{"title":"Estimating undiagnosed HIV infections by age group in Japan: an extended age-dependent back-calculation","authors":"Seiko Fujiwara , Hiroshi Nishiura , Takuma Shirasaka , Akifumi Imamura","doi":"10.1016/j.idm.2025.06.001","DOIUrl":null,"url":null,"abstract":"<div><div>Understanding the number of undiagnosed HIV-infected individuals by age is essential for improving the test-and-treat strategy. We developed an extended back-calculation by age group to investigate the situation in Japan, describing the data-generating process of AIDS cases and HIV diagnoses as a function of age and time. We considered the incubation period as a function of both age and time since infection, and estimated the number of new HIV infections and annual diagnosis rate by age and time. The diagnosed proportion of HIV infections at the end of 2022 was estimated to be 93.2 % (95 % CI: 90.2, 95.8) in their 20s, 90.4 % (95 % CI: 87.0, 93.7) in their 40s, 90.3 % (95 % CI: 86.9, 93.5) in their 50s or older, and 89.4 % (95 % CI: 85.1, 93.2) in their 30s. The annual rate of diagnosis of people in their 40s decreased from 16.9 % in 2015–2019 to 14.8 % in 2020–22. Despite increasing trend in diagnostic rate, the estimate for those in their 50s was as small as 13.6 % (95 % CI: 8.5, 19.4) in 2020–2022. We identified a difficulty in diagnosing HIV-infected individuals aged 40 and older. The absolute number of infections is greater among those in their 30s than 40s, but the AIDS incidence is the opposite, suggesting that older individuals would require more customized (and easy to access) opportunities for diagnosis.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 4","pages":"Pages 1116-1125"},"PeriodicalIF":8.8000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042725000491","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Understanding the number of undiagnosed HIV-infected individuals by age is essential for improving the test-and-treat strategy. We developed an extended back-calculation by age group to investigate the situation in Japan, describing the data-generating process of AIDS cases and HIV diagnoses as a function of age and time. We considered the incubation period as a function of both age and time since infection, and estimated the number of new HIV infections and annual diagnosis rate by age and time. The diagnosed proportion of HIV infections at the end of 2022 was estimated to be 93.2 % (95 % CI: 90.2, 95.8) in their 20s, 90.4 % (95 % CI: 87.0, 93.7) in their 40s, 90.3 % (95 % CI: 86.9, 93.5) in their 50s or older, and 89.4 % (95 % CI: 85.1, 93.2) in their 30s. The annual rate of diagnosis of people in their 40s decreased from 16.9 % in 2015–2019 to 14.8 % in 2020–22. Despite increasing trend in diagnostic rate, the estimate for those in their 50s was as small as 13.6 % (95 % CI: 8.5, 19.4) in 2020–2022. We identified a difficulty in diagnosing HIV-infected individuals aged 40 and older. The absolute number of infections is greater among those in their 30s than 40s, but the AIDS incidence is the opposite, suggesting that older individuals would require more customized (and easy to access) opportunities for diagnosis.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.