimental data show that drug-resistance-conferring mutations are often associated with a decrease in the replicative fitness of bacteria in vitro, and that this fitness cost can be mitigated by compensatory mutations; however, the role of compensatory evolution in clinical settings is less clear. We assessed whether compensatory evolution was associated with increased transmission of rifampicin-resistant tuberculosis in Khayelitsha, Cape Town, South Africa.MethodsWe did a genomic epidemiological study by analysing available M tuberculosis isolates and their associated clinical data from individuals routinely diagnosed with rifampicin-resistant tuberculosis in primary care and hospitals in Khayelitsha, Cape Town, South Africa. Isolates were collected as part of a previous study. All individuals diagnosed with rifampicin-resistant tuberculosis and with linked biobanked specimens were included in this study. We applied whole-genome sequencing, Bayesian reconstruction of transmission trees, and phylogenetic multivariable regression analysis to identify individual and bacterial factors associated with the transmission of rifampicin-resistant M tuberculosis strains.FindingsBetween Jan 1, 2008, and Dec 31, 2017, 2161 individuals were diagnosed with multidrug-resistant or rifampicin-resistant tuberculosis in Khayelitsha, Cape Town, South Africa. Whole-genome sequences were available for 1168 (54%) unique individual M tuberculosis isolates. Compensatory evolution was associated with smear-positive pulmonary disease (adjusted odds ratio 1·49, 95% CI 1·08-2·06) and a higher number of drug-resistance-conferring mutations (incidence rate ratio 1·38, 95% CI 1·28-1·48). Compensatory evolution was also associated with increased transmission of rifampicin-resistant disease between individuals (adjusted odds ratio 1·55; 95% CI 1·13-2·12), independent of other patient and bacterial factors.InterpretationOur findings suggest that compensatory evolution enhances the in vivo fitness of drug-resistant M tuberculosis genotypes, both within and between patients, and that the in vitro replicative fitness of rifampicin-resistant M tuberculosis measured in the laboratory correlates with the bacterial fitness measured in clinical settings. These results emphasise the importance of enhancing surveillance and monitoring efforts to prevent the emergence of highly transmissible clones capable of rapidly accumulating new drug resistance mutations. This concern becomes especially crucial at present, because treatment regimens incorporating novel drugs are being implemented.FundingFunding for this study was provided by a Swiss and South Africa joint research award (grant numbers 310030_188888, CRSII5_177163, and IZLSZ3_170834), the European Research Council (grant number 883582), and a Wellcome Trust fellowship (to HC; reference number 099818/Z/12/Z). ZS-D was funded through a PhD scholarship from the South African National Research Foundation and RMW was funded through the South African Medical Research Council.

Project description:BackgroundTrachoma, the worldwide leading infectious cause of blindness, is due to repeated conjunctival infection with Chlamydia trachomatis. The effects of control interventions on population levels of infection and active disease can be promptly measured, but the effects on severe ocular sequelae require long-term monitoring. We present an age-structured mathematical model of trachoma transmission and disease to predict the impact of interventions on the prevalence of blinding trachoma.Methodology/principal findingsThe model is based on the concept of multiple reinfections leading to progressive conjunctival scarring, trichiasis, corneal opacity and blindness. It also includes aspects of trachoma natural history, such as an increasing rate of recovery from infection and a decreasing chlamydial load with subsequent infections that depend upon a (presumed) acquired immunity that clears infection with age more rapidly. Parameters were estimated using maximum likelihood by fitting the model to pre-control infection prevalence data from hypo-, meso- and hyperendemic communities from The Gambia and Tanzania. The model reproduces key features of trachoma epidemiology: 1) the age-profile of infection prevalence, which increases to a peak at very young ages and declines at older ages; 2) a shift in this prevalence peak, toward younger ages in higher force of infection environments; 3) a raised overall profile of infection prevalence with higher force of infection; and 4) a rising profile, with age, of the prevalence of the ensuing severe sequelae (trachomatous scarring, trichiasis), as well as estimates of the number of infections that need to occur before these sequelae appear.Conclusions/significanceWe present a framework that is sufficiently comprehensive to examine the outcomes of the A (antibiotic) component of the SAFE strategy on disease. The suitability of the model for representing population-level patterns of infection and disease sequelae is discussed in view of the individual processes leading to these patterns.

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Project description:BackgroundBedaquiline is a life-saving tuberculosis drug undergoing global scale-up. People at risk of weak tuberculosis drug regimens are a priority for novel drug access despite the potential source of Mycobacterium tuberculosis-resistant strains. We aimed to characterise bedaquiline resistance in individuals who had sustained culture positivity during bedaquiline-based treatment.MethodsWe did a retrospective longitudinal cohort study of adults (aged ≥18 years) with culture-positive pulmonary tuberculosis who received at least 4 months of a bedaquiline-containing regimen from 12 drug-resistant tuberculosis treatment facilities in Cape Town, South Africa, between Jan 20, 2016, and Nov 20, 2017. Sputum was programmatically collected at baseline (ie, before bedaquiline initiation) and each month to monitor treatment response per the national algorithm. The last available isolate from the sputum collected at or after 4 months of bedaquiline was designated the follow-up isolate. Phenotypic drug susceptibility testing for bedaquiline was done on baseline and follow-up isolates in MGIT960 media (WHO-recommended critical concentration of 1 μg/mL). Targeted deep sequencing for Rv0678, atpE, and pepQ, as well as whole-genome sequencing were also done.FindingsIn total, 40 (31%) of 129 patients from an estimated pool were eligible for this study. Overall, three (8%) of 38 patients assessable by phenotypic drug susceptibility testing for bedaquiline had primary resistance, 18 (47%) gained resistance (acquired or reinfection), and 17 (45%) were susceptible at both baseline and follow-up. Several Rv0678 and pepQ single-nucleotide polymorphisms and indels were associated with resistance. Although variants occurred in Rv0676c and Rv1979c, these variants were not associated with resistance. Targeted deep sequencing detected low-level variants undetected by whole-genome sequencing; however, none were in genes without variants already detected by whole-genome sequencing. Patients with baseline fluoroquinolone resistance, clofazimine exposure, and four or less effective drugs were more likely to have bedaquiline-resistant gain. Resistance gain was primarily due to acquisition; however, some reinfection by resistant strains occurred.InterpretationBedaquiline-resistance gain, for which we identified risk factors, was common in these programmatically treated patients with sustained culture positivity. Our study highlights risks associated with implementing life-saving new drugs and shows evidence of bedaquiline-resistance transmission. Routine drug susceptibility testing should urgently accompany scale-up of new drugs; however, rapid drug susceptibility testing for bedaquiline remains challenging given the diversity of variants observed.FundingDoris Duke Charitable Foundation, US National Institute of Allergy and Infectious Diseases, South African Medical Research Council, National Research Foundation, Research Foundation Flanders, Stellenbosch University Faculty of Medicine Health Sciences, South African National Research Foundation, Swiss National Science Foundation, and Wellcome Trust.

Dataset Information

Tuberculosis in Cape Town: An age-structured transmission model.

Publications

Tuberculosis in Cape Town: An age-structured transmission model.

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