It is known that in high TB incidence settings the rate of recurrent TB disease is much higher than the rate for first-time disease. It is not clear why the rate of reinfection disease can be elevated compared to the rate of primary disease. We set about attempting to estimate the actual values of the risk of reinfection and the rate of progress to disease for the high-incidence community of Ravensmead-Uitsig in Cape Town.
A new case of TB is the outcome of a recent infection event (primary TB) or is the result of the reactivation of a latent infection acquired some years previously. In a community where TB is endemic it is important to know the extent to which primary cases contribute to the overall burden as this can inform strategies to deal with the epidemic. This article discusses the methods for estimating the proportion of cases due to recent transmission by using cluster analysis. Sputum specimens from cases reporting to clinics are cultured and the TB strains are identified, commonly using molecular techniques of DNA ‘fingerprinting’. By comparing these fingerprints from various patients it becomes possible to classify them as unique or clustered. The proportion of clustered individuals can then be used as an indicator of the proportion of on-going or recent transmission.
Transmission of tuberculosis (TB) involves random processes operating at two very different levels. On the one hand, an infectious person must be in reasonably close proximity to a susceptible person for a minimum period of time (macro-level). On the other hand, minute droplets containing bacteria entities that are exhaled by the infectious person are inhaled by the recipient (micro-level). At both these levels the chance events can be described by a statistical formula, the Poisson distribution. An analysis of these two processes in this way reveals a surprising phenomenon that manifests in communities experiencing high incidences of TB disease.
A significant contributing factor to the high incidence rates of tuberculosis (TB) in countries such as South Africa is the phenomenon of reinfection leading to further disease episodes. Researchers of SACEMA explored the relationship between incidence of TB and reinfection further by constructing a model that simulates the epidemiology of a TB endemic. This article describes the results of this analysis and recommendations based on these.