Examining the Impact, Cost and Cost Effectiveness of Targeted Testing and Treatment for Latent Tuberculosis Infection in Key Populations

California, Texas, Florida and New York as case studies

This site shows results of a mathematical model of the impact and cost-effectiveness of targeted testing and treatment (TTT) for latent tuberculosis infection (LTBI) among key populations in the four most populous US states.

For reference, please see:

Cherng ST, Shrestha S, Reynolds S, Hill AN, Marks SM, Kelly J, Dowdy DW. A Four-State Example of State-Level Differences in Tuberculosis Incidence among Populations at High Risk. American Journal of Public Health. 2018 Supplement 4;108(S4):S311-S314. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6215364/

Jo Y, Shrestha S, Gomes I, Marks S, Hill A, Asay G, Dowdy D. Model-based cost-effectiveness of state-level tuberculosis interventions in California, Florida, New York and Texas. Under review.

Clicking on the 'impact' tab will show estimated reductions in TB incidence that can be achieved by testing and treating key populations for LTBI.

Clicking on the "cost" tab will show the estimated cost of TTT among key populations in each state.

Clicking on the "cost effectiveness" tab will show the estimated cost-effectiveness of TTT among key populations in each state.

508 Accessibility of this Product

Section 508 requires Federal agencies, including grantees, and contractors to ensure that individuals with disabilities who are members of the public or Federal employees have access to and use of electronic and information technology (EIT) that is comparable to that provided to individuals without disabilities, unless an undue burden would be imposed on the agency.

The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the CDC or other authors’ affiliated institutions.

This project was funded by the U.S. Centers for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention Epidemiologic and Economic Modeling Agreement (NEEMA, # 5U38PS004646).

If you need assistance, please contact jpennin6@jhu.edu.