The Risk of Tuberculosis Reinfection Soon after Cure of a First Disease Episode Is Extremely High in a Hyperendemic Community.

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.

Towards eliminating bias in cluster analysis of TB genotyped data.

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). Naïve methods previously applied to the analysis of such data are known to provide biased estimates of the proportion of unclustered cases.

Transmission elasticity in communities hyperendemic for tuberculosis.

Background: Despite consistently meeting international performance targets for tuberculosis case detection and treatment success, areas where tuberculosis is hyperendemic fail to achieve the predicted epidemiological impact. In this article, we explore the anomalous relationship between defined performance targets and actual reduction in tuberculosis transmission.

Methods: In areas where tuberculosis is endemic, poorly ventilated social gathering places such as shebeens (informal alcohol drinking places), minibus taxis, and clinic waiting rooms are all potential transmission hot spots.

Tuberculosis transmission to young children in a South African community: modeling household and community infection risks.

Background: Tuberculosis transmission is determined by contact between infectious and susceptible individuals. A recent study reported a 4% annual risk of child tuberculosis infection in a southern African township. A model was used to explore the interactions between prevalence of adult tuberculosis infection, adult-to-child contacts, and household ventilation, which could result in such a high annual risk of tuberculosis infection.

Potential of rapid diagnosis for controlling drug-susceptible and drug-resistant tuberculosis in communities where Mycobacterium tuberculosis infections are highly prevalent.

The long-term persistence of Mycobacterium tuberculosis in communities with high tuberculosis prevalence is a serious problem aggravated by the presence of drug-resistant tuberculosis strains. Drug resistance in an individual patient is often discovered only after a long delay, particularly if the diagnosis is based on current culture-based drug sensitivity testing methods. During such delays, the patient may transmit tuberculosis to his or her contacts.

Tuberculosis reinfection rate as a proportion of total infection rate correlates with the logarithm of the incidence rate: a mathematical model.

In a significant number of instances, an episode of tuberculosis can be attributed to a reinfection event. Because reinfection is more likely in high incidence regions than in regions of low incidence, more tuberculosis (TB) cases due to reinfection could be expected in high-incidence regions than in low-incidence regions. Empirical data from regions with various incidence rates appear to confirm the conjecture that, in fact, the incidence rate due to reinfection only, as a proportion of all cases, correlates with the logarithm of the incidence rate, rather than with the incidence rate itself.

The effect of diagnostic delays on the drop-out rate and the total delay to diagnosis of tuberculosis.

Background: Numerous patient and healthcare system-related delays contribute to the overall delay experienced by patients from onset of TB symptoms to diagnosis and treatment. Such delays are critical as infected individuals remain untreated in the community, providing more opportunities for transmission of the disease and adversely affecting the epidemic.

Methodology/principal Findings: We present an analysis of the factors that contribute to the overall delay in TB diagnosis and treatment, in a resource-poor setting.

A threshold value for the time delay to TB diagnosis.

Background: In many communities where TB occurs at high incidence, the major force driving the epidemic is transmission. It is plausible that the typical long delay from the onset of infectious disease to diagnosis and commencement of treatment is almost certainly the major factor contributing to the high rate of transmission.

Methodology/principal Findings: This study is confined to communities which are epidemiologically relatively isolated and which have low HIV incidence.

TB epidemiology and human genetics.

The impact of tuberculosis (TB) is considerably lower than one may expect, since in the absence of immunosuppression, fewer than 10% of infected individuals will develop active disease. The relatively low proportion of individuals who progress to active disease after infection can probably be ascribed to innate resistance in most infected individuals, since vaccination using BCG or a previous episode of TB does not work reliably or effectively to confer protection in high burden parts of the world. Innate factors affecting resistance or susceptibility can be modulated by the environment and such external influences cannot be ignored.

On the nature of genetic changes required for the development of esophageal cancer.

It is clear that genetic mutations are necessary for the development of cancer, but the exact number required is not clear, with estimates ranging from one critical hit (e.g., p53) to dozens or perhaps even hundreds of expression changes (by microarray analysis) or chromosomal aberrations.