The direct healthcare costs attributable to West Nile virus illness in Ontario, Canada: a population-based cohort study using laboratory and health administrative data
Bibliographic record
Abstract
Abstract Background West Nile virus (WNV) is a mosquito-borne flavivirus, first detected in the Western Hemisphere in 1999 and spread across North America over the next decade. Though endemic in the most populous areas of North America, few studies have estimated the healthcare costs associated with WNV. The objective of this study was to determine direct healthcare costs attributable to WNV illness in Ontario, Canada. Methods We conducted a cost-of-illness study on incident laboratory confirmed and probable WNV infected subjects identified from the provincial laboratory database from Jan 1, 2002 through Dec 31, 2012. Infected subjects were linked to health administrative data and matched to uninfected subjects. We used phase-of-care methods to calculate costs for 3 phases of illness: acute infection, continuing care, and final care prior to death. Mean 10-day attributable costs were reported in 2014 Canadian dollars, per capita. Sensitivity analysis was conducted to test the impact of WNV neurologic syndromes on healthcare costs. Results One thousand five hundred fifty-one laboratory confirmed and probable WNV infected subjects were ascertained; 1540 (99.3%) were matched to uninfected subjects. Mean age of WNV infected subjects was 49.1 ± 18.4 years, 50.5% were female. Mean costs attributable to WNV were $1177 (95% CI: $1001, $1352) for acute infection, $180 (95% CI: $122, $238) for continuing care, $11,614 (95% CI: $5916, $17,313) for final care - acute death, and $3199 (95% CI: $1770, $4627) for final care - late death. Expected 1-year costs were $13,648, adjusted for survival. Three hundred seventeen infected subjects were diagnosed with at least one neurologic syndrome and greatest healthcare costs in acute infection were associated with encephalitis ($4710, 95% CI: $3770, $5650). Conclusions WNV is associated with increased healthcare resource utilization across all phases of care. High-quality studies are needed to understand the health system impact of vector-borne diseases and evaluate the cost effectiveness of novel WNV interventions.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".