ArticlemedRxiv : the preprint server for health sciences2026
Age as a Leading Indicator: A Multi-Outcome Analysis of Influenza Lead-Lag Relationships.
Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
5 authors.
Funding
Abstract
Prior work has shown that school-age children's influenza activity precedes that of adults by one to two weeks. Whether this is robust across outcomes or constant across a season's course is unexamined. Using electronic health record data from two health systems in South Carolina (2016-2026) on individuals with an influenza diagnosis or positive test, we tested age-group lead-lag relationships across six measures using differenced cross-correlation and Granger causality, with significance confirmed via heteroskedasticity-robust block permutation. We tested whether relationships differed between a season's growth and decline phases. Children 5-17 years led every other age group by approximately one week in four out of six outcomes and were the only group showing any nonzero-lag relationship across 60 pairwise combinations. A screen of 150 source-target combinations identified 26 permutation-confirmed instances of children's lower-acuity activity preceding elevated emergency department or inpatient burden in other age groups. The same-outcome lead was concentrated during a season's growth phase, while the cross-severity lead was robust throughout both a season's growth and decline. School-age children's influenza activity is a robust, multi-outcome leading indicator with distinct transmission-timing and severity-progression signals in different phases of seasonal epidemics, supporting incorporation of age-stratified, phase-aware indicators into influenza forecasting.
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Registered trials
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