Evaluating health and economic effects of targeted strategies in TB/HIV
|Project Period||July 2015 to June 2020|
|Co-Principal Investigators||Ted Cohen (Yale) and Jason Andrews (Stanford)|
|Subcontract Institutions||Harvard T.H. Chan School of Public Health|
|Locations of interest||Democratic Republic of the Congo, Ethiopia, Kenya, Mozambique, Nigeria, Rwanda, South Africa, Tanzania and Zimbabwe|
Public Health Relevance: Global progress toward the control of tuberculosis (TB) is not on pace to meet post-2015 TB elimination strategy goals of 80% reduction in TB deaths, 60% reduction in TB incidence, and zero catastrophic costs for families affected by TB by 2030. Transmission dynamic modeling studies have concluded that these targets are unlikely to be reached in countries where the majority of global TB cases occur (i.e. India and China), even assuming substantial improvement in and scale up of existing approaches for TB control, including active case finding, access to new diagnostics and better treatment, and widespread use of preventive therapy .
This effort will constitute the first attempt to use WGS to fully understand TB transmission at the level of an entire high incidence country and to inform targeted interventions.
 Houben R et al. Feasibility of achieving the post-2015 Global TB Targets in South Africa, China and India: A combined analysis of 11 models. Lancet Global Health 2016.
DESCRIPTION : The HIV epidemic has triggered a sharp increase in the burden of tuberculosis (TB) in sub-Saharan Africa. An emerging consensus suggests that the conventional strategy for global TB control, based on passive identification of individuals with active pulmonary disease, may not be sufficiently aggressive to address HIV-fuelled TB epidemics. As a result, the World Health Organization has updated recommendations to support wider use of treatment for latent M. tuberculosis infection (TLTBI) and more active screening for TB disease, as two key components of a new strategic approach for control of HIV-associated TB epidemics. Community-randomized studies testing these strategies on a broad population-wide scale, have produced disappointing results thus far. We hypothesize that targeted use of TLTBI and active TB case-finding may prove more effective, and more cost-effective, than non-targeted use.
Our overall goal in this project is to use mathematical models of TB and HIV epidemics to examine this hypothesis and evaluate the comparative effectiveness and efficiency of alternative choices in the design and implementation of targeted strategies. Toward this goal our project has three specific aims: (1) To develop a detailed simulation model of TB/HIV co-epidemics and calibrate the model to 9 high burden countries in sub-Saharan Africa. (2) To use this model to identify strategies for effective and cost-effective use of targeted screening for active tuberculosis. (3) To use this model to identify strategies for effective and cost-effective use of targeted TLTBI. Mathematical models can provide a unique approach to consolidate information from available studies to compare the projected effects (and costs) of alternative strategies for targeting and combining screening interventions.
The models we propose aim to meet this critical need and supply new tools to inform development and revision of national and international strategies for deploying interventions that can maximize impact and value for money when used singly and in combination. We expect this study to provide essential information for policy makers and researchers seeking to identify key priorities and set targets for tuberculosis control in settings of high HIV prevalence. In addition to providing evidence with immediate relevance to policy, the approach developed in this study will provide a durable template for further analyses, including prospective assessment of other targeted or general TB control strategies; retrospective evaluation of the impact and cost- effectiveness of programs; and monitoring of progress towards key goals for reducing the burdens of TB and HIV in resource limited settings.