{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T16:56:04Z","timestamp":1791219364580,"version":"4.1.0"},"reference-count":68,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T00:00:00Z","timestamp":1778716800000},"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. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The COVID-19 pandemic significantly disrupted seasonal influenza dynamics. Understanding post-pandemic rebound patterns is crucial for optimizing future public health strategies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a comprehensive epidemiological analysis of multi-source surveillance data collected from Chaoyang District, Beijing, China, a representative core urban area, spanning 2015 to 2024. Data sources included: Influenza-like illness (ILI) surveillance records, virological results, and reported influenza cases. A segmented interrupted time-series (ITS) framework, utilizing generalized additive mixed models (GAMMs) with negative binomial distribution and AR (1) structure, characterized the disruption and post-pandemic shifts. This robust modeling approach quantified deviations from historical baselines. We also characterized epidemic seasonality, viral strain dominance, and calculated age-stratified rate ratios (RRs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Analysis of 2,468,817 ILI cases revealed a distinct \u201cincrease-suppression-resurgence\u201d pattern. The annual proportion of influenza-like illness (ILI%) exhibited a peak of 3.85% in 2019, subsequently declined to 2.29% during 2020\u20132022, and then rebounded to 4.42% in 2024. Segmented GAMM-AR(1) modeling demonstrated that pandemic-era ILI% remained consistently below counterfactual projections, succeeded by a substantial post-pandemic rebound (RR\u202f=\u202f1.72,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f0.001). The models also indicated a structural shift from stable historical seasonality toward highly non-linear temporal dynamics (edf\u202f=\u202f9.19,\n                      <jats:italic>p<\/jats:italic>\n                      \u202f&amp;lt;\u202f001), where typical winter epidemics were replaced by irregular outbreaks, followed by a prolonged 28-week season in 2023\u20132024. Virological surveillance consistently showed the absence of B\/Yamagata lineage detection after 2020. Notably, while children maintained the highest absolute incidence, adults (15\u201364\u202fyears) exhibited the most profound post-pandemic surge in relative risk (RR\u202f=\u202f8.43 vs. 2016\u20132019 baseline), significantly outpacing people over 65 (RR\u202f=\u202f3.53) and children (RR\u202f=\u202f3.28).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The COVID-19 pandemic was associated with a complex shift in influenza epidemiology, characterized by intensified post-pandemic activity, altered seasonality, and a disproportionate redistribution of reported burden toward working-age adults. This demographic shift likely reflects a combination of post-pandemic changes in healthcare-seeking behavior, surveillance sensitivity, and host-level biological factors, with potential contributions from population-level immune waning. The sustained absence of B\/Yamagata lineage detections aligns with global evidence of its probable extinction. These findings underscore the importance of age-stratified influenza monitoring and highlight the need for integrated serological, virological, and behavioral studies to elucidate the determinants of post-pandemic influenza burden.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1800701","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T05:34:57Z","timestamp":1778736897000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Suppression and resurgence: the evolving epidemiology of seasonal influenza from 2015 to 2024 in a core urban district of Beijing, China"],"prefix":"10.3389","volume":"14","author":[{"given":"Xing","family":"Gao","sequence":"first","affiliation":[{"name":"Institute of Medical Information\/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panpan","family":"Qin","sequence":"additional","affiliation":[{"name":"Institute of Medical Information\/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiao","family":"Qi","sequence":"additional","affiliation":[{"name":"Center for Disease Control and Prevention of Chaoyang District","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanli","family":"Wan","sequence":"additional","affiliation":[{"name":"Institute of Medical Information\/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiyuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Center for Disease Control and Prevention of Chaoyang District","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongpu","family":"Hu","sequence":"additional","affiliation":[{"name":"Institute of Medical Information\/Medical Library, Chinese Academy of Medical Sciences & Peking Union Medical College","place":["Beijing, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,14]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"e28888","DOI":"10.1002\/jmv.28888","article-title":"Change from low to out-of-season epidemics of influenza in China during the COVID-19 pandemic: a time series study","volume":"95","author":"Cao","year":"2023","journal-title":"J Med Virol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"ofaf493","DOI":"10.1093\/ofid\/ofaf493","article-title":"Changes to endemic respiratory virus circulation and testing before, during, and after the COVID-19 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