{"doi":"10.5588/ijtld.22.0567","title":"Cost to perform door-to-door universal sputum screening for TB in a high-burden community","abstract":"BACKGROUND: Population-based active case-finding (ACF) identifies people with TB in communities but can be costly. METHODS: We conducted an empiric costing study within a door-to-door household ACF campaign in an urban community in Uganda, where all adults, regardless of symptoms, were screened by sputum Xpert Ultra testing. We used a combination of direct observation and self-reported logs to estimate staffing requirements. Study budgets were reviewed to collect costs of overheads, equipment, and consumables. Our primary outcome was the cost per person diagnosed with TB. RESULTS: Over a 28-week period, three teams of two people collected sputum from 11,341 adults, of whom 48 (0.4%) tested positive for TB. Screening 1,000 adults required 258 person-hours of effort at a cost of US$35,000, 70% of which was for GeneXpert cartridges. The estimated cost per person screened was $36 (95% uncertainty range [95% UR] 34–38), and the cost per person diagnosed with Xpert-positive TB was $8,400 (95% UR 8,000–8,900). The prevalence of TB in the underlying community was the primary modifiable determinant of the cost per person diagnosed. CONCLUSION: Door-to-door screening can be feasibly performed at scale, but will require effective triage and identification of high-prevalence populations to be affordable and cost-effective.","journal":"The International Journal of Tuberculosis and Lung Disease","year":2023,"id":361799,"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":8,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9504,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":316277,"name":"Olga Nakasolya","orcid":null,"position":1,"is_corresponding":false},{"id":316278,"name":"David Isooba","orcid":null,"position":2,"is_corresponding":false},{"id":316276,"name":"James Mukiibi","orcid":null,"position":3,"is_corresponding":false},{"id":315462,"name":"Peter James Kitonsa","orcid":"0000-0003-2971-216X","position":4,"is_corresponding":false},{"id":316275,"name":"Kamoga Caleb Erisa","orcid":null,"position":5,"is_corresponding":false},{"id":315463,"name":"Annet Nalutaaya","orcid":"0000-0003-3903-303X","position":6,"is_corresponding":false},{"id":315465,"name":"Katherine Robsky","orcid":"0000-0001-7789-5779","position":7,"is_corresponding":false},{"id":1114572,"name":"Olivia Ferguson","orcid":"0000-0002-3661-6822","position":8,"is_corresponding":false},{"id":315461,"name":"Emily A. Kendall","orcid":"0000-0002-0083-422X","position":9,"is_corresponding":false},{"id":864652,"name":"Haewon Sohn","orcid":"0000-0002-5126-0676","position":10,"is_corresponding":false},{"id":315467,"name":"Achilles Katamba","orcid":"0000-0002-2347-4183","position":11,"is_corresponding":false},{"id":315468,"name":"David W. Dowdy","orcid":"0000-0003-0481-7475","position":12,"is_corresponding":false},{"id":315464,"name":"Yeonsoo Baik","orcid":"0000-0001-7016-0438","position":0,"is_corresponding":true}],"reference_count":16,"raw_metadata":null,"created_at":"2026-07-19T01:14:15.063476Z","pmid":"36855034","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":[]}