Expanding ART coverage to healthier HIV patients is widely regarded as a potential strategy for addressing the rampant TB epidemic in high HIV-TB burden settings. Estimating the population-level impact of ART expansion on TB disease has proven challenging. We set out to estimate the potential effects of changing HIV treatment policy on TB outcomes in South Africa, comparing the results of three independent TB models. This project was part of a broader effort to shed light on the consequences of HIV policy changes, through model comparison and consensus building, a process pioneered in the HIV modelling field by the HIV Modelling Consortium.
There are few students in epidemiological modeling and analysis who can resist the temptation to fit a theoretical disease model to real epidemic data. A recent DNA fingerprinting project from Masiphumelele, a township near Cape Town, offered such a temptation. The result is a short journey into the world of statistically rare events, in this case brought about by the relatively small size of Masiphumele and by the slow reactivation rates of TB.
The focus of this paper is to evaluate PrEP alongside ART and condom-use interventions in South Africa, informed by national HIV and demographical surveys. The age-structured model we developed pays close attention to the distribution of relative infection risks between age categories. It includes dynamical effects usually not explicitly modelled, such as age-dependent condom use and partner choice. Despite some the limitations of the model, the model offers a relatively simple approach to studying the impact of PrEP in the context of national and generalized HIV epidemics. The inclusion of an age variable offers a direct way of studying age-structured prioritising strategies.