{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T17:33:11Z","timestamp":1785346391282,"version":"3.55.0"},"reference-count":39,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:00:00Z","timestamp":1750204800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>This study aimed to investigate the epidemiological characteristics and determinants of breakthrough varicella (BV) cases in student populations, identify key factors influencing breakthrough infection intervals, and provide recommendations for vaccination strategy optimization.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A retrospective analysis was conducted on varicella cases and vaccination records among students in Jiulongpo District, Chongqing (2019-2023). Descriptive epidemiology methods were employed to characterize BV cases, with linear regression modeling assessing correlations between post-vaccination breakthrough intervals, primary immunization age, and the interval between two doses.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among 970 BV cases (27.25% of total cases), significant difference was observed: (1) Temporal distribution exhibited bimodal epidemic peaks (May-June and October-December), with seasonal variation in breakthrough proportions (spring 28.35%, summer 25.33%, autumn 29.67%, winter 23.97%); (2) Geographic analysis revealed differential distribution across urban (28.07%), urban-rural fringe (23.04%), and rural areas (28.97%); (3) Population stratification showed highest proportions in kindergarten children (37.45%), followed by primary school (33.63%), middle school (24.75%), and high school students (6.87%). The linear regression analysis demonstrated that single-dose BV cases showed a negative correlation between post-vaccination breakthrough interval and primary immunization age (r=-0.384, P&amp;lt;0.05); two-dose BV cases exhibited dual negative correlations with both primary immunization age (r=-0.225, P&amp;lt;0.05) and the interval between two doses (r=-0.228, P&amp;lt;0.05).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The rising incidence of varicella breakthrough infections necessitates transitioning to a two-dose regimen. To reduce the risk of breakthrough infections in student populations, we recommend timely administration of the first varicella vaccine dose at 12 months of age, followed by a second booster dose as early as possible.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fimmu.2025.1594598","type":"journal-article","created":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:16:45Z","timestamp":1750220205000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Epidemiological characteristics of breakthrough varicella cases among students in Jiulongpo District, Chongqing: implications for vaccination 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