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Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2026,6,30]]},"abstract":"<jats:p>\n                    Every year, over 700,000 people, particularly children under five, die from vector-borne diseases worldwide. Effectively controlling endemics and preventing new outbreaks requires an integrated approach that can lead to the elimination of both vectors and diseases. In the last two decades, integrating medical interventions and vector control has significantly reduced the incidence of Gambian Human African Trypanosomiasis (g-HAT), with the World Health Organization validating eight countries as having eliminated the disease as a public health problem. However, elimination of the tsetse vector has not been confirmed, leaving the possibility of re-emergence. We developed a six-step modeling framework to assess vector elimination by calculating: i) the probability of vector capture; ii) the probability of observing a series of zero catches, even without actual elimination; iii) the probability of natural elimination; iv) the probability of failing to detect a rebound; v) the reinvasion risk; and vi) the sensitivity analysis. Our case study is g-HAT in Mandoul, Chad, and the elimination of\n                    <jats:italic toggle=\"yes\">Glossina fuscipes fuscipes.<\/jats:italic>\n                    We used vector control from 2014 to 2025 with no tsetse detected since 2018. We cannot yet conclude, with over 90% confidence, that tsetse has been eliminated from Mandoul, nor that any remnant population will be naturally eliminated. However, since vector control stopped in April 2025, we estimate that with continued sampling over the next 2 y, and no tsetse detected, elimination could be demonstrated with 99% confidence. Our multistep modeling framework can be applied to other vectors, providing policymakers with guidelines for ongoing and future efforts.\n                  <\/jats:p>","DOI":"10.1073\/pnas.2524729123","type":"journal-article","created":{"date-parts":[[2026,6,23]],"date-time":"2026-06-23T18:06:47Z","timestamp":1782238007000},"update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":1,"title":["Modeling framework to demonstrate elimination of a vector population: Tsetse elimination in Chad"],"prefix":"10.1073","volume":"123","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0346-5260","authenticated-orcid":false,"given":"John","family":"Hargrove","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/05bk57929","id-type":"ROR","asserted-by":"publisher"}],"name":"South African Centre for Epidemiological Modelling and Analysis, Centre for Epidemic Response and Innovation, School for Data Science and Computational Thinking, 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