The Annual Burden of Seasonal Influenza in the US Veterans Affairs Population
Bibliographic record
Abstract
Seasonal influenza epidemics have a substantial public health and economic burden in the United States (US). On average, over 200,000 people are hospitalized and an estimated 23,000 people die from respiratory and circulatory complications associated with seasonal influenza virus infections each year. Annual direct medical costs and indirect productivity costs across the US have been found to average respectively at $10.4 billion and $16.3 billion. The objective of this study was to estimate the economic impact of severe influenza-induced illness on the US Veterans Affairs population. The five-year study period included 2010 through 2014. Influenza-attributed outcomes were estimated with a statistical regression model using observed emergency department (ED) visits, hospitalizations, and deaths from the Veterans Health Administration of the Department of Veterans Affairs (VA) electronic medical records and respiratory viral surveillance data from the Centers for Disease Control and Prevention (CDC). Data from VA's Managerial Cost Accounting system were used to estimate the costs of the emergency department and hospital visits. Data from the Bureau of Labor Statistics were used to estimate the costs of lost productivity; data on age at death, life expectancy and economic valuations for a statistical life year were used to estimate the costs of a premature death. An estimated 10,674 (95% CI 8,661-12,687) VA ED visits, 2,538 (95% CI 2,112-2,964) VA hospitalizations, 5,522 (95% CI 4,834-6,210) all-cause deaths, and 3,793 (95% CI 3,375-4,211) underlying respiratory or circulatory deaths (inside and outside VA) among adult Veterans were attributable to influenza each year from 2010 through 2014. The annual value of lost productivity amounted to $27 (95% CI $24-31) million and the annual costs for ED visits were $6.2 (95% CI $5.1-7.4) million. Ninety-six percent of VA hospitalizations resulted in either death or a discharge to home, with annual costs totaling $36 (95% CI $30-43) million. The remaining 4% of hospitalizations were followed by extended care at rehabilitation and skilled nursing facilities with annual costs totaling $5.5 (95% CI $4.4-6.8) million. The annual monetary value of quality-adjusted life years (QALYs) lost amounted to $1.1 (95% CI $1.0-1.2) billion. In total, the estimated annual economic burden was $1.2 (95% CI $1.0-1.3) billion, indicating the substantial burden of seasonal influenza epidemics on the US Veterans Affairs population. Premature death was found to be the largest driver of these costs, followed by hospitalization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".