The cost of lower respiratory tract infections hospital admissions in the Canadian Arctic
Bibliographic record
Abstract
BACKGROUND: Inuit infants who reside in the Nunavut (NU) regions of Arctic Canada have extremely high rates of lower respiratory tract infections (LRTIs) associated with significant health expenditures, but the costs in other regions of Arctic Canada have not been documented. OBJECTIVE: This prospective surveillance compares, across most of Arctic Canada, the rates and costs associated with LRTI admissions in infants less than 1 year of age, and the days of hospitalization and costs adjusted per live birth. DESIGN: This was a hospital-based surveillance of LRTI admissions of infants less than 1 year of age, residing in Northwest Territories (NT), the 3 regions of Nunavut (NU); [Kitikmeot (KT), Kivalliq (KQ) and Qikiqtani (QI)] and Nunavik (NK) from 1 January 2009 to 30 June 2010. Costs were obtained from the territorial or regional governments and hospitals, and included transportation, hospital stay, physician fees and accommodation costs. The rates of LRTI hospitalizations, days of hospitalization and associated costs were calculated per live birth in each of the 5 regions. RESULTS: There were 513 LRTI admissions during the study period. For NT, KT, KQ, QI and NK, the rates of LRTI hospitalization per 1000 live births were 38, 389, 230, 202 and 445, respectively. The total days of LRTI admission per live birth were 0.25, 3.3, 2.6, 1.7 and 3 for the above regions. The average cost per live birth for LRTI admission for these regions was $1,412, $22,375, $14,608, $8,254 and $10,333. The total cost for LRTI was $1,498,232 in NT, $15,662,968 in NU and $3,874,881 in NK. Medical transportation contributed to a significant proportion of the costs. CONCLUSION: LRTI admission rates in NU and Nunavik are much higher than that in NT and remain among the highest rates globally. The costs of these admissions are exceptionally high due to the combination of very high rates of admission, very expensive medical evacuations and prolonged hospitalizations. Decreasing the rates of LRTI in this population could result in substantial health savings.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".