{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,12]],"date-time":"2026-07-12T02:32:40Z","timestamp":1783823560335,"version":"3.55.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T00:00:00Z","timestamp":1752710400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["U01 AI152087"],"award-info":[{"award-number":["U01 AI152087"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 AI130058"],"award-info":[{"award-number":["R01 AI130058"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["K24 AI182647"],"award-info":[{"award-number":["K24 AI182647"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Community-based active case finding (ACF) may reduce tuberculosis incidence and mortality but is not widely implemented due to resource constraints. How novel screening test characteristics would affect the impact and costs of ACF strategies is not clear.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed mathematical models of tuberculosis natural history and transmission, calibrated to data from 3 high tuberculosis burden countries (India, Vietnam, and the Philippines) and simulated the impact of annual community-based ACF programs. We compared annual screening, with or without an initial symptom screen, for 10 years with 2 hypothetical screening assays based on target product profile minimum targets: a low complexity (reaches 60% of the population) test with high sensitivity (90%) and moderate specificity (80%) costing $3; and a near point-of-care (reaches 80% of the population) test with moderate sensitivity (55%) and high specificity (98%) costing $2. We projected reductions in tuberculosis incidence, mortality, and costs under each scenario.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Annual screening with a low-complexity, high-sensitivity screening assay was projected to reduce tuberculosis mortality by 24%\u201338%, at an annual cost of $5.04\u2013$5.83 per capita. Annual screening with a near-point-of-care, moderate-sensitivity assay was projected to achieve comparable reductions in mortality (24%\u201342%) at $3.49\u2013$3.63 per capita. Symptom-based screening would yield more modest reductions in tuberculosis mortality (17%\u201324%) at an annual cost of around $1 per capita.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Near point-of-care, moderate-sensitivity screening assays for tuberculosis could achieve substantial impact on tuberculosis mortality\u2014equivalent to that of high-sensitivity assays and at lower cost\u2014if they can be performed at scale in community settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/cid\/ciaf395","type":"journal-article","created":{"date-parts":[[2025,7,17]],"date-time":"2025-07-17T10:08:29Z","timestamp":1752746909000},"page":"776-784","source":"Crossref","is-referenced-by-count":1,"title":["Projecting the Impact and Costs of Near Point-of-Care Tuberculosis Screening Assays in Community-based Active Case Finding"],"prefix":"10.1093","volume":"81","author":[{"given":"Jason R","family":"Andrews","sequence":"first","affiliation":[{"name":"Department of Medicine, Stanford University School of Medicine , Stanford, California ,","place":["USA"]},{"name":"Department of Global Health and Amsterdam Public Health, Amsterdam University Medical Centers Location University of Amsterdam , Amsterdam ,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emily A","family":"Kendall","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Johns Hopkins University School of Medicine , Baltimore, Maryland ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adithya","family":"Cattamanchi","sequence":"additional","affiliation":[{"name":"Division of Pulmonary Diseases and Critical Care Medicine, UC Irvine , Irvine, California ,","place":["USA"]},{"name":"UCSF Center for Tuberculosis, University of California San Francisco , San Francisco, California ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Claudia M","family":"Denkinger","sequence":"additional","affiliation":[{"name":"Department of Infectious Disease and Tropical Medicine, Heidelberg University Hospital , Heidelberg ,","place":["Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2811-1311","authenticated-orcid":false,"given":"Payam","family":"Nahid","sequence":"additional","affiliation":[{"name":"UCSF Center for Tuberculosis, University of California San Francisco , San Francisco, California ,","place":["USA"]},{"name":"Division of Pulmonary and Critical Care Medicine, University of California San Francisco , San Francisco, California ,","place":["USA"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sourya","family":"Shrestha","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Johns Hopkins Bloomberg School 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