Browsing by Author "Uys, Pieter"

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    The risk of tuberculosis reinfection soon after cure of a first disease episode is extremely high in a hyperendemic community
    (Public Library of Science, 2015) Uys, Pieter; Brand, Hilmarie; Warren, Robin M.; Van der Spuy, Gian; Hoal, Eileen G.; Van Helden, Paul D.
    Elevated rates of reinfection tuberculosis in various hyperendemic regions have been reported and, in particular, it has been shown that in a high-incidence setting near Cape Town, South Africa, the rate of reinfection tuberculosis (TB) disease after cure of a previous TB disease episode is about four times greater than the rate of first-time TB disease. It is not known whether this elevated rate is caused by a high reinfection rate due, for instance, to living circumstances, or a high rate of progress to disease specific to the patients, or both. In order to address that question we analysed an extensive data set from clinics attended by TB patients in the high-incidence setting near Cape Town, South Africa and found that, in fact, the (average) rate of reinfection (as opposed to the rate of reinfection disease) after cure of a previous TB disease episode is initially about 0.85 per annum. This rate diminishes rapidly over time and after about ten years this rate is similar to the rate of infection in the general population. Also, the rate of progress to disease after reinfection is initially high but declines in subsequent years down to the figure typical for the general population. These findings suggest that the first few months after cure of a TB disease episode form a critical period for controlling reinfection disease in a hyperendemic setting and that monitoring such cured patients could pre-empt a reinfection progressing to active disease.
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    Towards eliminating bias in cluster analysis of TB genotyped data
    (PLOS One, 2012-03) Van Schalkwyk, Cari; Cule, Madeleine; Welte, Alex; Van Helden, Paul; Van Der Spuy, Gian; Uys, Pieter
    The relative contributions of transmission and reactivation of latent infection to TB cases observed clinically has been reported in many situations, but always with some uncertainty. Genotyped data from TB organisms obtained from patients have been used as the basis for heuristic distinctions between circulating (clustered strains) and reactivated infections (unclustered strains). Naıve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases. The hypergeometric distribution, which generates probabilities of observing clusters of a given size as realized clusters of all possible sizes, is analyzed in this paper to yield a formal estimator for genotype cluster sizes. Subtle aspects of numerical stability, bias, and variance are explored. This formal estimator is seen to be stable with respect to the epidemiologically interesting properties of the cluster size distribution (the number of clusters and the number of singletons) though it does not yield satisfactory estimates of the number of clusters of larger sizes. The problem that even complete coverage of genotyping, in a practical sampling frame, will only provide a partial view of the actual transmission network remains to be explored.