Decline in Respiratory Syncytial Virus Hospitalizations in a Region With High Hospitalization Rates and Prolonged Season
Bibliographic record
Abstract
BACKGROUND: During 1993 to 1996, Alaska Native infants <1 year of age from the Yukon Kuskokwim (YK) Delta in Alaska experienced a respiratory syncytial virus (RSV) hospitalization rate 5 times the U.S. general infant population rate. We describe trends in lower respiratory tract infection (LRTI) and RSV hospitalizations in YK children from 1994 to 2004. METHODS: We abstracted hospital dates, RSV test results and clinical information from the hospital records for YK children <3 years of age hospitalized between July 1994 and June 2004. RESULTS: : The RSV hospitalization rate in YK Delta children <1 year of age decreased from 178 per 1000 infants per year (1994-1997) to 104 per 1000 infants per year (2001-2004) (P < 0.001), and the RSV hospitalization rate for premature infants decreased from 317 to 123 per 1000 infants per year (P < 0.001). The risk reduction for RSV hospitalization was greater in premature (relative risk, 0.39) than in term infants (relative risk, 0.60; P = 0.04). The rate of non-RSV LRTI hospitalizations increased from 153 to 215 per 1000 infants per year (P < 0.001). The median RSV season length was 30.5 weeks. Pneumonia was diagnosed in more than half of RSV admissions. CONCLUSIONS: In YK infants, the RSV hospitalization rate decreased by one-third between 1994 and 2004; however, the overall LRTI hospitalization rate did not change. The median RSV season was twice as long as for the U.S. population. Palivizumab prophylaxis may be responsible for the larger decrease in the RSV hospitalization rate among premature infants; however, the 2001-2004 RSV hospitalization rate among YK infants remained 3 times higher than the U.S. infant rate.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".