{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T05:49:53Z","timestamp":1777009793622,"version":"3.51.4"},"reference-count":63,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T00:00:00Z","timestamp":1776297600000},"content-version":"vor","delay-in-days":15,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100008018","name":"Victorian Cancer Agency","doi-asserted-by":"publisher","award":["ECR20005"],"award-info":[{"award-number":["ECR20005"]}],"id":[{"id":"10.13039\/100008018","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008018","name":"Victorian Cancer Agency","doi-asserted-by":"publisher","award":["MCRF20049"],"award-info":[{"award-number":["MCRF20049"]}],"id":[{"id":"10.13039\/100008018","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cancer Medicine"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>The COVID\u201019 pandemic significantly disrupted colorectal cancer (CRC) diagnosis and treatment globally. Most research on long\u2010term impacts has focused on population\u2010level outcomes, overlooking disparities in under\u2010screened groups. This study examines the long\u2010term effects of COVID\u201019 disruptions on health inequalities and healthcare costs in Victoria, Australia.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A Markov microsimulation model (PRISM\u2010CRC), containing socioeconomic quintiles in Victoria, estimated health outcomes in a population aged 50\u201374\u2009years from 2023\u20132037. The model simulated the development of CRC, considering the expected population increase in CRC cases projected by the Victorian Cancer Registry (VCR) due to COVID\u201019 disruptions and counterfactual scenarios with no disruptions. The model estimated CRC case numbers, CRC deaths, and total costs of CRC screening and treatment by quintile. Screened status, stage of diagnosis, and survival were obtained using a dataset linked to patients diagnosed with CRC in 2009\u20132021 from the VCR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Post COVID\u201019, CRC cases and mortality increased across all quintiles, with the greatest impacts in the most disadvantaged groups. Quintile 2 showed the largest relative cancer cases increase (21.7%), followed by quintile 1 (16.3%), whilst quintile 5 increased only 1.2%. CRC deaths rose 30.1% in quintile 1 and 28% in quintile 2, compared to 1.6% in quintile 5. Combined screening, diagnostic testing and treatment costs increased 21.4% in quintiles 1 and 24.8% in quintiles 2, versus 3.4% in quintile 5. Overall, the post\u2010COVID\u201019 period intensifies the social gradient in CRC incidence, mortality, and healthcare costs.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Our study underscores the significant impact of COVID\u201019 disruptions on worsening cancer inequalities. Targeted CRC screening interventions are essential to protect vulnerable populations. Enhanced demographic data from screening programs will help better understand non\u2010participants and groups with low participation rates.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/cam4.71816","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T03:56:11Z","timestamp":1776398171000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Long\u2010Term Health and Economic Impacts of\n                    <scp>COVID<\/scp>\n                    \u201019 Disruptions on Bowel Cancer Inequalities in Victoria, Australia: A Modelling Study"],"prefix":"10.1002","volume":"15","author":[{"given":"Anita","family":"Lal","sequence":"first","affiliation":[{"name":"Deakin Health Economics Institute for Health Transformation, Deakin University  Geelong Victoria 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