Modeling the implementation of population-level isoniazid preventive therapy for tuberculosis control in a high HIV-prevalence setting.

BACKGROUND: We model the epidemiological impact of providing isoniazid preventive therapy (IPT) to South African adolescents, among whom HIV prevalence is low, latent tuberculosis (TB) prevalence is high, and school-based programs may enable population-level coverage. METHODS: We simulate a dynamic compartmental model of age-structured HIV and TB coepidemics in South Africa. HIV dynamics are modeled by infection status, CD4 cell count, and antiretroviral therapy; TB dynamics are modeled by disease stage, diagnosis, treatment, and IPT status. We analyze the effects of continuous IPT coverage among adolescents from 5 (baseline) to 90%. RESULTS: Our model is calibrated to WHO and the Joint United Nations Programme on HIV/AIDS epidemiological estimates. In simulations, increasing IPT coverage to 50% among adolescents reduced active TB incidence by 5-34%. Increasing coverage to 90% led to a 9-40% reduction in active TB incidence. Expanded IPT access causes TB incidence to decline in the general population of HIV-positive individuals, as well as in adult HIV-positive individuals. CONCLUSION: Targeting IPT to a secondary school population with high latent TB prevalence and low-HIV prevalence, in which risk of false-negative diagnosis of active TB is low and IPT benefits are more established, could have substantial benefits to adolescents and spillover benefits to the adult population.

Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: a combined analysis of 11 mathematical models.

BACKGROUND: The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements. METHODS: 11 independently developed mathematical models of tuberculosis transmission projected the epidemiological impact of currently available tuberculosis interventions for prevention, diagnosis, and treatment in China, India, and South Africa. Models were calibrated with data on tuberculosis incidence and mortality in 2012. Representatives from national tuberculosis programmes and the advocacy community provided distinct country-specific intervention scenarios, which included screening for symptoms, active case finding, and preventive therapy. FINDINGS: Aggressive scale-up of any single intervention scenario could not achieve the post-2015 End TB Strategy targets in any country. However, the models projected that, in the South Africa national tuberculosis programme scenario, a combination of continuous isoniazid preventive therapy for individuals on antiretroviral therapy, expanded facility-based screening for symptoms of tuberculosis at health centres, and improved tuberculosis care could achieve a 55% reduction in incidence (range 31-62%) and a 72% reduction in mortality (range 64-82%) compared with 2015 levels. For India, and particularly for China, full scale-up of all interventions in tuberculosis-programme performance fell short of the 2025 targets, despite preventing a cumulative 3·4 million cases. The advocacy scenarios illustrated the high impact of detecting and treating latent tuberculosis. INTERPRETATION: Major reductions in tuberculosis burden seem possible with current interventions. However, additional interventions, adapted to country-specific tuberculosis epidemiology and health systems, are needed to reach the post-2015 End TB Strategy targets at country level. FUNDING: Bill and Melinda Gates Foundation.

The role of sex differences in the prevalence and transmission of tuberculosis.

Tuberculosis (TB) epidemiology is characterized by significant differences in prevalence between men and women worldwide, with cases among men exceeding those found in women by a ratio of 2:1 in some regions. In this paper, we review the literature concerning differences in TB prevalence by sex, as well as arguments that have been offered to explain these differences. We conclude that, while underreporting and latent variables undoubtedly bias the observed differences in prevalence between males and females to some degree, there is also strong evidence that sex-based differences in TB prevalence represent real epidemiological differences. Such differences have implications for models of TB dynamics in countries with skewed population sex ratios such as China and India, and should be incorporated into models for TB control and forecasting.