Out of focus but still relevant? Influenza-related resource utilization and vaccination coverage gaps in adults below 60 years of age with underlying conditions: an analysis of 2016–2024 real-world data in Germany
Bibliographic record
Abstract
BACKGROUND: In 2003, the WHO aimed for a 75% or higher influenza vaccination rate among at-risk populations. However, this target was achieved in a few groups during selected seasons in some European countries, and never in Germany. Adults with underlying conditions (UCs) are a critical negleted group for influenza vaccination. This study aimed to identify data gaps in influenza burden and vaccination coverage among adults under 60 with UCs in Germany and bridge these gaps using real-world data. MATERIAL AND METHODS: We conducted systematic research and analyses using German administrative and claims databases from June 2016 to April 2024. We report on epidemiology, direct care costs, indirect costs from work incapacity, vaccination coverage rates, and describe data gaps. RESULTS: Influenza data for high-risk populations are limited. Comprehensive data on influenza epidemiology and vaccination coverage rates (VCR) is available, though with a delay in data availability. Before and after the pandemic, individuals aged 50-59 had the highest rates of influenza-related hospitalization and ICU admission compared to younger age groups. Across all age groups and seasons, individuals with UC experienced higher rates of medically attended influenza cases, hospitalizations, and healthcare costs, with those aged 35-59 being particularly vulnerable. Vaccine coverage was higher in adults aged 35-59 compared to those aged 18-24, and in females compared to males. LIMITATIONS: Discrepancies of vaccination status, limited data availability, and variations among the extent of UCs. CONCLUSION: In Germany, recent policy measures have mainly targeted those aged 60 and above. While this elderly population experiences the highest disease-related impact, influenza can also lead to substantial healthcare resource utilization (HCRU) and costs in younger populations with chronic UCs; Facilitating vaccination access for this group, such as through pharmacies, is essential. Definition of quantifiable vaccination targets and measures to increase vaccination rates based on these targets are required.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".