{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T08:44:00Z","timestamp":1782981840329,"version":"3.54.5"},"reference-count":55,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["Vaccine Impact Modelling Consortium [Grant Number"],"award-info":[{"award-number":["Vaccine Impact Modelling Consortium [Grant Number"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001125","name":"gavi alliance","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001125","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100023693","name":"vaccine impact modelling consortium","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100023693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["MDM Policy &amp; Practice"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Implementation delays reduce population-level effects of evidence-based interventions. We conducted a modeling study to estimate the effect of priority policy decisions on a human papillomavirus (HPV) vaccination program in Kenya.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>We used a static cohort model to estimate the health effects and costs of introduction and 1-dose switch delays, switching to nonavalent vaccine (9vHPV), supply disruptions, and various scale-up scenarios. Costs were evaluated from the health system perspective. We estimated cervical cancer cases, deaths, disability-adjusted life-years (DALYs), and program and health care costs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>Compared with no vaccination, maintaining current program performance would avert approximately 173,000 (95% UI: 149,000\u2013191,000) cases and 2.7 (2.3\u20133.0) million DALYs across 2019 to 2100. A gradual scale-up of the current 2-dose quadrivalent vaccine (4vHPV) program would avert an additional 16,000 (14\u201318,000) cases (9%), increasing to 33,000 (28\u201337,000) cases (19%) if a multiage catchup is implemented in 2030. Accelerated scale-up of 1-dose bivalent vaccine (2vHPV) would avert 184,000 (164\u2013199,000) cases and 3.0 (2.6\u20133.2) million DALYs, compared with no vaccination; translating to an additional 11,000 (2\u201317,000) cases averted (6%) compared with maintaining a 2-dose strategy, but at lower program ($81\u2009million vs $76\u2009million) and treatment costs ($2.09\u2009billion vs $2.07\u2009billion). HPV vaccination introduction in 2015 rather than 2019 would have averted an additional 74,000 (43%) cases. Annual vaccine supply disruptions translates to less than 9,000 (200\u201316,000) cases (5%) and 212,000 (74\u2013305,000) DALYs averted (7%) compared with a 1-dose strategy. A 1-dose 9vHPV strategy would have more health benefits and save additional treatment costs compared with a 1-dose 2vHPV vaccine.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions:<\/jats:title>\n                    <jats:p>Prompt 1-dose switch and rapid scale-up and adoption of a 9vHPV program should be priority policy decisions for Kenya.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/23814683261456695","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T06:36:17Z","timestamp":1782801377000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Impact of Implementing Alternative Human Papillomavirus (HPV) Vaccination Strategies in Kenya: A Modeling Study"],"prefix":"10.1177","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1956-7440","authenticated-orcid":false,"given":"Valerian","family":"Mwenda","sequence":"first","affiliation":[{"name":"ThinkWell, Nairobi, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joan-Paula","family":"Bor","sequence":"additional","affiliation":[{"name":"National Cancer Control Program, Ministry of Health, Nairobi, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rose","family":"Jalang\u2019o","sequence":"additional","affiliation":[{"name":"National Vaccines and Immunization Program, Ministry of Health, Nairobi, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne","family":"Musuva","sequence":"additional","affiliation":[{"name":"ThinkWell, Nairobi, Kenya"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8467-1324","authenticated-orcid":false,"given":"Allison","family":"Portnoy","sequence":"additional","affiliation":[{"name":"Department of Global Health, Boston University School of Public Health, Boston, MA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,6,29]]},"reference":[{"key":"e_1_3_3_2_2","unstructured":"World Health Organization. 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