{"doi":"10.1093/cid/ciaa857","title":"Model-based Cost-effectiveness of State-level Latent Tuberculosis Interventions in California, Florida, New York, and Texas","abstract":"BACKGROUND: Targeted testing and treatment (TTT) for latent tuberculosis (TB) infection (LTBI) is a recommended strategy to accelerate TB reductions and further TB elimination in the United States. Evidence on cost-effectiveness of TTT for key populations can help advance this goal. METHODS: We used a model of TB transmission to estimate the numbers of individuals who could be tested by interferon-γ release assay and treated for LTBI with 3 months of self-administered rifapentine and isoniazid (3HP) under various TTT scenarios. Specifically, we considered rapidly scaling up TTT among people who are non-US-born, diabetic, living with human immunodeficiency virus (HIV), homeless or incarcerated in California, Florida, New York, and Texas-states where more than half of US TB cases occur. We projected costs (from the healthcare system perspective, in 2018 dollars), 30-year reductions in TB incidence, and incremental cost-effectiveness (cost per quality-adjusted life-year [QALY] gained) for TTT in each modeled population. RESULTS: The projected cost-effectiveness of TTT differed substantially by state and population, while the health impact (number of TB cases averted) was consistently greatest among non-US-born individuals. TTT was most cost-effective among persons with HIV (from $2828/QALY gained in Florida to $11 265/QALY gained in New York) and least cost-effective among people with diabetes (from $223 041/QALY gained in California to $817 753/QALY in New York). CONCLUSIONS: The modeled cost-effectiveness of TTT for LTBI varies across states but was consistently greatest among people with HIV; moderate among people who are non-US-born, incarcerated, or homeless; and least cost-effective among people with diabetes.","journal":"Clinical Infectious Diseases","year":2020,"id":94305,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":38,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9174,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":469879,"name":"Sourya Shrestha","orcid":"0000-0002-6106-6834","position":1,"is_corresponding":false},{"id":469880,"name":"Isabella Gomes","orcid":"0000-0002-2594-2649","position":2,"is_corresponding":false},{"id":325517,"name":"Suzanne M. Marks","orcid":"0000-0003-3024-1940","position":3,"is_corresponding":false},{"id":364037,"name":"Andrew Hill","orcid":"0000-0002-7418-6456","position":4,"is_corresponding":false},{"id":470660,"name":"Garrett R. Beeler Asay","orcid":null,"position":5,"is_corresponding":false},{"id":315468,"name":"David W. Dowdy","orcid":"0000-0003-0481-7475","position":6,"is_corresponding":false},{"id":469878,"name":"Youngji Jo","orcid":"0000-0002-1440-2786","position":0,"is_corresponding":true}],"reference_count":33,"raw_metadata":null,"created_at":"2026-07-18T22:32:04.778261Z","pmid":"32584968","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}