NEEMA Funded Projects by Topic Area - Tuberculosis
NEEMA 2.0 (2019-2024)
While TB transmission rates have declined nationally in the US in the last two decades – owing largely to TB control efforts – ongoing transmission of TB, which can lead to sporadic outbreaks in select populations and communities (such as the homeless and incarcerated), remains an important priority for TB control. Previous studies described state-level models of TB transmission (and ongoing TB control) in the four most populous states, California, Florida, New York, and Texas. CDC has simultaneously developed an enriched database that includes both whole genome sequencing data and corresponding epidemiological links, which can be leveraged to inform TB controllers as to which cases that emerge as part of large outbreaks (>10 cases over a 3-year period) are genetically and epidemiologically linked. This project aims to merge these novel data with existing models of TB transmission to provide (i) better estimates of the impact of TB control efforts focused on preventing TB transmission, (ii) insights on how to improve our efforts on prevention of local TB transmission, and (iii) estimates of the efficiency and cost-effectiveness of using WGS and phylogenetic analysis to inform outbreak investigation.
The majority of TB cases in the US result from reactivation of latent TB infection (LTBI). For this reason, identifying and treating individuals with LTBI is a primary focus of TB prevention. Evidence suggests that LTBI reactivation rates vary according to age and time since infection, as well as the presence of individual risk factors associated with minor (smoking, diabetes, under-nutrition) or major (advanced HIV, ESRD) immune suppression. Estimates of current and future LTBI reactivation rates among populations are critical inputs for cost-effectiveness analyses of LTBI testing and treatment, as these rates determine the cumulative TB risk that can be averted by this intervention. Reactivation rates are also important inputs for analyses investigating the current status and future course of population-level TB epidemiology. Despite their importance, reactivation rate estimates for different US risk population are either unavailable or are relatively uncertain. This study will use a Bayesian evidence synthesis to estimate the distribution of likely reactivation rates for key TB risk populations. Furthermore, it will predict the future trajectory of these rates to estimate cumulative lifetime reactivation risks.
Information on the costs and health outcomes of TB services is important for national, state, and local TB decision-making. Agencies must understand the implications of policy and funding decisions, and allocate resources to maximize health impact, considering how different interventions should be targeted across risk populations. Locally-tailored evidence on the short- and long-term costs of TB and LTBI (as well as interventions to address these conditions) would also help local areas communicate the importance of TB prevention to local officials and media and advocate for the funding required to effectively address the burden of TB and LTBI. This work would extend the functionality of existing user-friendly tool Tabby2 by providing locally tailored results for all 50 states and the District of Columbia and by broadening the functionality of the tool to report future costs and cost-savings associated with TB and TB interventions.