Browsing by Author "Marx, Florian Michael"

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    Mathematical modelling to project the impact of interventions targeted to previously treated individuals on the trajectory of the tuberculosis epidemic in high tuberculosis prevalence settings
    (Stellenbosch : Stellenbosch University, 2018-03) Marx, Florian Michael; Beyers, Nulda; Cohen, Theodore; Stellenbosch University. Faculty of Medicine and Health Sciences. Paediatrics and Child Health.
    ENGLISH ABSTRACT: Better strategies are needed to reduce Mycobacterium tuberculosis (M.tb) transmission in tuberculosis (TB) high-incidence settings. Targeting additional control interventions towards groups at highest TB risk may thereby constitute a reasonable approach to make best use of limited resources. One group considered at high TB risk are people with a history of previous TB treatment. In recent years, high rates of recurrent TB after successful TB treatment, frequently due to reinfection with another M.tb strain, have been reported from several highincidence settings. The extent to which previously treated people contribute to the overall TB burden in these settings, and whether control interventions targeted towards this high-risk group could help reduce transmission has not been established. The aim of the research presented in this dissertation was to characterise the risk of TB among people with a history of previous TB treatment, and to project the impact of control interventions targeted at this subgroup on the trajectory of TB epidemics in high-incidence settings. Towards this aim, I conducted a total of five studies, four of which are based on traditional epidemiological analysis (Chapters 2,3, and 5,6), and one used a transmission-dynamic mathematical model (Chapter 4). Two studies were based on routine TB program data from a high-incidence setting in suburban Cape Town. The first aimed at estimating the rate of re-treatment for smear-positive TB dependent on whether individuals had completed their previous TB treatment (Chapter 2). For the second, I used M.tb strain-type DNA fingerprinting data for a subset of patients re-treated for recurrent smear-positive TB to investigate the relationship between the type of recurrence, i.e. endogenous reactivation (relapse) or exogenous reinfection, and the time to recurrent smear-positive TB (Chapter 3). I found, among 2,136 smear-positive TB patients, a high rate of re-treatment for smear-positive TB among those who had been lost to follow-up from treatment (6.86 [5.59-8.41] per 100 PYRS). By the end of the second year 28% had been diagnosed again with smear-positive TB. The rate was 3-5-times higher (aHR: 3.97 [3.00 - 5.26]) than after treatment success (cure: 2.09 [1.81-2.41]). Among those who had successfully completed TB treatment, the rate of smear-positive TB was at least 4-times higher than the estimated rate of new smear-positive TB in this setting. Individuals after successful treatment accounted for the majority (68%) of TB patients re-treated for smear-positive TB (Chapter 2). Exogenous reinfection was the underlying mechanism of disease recurrence in 66 (51%) of 130 individuals re-treated for smear-positive TB after previous treatment success. The proportion did not change after restricting the analysis to individuals with documented HIVnegative test results (27 [51%] reinfections of 53 recurrences). The rate of relapse was highest 4-5 months after treatment completion, whereas the rate of reinfection TB dominated after the first year and remained high for several years (Chapter 3). I then used a calibrated transmission-dynamic mathematical model to project the populationlevel impact of interventions targeted at previously treated people in the same high-incidence setting. The interventions modelled were annual targeted active case finding (TACF) and secondary isoniazid preventive therapy (2°IPT) among people who had successfully completed TB treatment. The model projected that, under current control efforts, local TB incidence will remain in slow decline for at least another decade in this setting, and that interventions targeted at previously treated people would greatly accelerate this decline. Annual TACF combined with 2°IPT was projected to avert 40% (20%-59%) of incident TB cases and 41% (16%-62%) of TB deaths estimated to occur in the local population between 2016 and 2025 (Chapter 4). While the previous 3 studies (Chapters 2-4) had focussed on a particular TB high-incidence setting in suburban Cape Town, I conducted two further studies to explore whether specific characteristics of previously treated TB observed in suburban Cape Town extend to other highincidence settings in Southern Africa. I analysed TB prevalence survey data for more than 64,000 adults in 8 South African and 16 Zambian communities, to estimate TB prevalence stratified by history of previous TB treatment, and to investigate the extent to which previously treated people contributed to the overall prevalent TB burden. The study revealed a high prevalence of bacteriologically-confirmed TB among previously treated people in the 8 South African (overall: 3.81% [95%CI 3.25%–4.47%]) and the 16 Zambian (1.01% [95%CI: 0.65%–1.55%]) communities. Previously treated people accounted for 20.7% and 10.4% of prevalent TB cases in the South African and Zambian communities, respectively, and for more than 20% in 9 of the 24 communities overall (Chapter 5). Finally, I made use of electronic TB register data from the 52 South African health districts to investigate the proportion of previously treated individuals among notified TB patients treated for bacteriologically-confirmed TB in 2011. The study showed that the proportion of previously treated TB varied in the 52 health districts between 7.6% and 40%. The proportion exceeded 20% in 17 of the 52 districts. Higher proportions of previously treated TB correlated with higher TB case notification rates (r=0.75; P<0.001) and lower estimates of HIV prevalence (r=-0.45; P<0.001) in the districts (Chapter 6). In conclusion, this research documents high rates of TB after previous loss to follow-up from treatment and after treatment success in a high-incidence setting. People who previously completed TB treatment constitute the majority of smear-positive TB re-treatment patients, suggesting that efforts to ensure treatment adherence alone are unlikely to be sufficient to reduce the TB burden among previously treated people. Our study is consistent with earlier findings from this setting that reinfection contributes considerably to recurrent TB, even among HIV-uninfected individuals. I document for the first-time distinct temporal dynamics of relapse and reinfection TB. These dynamics suggest that sampling bias/differences in follow-up time is likely to explain the substantial variation in the contribution of reinfection to disease recurrence reported in observational studies. High rates of reinfection TB over a lengthy time after treatment completion suggest that the performance of TB treatment alone is unlikely to explain the high burden of recurrent TB in this setting. I used a transmission-dynamic mathematical model to address the idea of a targeted control strategy at a time when novel strategies are urgently needed to reduce transmission and the TB burden in populations most severely affected by TB. The model suggests considerable public health potential for TB control interventions targeted at previously treated people in this high-incidence setting. I identified several other high-incidence communities (and districts) where previously treated individuals contribute considerably to the prevalent and incident (notified) TB burden, and where interventions in this high-risk group might be relevant. This work represents only a first step towards evaluating the potential of this targeted control approach. Further research will be necessary to determine the feasibility, impact and costeffectiveness of targeting interventions towards previously treated people for reducing transmission and the TB burden in high-incidence settings.